It also followed a day-in-the-life of a robotics developer (named Maya) and a stressful one at that; fumbling and bumbling her way through the lifecycle of robotics data, i.e. a physical AI ‘data flywheel’.

Today, we’re blasting Maya into the future.

This is what it feels like when the data flywheel runs itself.

Enjoy.

PS: When I first wrote this, it was before the release of agentic tools like OpenClaw. Suddenly, this stuff is not nearly as sci-fi as you might think. Much of ‘2033’ will likely be pulled into 2028-29, if not sooner.

Robots-as-a-Service

Maya was an entrepreneur and the kind the world needed to see.

She set the standard for what’s possible in the age of AI. Rather, the age of embodied-AI. The age of near-infinite leverage.

Turns out, companies didn’t make huge headcount cuts. They empowered existing headcount to do more. Much, much more. This IKEA example from 2026 set the stage.

Entrepreneurs did the same, and in robotics, Maya became the shining example.

A roboticist by trade, an agentic tinkerer by night, Maya caught one of AI’s largest waves: owning and managing her own fleet of robots for industrial tasks. Similar to the trucking or large equipment rental business.

Of course, most Fortune 500’s owned their own fleets, with the in-house capability to post-train, deploy, and orchestrate across their infrastructure (factories, warehouses, refineries, you name it).

But the SMB market? A much different story. They needed to outsource and Maya was primed for the opportunity. Texas was a honey pot of small manufacturers and logistics firms. She seized it.

But Maya was also a mom and the kind who refused to succumb to the status quo of choosing between family or work.

With infinite leverage machines, she could do both. Here’s how.

8am: Observe & Collect Experience

Maya’s day doesn’t start with code. And it certainly doesn’t involve alarming Slack messages from her client’s warehouse team.

It starts with the warm embrace of her daughter and giggling laughter in bed.

It then follows with a friend; as Maya steps into her office, a cute little droid rolls in behind her, hand delivering a fresh and foamy latte.

She takes a sip and slips on her glasses. A small display lights up inside the lenses.

“Thanks Bill. Can you show me last nights report?”

Maya’s AR glasses come to life, displaying an immersive array of insights.

It’s not rows of raw robot logs and file names. It’s a clean list of actual events; various failures, anomalies, and edge cases, all detected automatically; a stumble here, a dropped package there, and a surprising number of wrong turns.

Her main KPI in the top right corner is yellow.

The average package transport time has dipped a few seconds. Not good, especially with the holidays right around the corner.

“Bill, show me the failure events with the longest time to recovery and then replay the top three scenes.”

A timestamp floats out of the report: 2:17am Event: Package dropped. Recovery time: 14.3 seconds. Type: Rare and emerging.

Immediate context, on demand.

“Play event.”

Her glasses switch into VR mode. Suddenly, Maya is the robot, reliving its experience.

As expected, each scene showed the same thing; a stack of boxes that were left in the rain, all slippery as can be.

The good old fashion sim-2-real gap strikes again.

9:30am: Understand the Gaps

“Bill, what are you seeing here? Where is the model falling short?”

The scene collapses and Maya is back in her office. Three holographic panels appear, each one replaying a different version of the failure.

“I’ve clustered the incidents,” he says, his voice chirpy and calm. “Eighty-two percent correlate with low-friction surface conditions after rainfall. This scenario is underrepresented in both your real-world dataset and simulation corpus.”

A 3D heatmap blooms into her field of view. It’s not just a spatial dashboard. It’s a diagnosis.

Red islands mark blind spots in the model’s experience. Yellow gradients show where performance degrades gracefully. Green shows confidence.

“So what changed?” Maya asks.

“Humidity,” Bill replies. “The model has insufficient exposure to wet-surface interactions at this humidity level, with these payload weights. And looking ahead... These conditions are going to persist on and off for the next week.”

Maya sat back and smiled.

She remembered the days of manually searching a data lake, knee-deep in SQL queries and half-broken scripts, trying to guess what the robot hadn’t seen enough of.

Now for the fun part…

10am: Creating the Right Experience

“Okay Bill, let’s fix this. Do we have the right 3D assets and physics parameters in our sim?”

A rotating saucer appears.

Numerous 3D models of cardboard boxes are displayed on top, each slightly soggy and deformed. Quite the desert plate.

“Here are the current assets in our library,” Bill says

Something is off. The boxes in the videos were a different shape, size, and color.

“Ah, forgot we got a new box vendor! Bill, extract images of the boxes and let’s GSplat ‘em”

“On it.”

Maya looks over to the video panels. A shimmering line traces the new boxes and pops them out like a cookie cutter. The images blur, spin, and voila: what was once a 2D image is now a perfect 3D model, with the exact same texture and lighting as the boxes in the video.

“Great. Now let’s optimize the physics engine and create the scene,” Maya commands.

“A step ahead of you. Here’s the plan.”

The 3D models and videos disappear. In their place, a workflow diagram, showing all the detected gaps and steps Bill took to fill them; new box material with new friction coefficients, new payload mass, new actuator latency to match the warm, damp motors.

“Great. Now randomize the domains across 10,000 different variations.”

A new report surfaces. Each scenario is parameterized, ranked, and tagged with an estimated learning yield.

These aren’t one-off virtual worlds anymore. They’re flexible experiences the system can probe and stretch. Now, the digital robot doesn’t just repeat the same failure; it explores all the variations around it.

In the past, Maya had to sit with a team of 3D developers, hand-authoring edge cases based on intuition and experience, hoping she’d imagined the right failures.

Now, simulation isn’t driven by imagination. It’s driven by evidence.

“Run the top tier of scenarios,” she says. “Stop when marginal gains flatten.”

“Already planned,” Bill replies. “Simulation will terminate once gradient contribution drops below threshold. Should take 127 minutes”

The parallelized simulations spin up automatically, along with all of the supporting cloud infrastructure; not as a bespoke experiment, but as a service the system knows how to use.

10:30am: Data Evaluation

Maya steps out for a walk with her husband; a refreshing stroll along the lake near their house. They grab a lite bite and toss bread to a family of waddling ducks.

As they wrap and head home, her device buzzes. She throws on her glasses.

“Hi Maya, beautiful day isn’t it? A quick update: the simulations and data parsing are complete.”

A 3D graph materializes on her horizon. Thousands of simulated trajectories appear, and just as quickly, most of them vanish.

Maya watches a thin curve chart downward as the system discards the majority of simulation runs. Only four percent survive.

“Redundant trajectories removed,” Bill narrates. “Retaining only samples that expand the AI model policy boundary or introduce novel recovery behavior.”

Each clip of the simulations has a short annotation. Things like ‘boundary condition’, ‘compounding failure’, ‘rare recovery’.

In the old world, Maya had to hoard all synthetic data because curation was painfully manual. Now, the curation is automatic and ruthless.

For the first time in her career, she has less data and more confidence.

She also has more time. When she gets home, she takes her daughter to music class and joins in on the musical fray, reliving her first-grade glory days on the recorder.

1pm: Time to Learn

When Maya gets home, she sifts through the curated data samples and summons Bill.

“Good stuff Bill. The data looks good. Let’s update the model.”

A soft confirmation pulse appears in her view.

“Training underway,” Bill says. “I’m blending last night’s real-world success data with the highest-signal simulation runs. I’ll focus the learning on low-friction recovery and weight transfer. Estimated time: 92 minutes”

Real-world data teaches the system what truth looks like. The simulation gives it the reps.

In the old days, this part always felt like a gamble. One bad assumption, one misaligned dataset, and the whole run was toast; discovered only after burning a night of (very expensive) compute.

Worse, real and synthetic data never played well together. They lived in different systems, followed different rules, and told slightly different stories about the same moment.

One came from a messy world full of quirks. The other from a clean digital one that always thought it was right.

Getting them to agree used to take weeks of human glue work. Now, the system treats both as the same thing: pure experience.

Maya leans back as learning continues quietly in the background.

2:30pm: Reality as the Judge

“Maya, training is complete. I’ve deployed a single canary back into the wet environment for validation. Do you want to observe?”

“Yep, give me a side by side”.

Two scenes appear.

On the left, a replay of the simulation: what the system expected the robot to do.

On the right, the real world; what actually happened in the warehouse.

The real robot stopped and stuttered for a split second. Not a huge deal. But could compound over time.

“Why the pause?” Maya asks.

“Motor response latency,” Bill replies. “Today’s humidity is higher than last night, reducing latency in the actuators by about 8%. I’ll adjust the simulation parameters and do one more quick roll out.”

Maya smiled. This is her favorite part.

Simulation is no longer guessing reality. It’s mirroring it.

3:00pm: Quiet Deployment

“The second training run is complete. Rolling out a new model to the first 10 units.”

“Thanks Bill, you’re a gem.”

Maya watches as the first squad of robots revisit the scene of the crime.

“Early indicators are positive. Recovery times are improving. No regressions detected,” Bill says.

Maya now watches the average delivery time KPI. It slowly drifts from yellow to green.

Success. No emergency calls. No one even notices.

3:30pm: Freedom

Maya’s days no longer drag on into the wee hours of the night. Her mission is complete and she can go enjoy the afternoon with family.

As she packs up, Bill chirps.

“Maya, one more thing.”

She pauses. “Whatya got?”

“There’s a cold front coming in three weeks,” Bill says. “Morning temperatures will slow actuator response.”

Maya sighs. “Of course.”

“I’ve already pulled real world data from our Canadian fleet,” he continues. “They saw this exact pattern last month. Cold starts, slight delays. Nothing dramatic, but enough to matter.”

A simple flow appears in her view: real footage from snowy warehouses feeding directly into new practice scenarios.

“Simulations will run overnight,” Bill says. “By the time the cold arrives here, the model will be ready.”

Maya smiles.

When she started this job, surprises like this meant late nights and rushed fixes. Now, the system learns ahead of time.

She heads for the door. Outside, it’s still warm. Inside the data flywheel, winter has already passed.

Hope you enjoyed this glimpse into the future.

Our next essay will break down which parts of this vision are real today, and what will be required to bring it all to life tomorrow.

Until then, subscribe below and stay tuned!

This is not just MLOps applied to robots.

It’s an entirely new discipline for running systems that move through the physical world all day, every day.

For the non-technical: MLOps is how dev teams reliably train, deploy, and operate machine learning models at scale.

It was built for the internet and it assumes AI lives in a safe, predictable digital bubble; where nothing can explode and data changes slowly.

If something breaks, it’s usually a math problem, not a physics problem; you just check the dashboard, teach the AI model a new trick, and push a software update.

Over the last decade, we’ve perfected the assembly line for this, with standard tools to organize data, track experiments, and manage versions, all optimized for things like chatbots, Netflix movie recommendations, and spam filters.

These systems live safely behind an API in the cloud, far away from the chaos of reality.

Physical AI breaks those assumptions, creating an entirely different paradigm.

The difference begins with what is being operated.

In MLOps, the primary artifacts are models, datasets, features, and training code.

Data is typically tabular, textual, or image-based, collected passively from digital systems. Models are trained offline, evaluated against static benchmarks, and deployed into well-instrumented digital environments.

In RobotOps, the artifacts are far more interdependent and dynamic: perception and control models, sensor configurations, calibration parameters, 2D/3D maps and world representations, simulation environments, digital assets, and massive streams of multimodal sensor data captured during real-world operation.

Code and models still matter, but they are no longer the center of gravity. Behavior, data, and interactive environments are.

The feedback loop also differs.

MLOps closes the loop through metrics, predictions, and downstream business signals inside digital systems. This includes:

• Click-through rates (did the model’s prediction cause a user to take the intended action?)

• Classification accuracy (how many predictions are technically “correct”)

• Drift statistics (is the data is slowly changing?)

• Loss curves (is a certain math score during training is going up or down?).

From there, data is logged, analyzed, and fed back into retraining pipelines on a human-defined cadence.

In contrast, RobotOps closes the loop through the physical world itself.

A deployed model produces behavior; that behavior interacts with an unpredictable environment; sensors capture the consequences; and those sensor logs must be ingested, indexed, graded, and transformed into new training data and simulation scenarios.

This loop is continuous, not episodic.

Training, validation, and operations collapse into a single, always-on learning system (or at least, that’s the goal...)

Failure also carries a very different weight.

In traditional MLOps, a failure is annoying: a model becomes biased, a user sees the wrong ad, an irrelevant search result is surfaced.

In RobotOps, failure is physical. It means damaged hardware, safety incidents, regulatory nightmares, or the silent poisoning of future training data.

A bad model doesn’t just output a wrong number; it creates a dangerous event.

Because of this, RobotOps has to treat provenance (knowing exactly where data came from) and determinism as survival mechanisms, not just best practices.

Knowing exactly which model, environment, and scenario caused a robot to twitch isn’t a debugging convenience. It’s a safety requirement.

And then, we have the most fickle of beasts: simulation.

This is where the gap between MLOps and RobotOps becomes a canyon.

In MLOps, you look backward.

You validate models by replaying historical data or shadow-deploying alongside existing systems. The model sits safely behind an API, observing the world without touching it.

In RobotOps, you must look forward.

You can’t just ask how a model performs on past data; you have to ask how it behaves when the world pushes back.

To answer that, you need simulation. You need to run candidate models through thousands of procedural scenarios (rare edge cases, lighting changes, sudden obstacles) before you ever let code touch a physical machine.

But here is the hard truth about simulation today: For most teams, it’s a pipe dream.

Ignore the shiny visuals you see in keynote demos. While a handful of advanced, deeply funded companies have achieved full-fidelity digital twins, the reality for the other 95% is starkly different.

Building a photorealistic, physics-accurate virtual world isn’t just an engineering task; it effectively requires building an in-house AAA game studio.

Today, most teams use simulation sparingly, mostly for synthetic data augmentation or simple component testing. It lives on the periphery.

Over the next few years, this will invert.

Eventually, simulation will move from a supporting role to the center of the development loop, becoming the primary environment for validation, regression, and learning.

But first, some core challenges must be addressed, starting with simulation’s fragility; if one small piece breaks, the entire run fails, so you can’t easily retry or patch part of the job like you would with normal ML training.

On top of that, you have massive 3D asset dependencies; each run depends on huge 3D worlds, physics models, and 3D models, and if you can’t replay thousands of simulations in exactly the same way every time, you can’t trust the results or compare models reliably.

The next MLOps vs. RobotOps contrast is automation.

MLOps automation is largely pipeline-driven and rule-based. Humans decide what data to collect, when to retrain, how to evaluate models, and which versions to promote. Automation accelerates execution, but intent remains human-defined. For now...

In RobotOps, the complexity quickly exceeds what humans can manage manually. Deciding which data is missing, which edge cases matter, which scenarios to simulate next, and which models should evolve becomes an ongoing cognitive bottleneck.

This is where AI-native automation enters the equation, and might be necessary to achieve serious scale.

I’m already seeing early signals of this: vision-language models auto-labeling sensor data, world models grading synthetic scenario quality, and agents proposing new simulation campaigns based on observed failures.

Over time, these agents will operate entire segments of the learning loop autonomously.

This is the true inflection point: when RobotOps systems begin to improve themselves faster than humans could ever direct.

To be clear, existing MLOps tools like model registries, training pipelines, orchestration frameworks, etc... these things still matter. But they operate at too low a level.

RobotOps requires higher-order abstractions: scenarios instead of datasets, behaviors instead of predictions, simulation campaigns instead of experiments, data grading instead of drift detection, and learning loops instead of deployment cycles.

In this sense, RobotOps is not just the next evolution of MLOps. It is the operational layer for embodied intelligence: systems that learn through action, adapt through experience, and operate under physical constraints.

But before this can be true... we must remove a ton of pain at every stage of the data lifecycle.

Other wise, we’ll never reach the RobotOps holy grail: a fully automated, physical AI data flywheel.

The Physical AI Data Flywheel

Every company has their own version of such a flywheel. Most look something like this.

To really feel that pain, let’s walk through a typical ‘day in the life’ of a robotics developer.

Her name is Maya.

08:00 AM - The Wake-Up Call (Observe + Collect)

Maya’s day doesn’t start with code; it starts with a Slack notification from the manufacturing ops team:

“Robot #104 stalled in the Cincinnati facility. It thinks a shadow is a solid object. Again.”

This moment straddles phases 7 & 1: Observe + Collect Experience.

The robot failed in the real world, but Maya has no idea why. The dashboard shows a generic Navigation Error, but the neural network offers no explanation. She is staring at a black box failure. To fix it, she needs to see what the robot saw— she needs the log data.

The underlying challenge: Robots fail silently, and observability is shallow

In robotics, most failures are not clean crashes. They’re subtle misinterpretations of the world: shadows, glare, dust, vibrations.

Yet most fleet monitoring systems surface only coarse error codes, not the perceptual or decision context that caused the failure.

Unlike traditional software, where logs explain behavior, neural policies often provide no causal trace. The “observe” loop exists, but it’s thin: teams know that something failed, not why.

This makes learning reactive, slow, and highly manual.

09:30 AM - The Sneakernet Struggle (Ingest & Organize)

Maya tries to pull the logs from Robot #104 remotely, but she hits the ingest bottleneck immediately.

The robot is deep inside a concrete warehouse with spotty Wi-Fi. It has generated 500GB of LiDAR and camera data in the last shift alone, but the upload speed is crawling at 2MB/s.

She can’t wait three days for the upload. She let’s out a deep sigh and calls the site manager in Cincinnati. He answers and she quickly makes her ask.

“I need you to physically walk out to the unit, pull the SSD drive, and upload it from the main office fiber line,” she says.

In an era of 5G and Starlink, Maya is still relying on the “Sneakernet”, physically moving drives because the bandwidth cost of streaming terabytes of raw sensor data is simply too high.

She is forced to make a blind decision: drop 90% of the data to save bandwidth, hoping she doesn’t accidentally delete the one frame that captures the failure.

The underlying challenge: Physical data is heavy, remote, and bandwidth-constrained

Robotics data is fundamentally different from web or mobile data. High-resolution video, LiDAR point clouds, and dense telemetry quickly reach terabyte scale. And robots often operate in warehouses, factories, fields, or mines with poor connectivity.

As a result, data collection becomes opportunistic and lossy. Teams must choose what not to upload before they know what matters. This breaks the data flywheel at its foundation: learning systems depend on complete context, but physical constraints force premature filtering.

11:00 AM - The Needle in the Haystack (Index & Curate)

The logs finally arrive. Now Maya faces the data curation nightmare.

She watches the replay: a forklift drove by with a reflective safety vest that flared in the camera lens, blinding the robot’s depth sensor.

She knows exactly how to fix this: retrain the vision model on more examples of high-glare reflections.

She opens her company’s S3 bucket, which holds 4 petabytes of video data from the last two years. But it’s a data swamp.

The files are named things like:

“log_2024_10_12_robot_55.bag”.

There is no search bar. She cannot type: “Show me videos with lens flare.”

Instead, she spends the next three hours manually scripting queries and skimming through random videos, hoping to find boring footage of shiny objects.

She finds 200 hours of useless driving for every 10 seconds of relevant glare.

She is drowning in data, but starving for information

The underlying challenge: Robotics data is often unindexed, unlabeled, and semantically blind.

Robotics teams collect massive volumes of data, but lack tools to search it by what happened, not when it was recorded. Failures are semantic—glare, hesitation, near-miss—but storage systems only understand filenames and timestamps.

Labeling is manual and expensive, so the most valuable edge cases stay buried. The real tax on iteration speed isn’t data collection—it’s curation.

The root cause is structural. Robotics data lives in formats like ROS bags or MCAP—black boxes that contain everything, perfectly synchronized. But once stored in the cloud, they become opaque blobs. A system can see a 50GB file, but not what’s inside. Container formats solve storage, not understanding. So teams build fragile pipelines and scripts just to find a single failure—turning weeks into days, and learning into archaeology.

02:00 PM - The Waiting Game (Train)

After painfully assembling a small dataset of “shiny vest” scenarios, Maya kicks off a new training run. This is the training bottleneck.

She is retraining a massive Vision-Language-Action model. Even with a cluster of H100 GPUs, this will take 14 hours. If she made a mistake in the data formatting — if even one timestamp is out of sync between LiDAR and camera — the model will hallucinate, and she won’t know until tomorrow morning.

She hits Run and crosses her fingers, knowing that her iteration speed is capped not by ideas, but by compute latency.

The underlying challenge: Training is fragile, slow, and tightly coupled to data quality

Modern robotics models are compute-hungry and extremely sensitive to data alignment.

A single synchronization bug can invalidate an entire training run, wasting hours or days of GPU time. Unlike web ML pipelines, robotics training must reconcile multiple sensor streams, action spaces, and temporal dependencies.

As models grow larger, iteration speed collapses; not because engineers lack insight, but because feedback loops stretch across days instead of minutes.

04:30 PM - The Crisis of Confidence (Validate)

While the model trains, Maya reviews a candidate model from the night before. It’s time for validation.

In a 3D simulation, the model scores 99.9% success. It navigates the digital warehouse flawlessly. But Maya feels the familiar sim-2-real anxiety, aka the sim-2-real gap.

The simulator is clean; the real world is dusty, vibrates, and smells faintly of oil. Alas, the occasional oil spill, aka robots doing their best ‘Bambi on ice’ impression.

(insert Bambi on ice image)

Maya remembers last month’s incident: a model that passed every sim test but caused robots to oscillate violently because the simulator didn’t model the latency of new motor controllers.

Without a trusted “golden regression set” of real-world scenarios, validation becomes less about proof and more about gut instinct.

The underlying challenge: Simulation confidence does not equal real-world safety

Robotics validation lives in an uncomfortable gray zone. On one hand, simulation is necessary but incomplete. On the other, real-world testing is slow, expensive, and risky.

Most teams lack standardized, trusted regression suites grounded in historical failures.

As a result, validation becomes subjective—an exercise in risk management rather than evidence. This uncertainty compounds as fleets grow, making every deployment decision emotionally and organizationally heavy.

06:00 PM - The Button Press (Deploy)

It’s time to push the patch. This is the deploy fear.

Unlike a web developer who can roll back a bad update in seconds, Maya is shipping code to a 300-pound machine moving near & around humans.

A bug here isn’t a broken UI, it’s a collision or worse.

She initiates a canary rollout, pushing the update to three robots in a low-risk zone (Canary rollout = deploying to only one or two robots to ensure everything’s working properly)

Maya will watch them obsessively for the next 24 hours. The fear of bricking hardware or causing harm slows everything down.

The team could deploy daily, but because of the risk, they deploy monthly.

The underlying challenge: Deployment carries physical, reputational, and regulatory risk

Robotics deployment is software delivery with real-world consequences.

Rollouts must be staged, monitored, and reversible—but many teams lack mature tooling for fine-grained canaries, fleet segmentation, and automated rollback.

Each deployment becomes a high-stakes event, encouraging conservatism. The result is a slow, cautious flywheel where learning is throttled by fear rather than ambition.

The Cycle Continues

Maya leaves work. The model is still training. The canary robots are still running. Tomorrow morning, she’ll open Slack to see whether the flywheel spun forward, or whether a new edge case brought it grinding to a halt again.

The meta-challenge: The flywheel exists, but it doesn’t compound

In theory, robotics should improve continuously: failures generate data, data trains models, models improve behavior.

In practice, each step is fragmented, manual, and fragile. The loop turns, but slowly, unevenly, and with enormous human effort.

Until the data flywheel becomes automatic, semantic, and tightly integrated end-to-end, robotics progress will continue to feel heroic rather than inevitable.

With that... Stay tuned for Part III.

We’ll be re-examining a day in Maya’s life, but this time, in the not-too-distant future; in which these challenges are solved, the fly wheel is automated, and human-robot collaboration is the norm.

We’ll also dive deeper into simulation, and all its fun challenges, traps, and promise.

So if that interests you, be sure to subscribe! More to come on the future of physical AI and being human out on this wild new frontier.

Oh, and in case you missed Part I of this series, here’s the link:

Physical AI Deep Dive: Part I | Market Timing

It answers the ‘why now’ question for physical AI + robotics.

The answer in a sentence: breakthroughs in data collection, vision language action models, and training recipes, i.e. bespoke combos of SL + RL/simulation + IL.

Otherwise... until next time!

I’m leaving AWS and joining Nebius, one of the top AI clouds, as their Head of Physical AI.

I’m also leaving my first professional love — spatial computing. At least in its most direct and advertised form, i.e. AR, VR, 3D, aka ‘XR’.

But in another sense, I’m not leaving at all. I’m going deeper.

As we’ve discussed, spatial computing is far more than XR. This is just one end-point; just one form of a computer relying on sensors to localize, track, and understand the physical world.

Self-driving cars, mobile robots, humanoids, autonomous drones... these are all ‘spatial computers’, each relying on a similar technical foundation, with similar computer vision tech, simulation tools, and ‘spatial’ data types, e.g. lidar, point clouds, 3D, video, IoT/sensors.

The key difference?

Autonomy and their ability to impact/interact with the physical world.

So again, I’m not leaving. I’m just moving downstream; from a ‘spatial tributary’ to a gushing river, surging with capital, progress, and commercial opportunity.

Jensen Huang (NVIDIA’s CEO) popularized the term ‘physical AI’ about a year ago. As it goes… interest and awareness has exploded ever since.

To be sure, Jensen likes to live 10+ years in the future. Physical AI remains early and is in a hype cycle of its own. One that, at first glance, feels like the hype cycle that sucked me into XR (heartbreak and shattered dreams, abound).

But this feels different. The timing feels right.

This essay summarizes why. You’ll leave here with a L200 grasp of this new tech stack and the key innovations worth monitoring.

In Part II of this series, we’ll cover some of the challenges that remain, including the ones that I’ll be trying to solve in my new role at Nebius.

Subscribe now

But first, some context.

What exactly is physical AI?

It’s the next (and I believe most impactful) phase of the AI revolution.

Definitions vary, but I like to keep things simple. I define physical AI as computers/machines that can understand, represent, and/or interact with the physical world.

It’s a broad umbrella with common underpinnings; the big three are real-world data, computer vision, and of course, generative AI.

The result doesn’t have to be as complex as a robot. It can include an AI-powered camera on the factory floor, recognizing anomalies and then adjusting an assembly line in real time.

It can also include AR glasses, with cameras gathering front-line insights and providing work instructions, or informing a soldier on the battlefield.

(This is what I’m most exited about — the combo for AR + robotics to keep humans ‘in the loop’, i.e. allowing both humans and machines to see the same thing and work/sing off the same sheet of music)

More abstractly, Physical AI is the merging of the physical and the digital world; the connection of atoms to bits.

Along the way, this includes the purely virtual, in which the physical world is reconstructed & simulated.

The most exciting examples here are Large World Models like Googles Genie (GenAI that can create virtual worlds with a single prompt) and digital twins: the simulation sandboxes where ‘robots learn to be robots’.

(If you haven’t seen this two minute Genie demo video, stop right now & watch. Trust me)

Most importantly, physical AI holds the key to tech’s ultimate endgame: artificial general intelligence (AGI). That key is the embodiment of AI. Without it, machines will struggle to gain a true understanding of our world, its physics, its randomness, its interconnectedness, our larger role within it all. With physical AI, perhaps the greatest mysteries of the universe will be revealed...

I find it all endlessly exciting and hopeful, and just incredible that we get to experience this phase of human history.

But I digress. Putting my realist cap back on.... We still have a little ways to go.

How much further?

I believe we’re where LLM’s were between 2017 - 2019.

World class teams have been funded, foundation models are in development, compelling demos are sparking the imagination, and VC dollars are flowing.

Most notably, many of the top AI minds from academia are leaving the labs in droves, founding companies and taking the commercial leap (e.g. Chelsea Finn & Sergey Levine @ Physical Intelligence, Ken Goldberg @ Ambi Robotics)

As such, it feels like we’re 3-4 years from the ChatGPT moment and 5-7 years away from this stuff hitting meaningful scale (e.g. robotic manufacturing & supply chains are dialed, millions of units are being deployed in the enterprise, and consumer adoption is starting to ramp).

And this is slightly conservative. After all... humans are terrible at grasping exponential curves.

What exactly is the ChatGPT moment?

It’s when we have a generalizable, foundation model for physical AI. Aka: an API to the real world, that can understand, navigate, and complete general tasks in a ‘zero shot’ fashion. Meaning, it can perform a task it has never been explicitly trained on before.

And when I say generalization, I mean across numerous variables, the most important being hardware. Meaning, it works with not just one form factor, but across many form factors, translating data + context into an action/output on humanoids, quadrupeds, AMRs with four arms, or even AR glasses.

So why now?

Because these foundation models are starting to arrive, giving developers a substrate upon which to further train & fine tune.

The first wave emerged in 2023/24. The most notable being Google’s RT-1 and RT-2, Physical Intelligence’s π0, Covariant’s RFM-1, and NVIDIA’s Project GR00T.

You can liken these to OpenAI’s GPT-1 & 2. Not super useful out of the box, but mind-blowing technical breakthroughs, nonetheless. They’re the result of upstream innovation in three main areas: (1) new architectures, (2) new data regimes, and (3) new training recipes.

(1) New Architectures

You’ve probably heard of the Transformer: the architecture that quietly changed the AI world in 2017. It’s the engine behind ChatGPT, Gemini, and every modern large language model. Transformers work by treating language as a sequence of tokens and predicting what comes next.

Its impact on text was obvious. Its impact on physical movement? Less so.

But roboticists quickly saw the parallel. A robotic action is just another kind of sequence. Instead of words, you have motor commands. Instead of sentences, you have trajectories—reach, grasp, lift, place.

Once we applied Transformers to robotics, something remarkable happened: robots could learn useful skills from dozens of demonstrations instead of thousands. Efficiency jumped by an order of magnitude, and for the first time, robots gained a model that could actually generalize across varied tasks. But moving is only half the battle. To interact with the world, you have to understand it.

This is where the Vision-Language-Action models enter the picture (aka VLAs)

Their predecessor was Vision-Language Models like CLIP. These systems fuse text and imagery into the same conceptual space, teaching machines to recognize “dog” as an idea, not a blob of pixels.

As you probably guessed, VLA’s add the missing piece: action. They “tokenize the world,” weaving together text tokens, image tokens, and motor tokens into a single sequence.

If you give them a high-level instruction like “pick up the apple,” and they can identify the apple, understand the intent, and sketch out a plan. It’s the beginnings of a generalist robotic brain.

But a brain that can imagine a plan is different from a body that can execute it.

For that, the industry started turning to Diffusion Policies. This is the same generative magic behind image creation tools like Midjourney or Nano Banana.

In generative art, diffusion starts with pure noise and gradually “de-noises” it into an image. In robotics, it starts with noisy, meaningless motor twitching and de-noises it into a fluid, coherent motion.

This approach solves one of robotics’ oldest curses: the multimodal problem.

This problem arises in tasks that have more than one ‘answer’. Take opening a drawer for example. It has multiple valid solutions: you can grab the handle from the left, right, or top.

Older models (convolutional neural networks) tried to average these demonstrations and ended up reaching for the center, where no handle exists. With diffusion, it doesn’t average; it chooses. It locks onto a single valid mode — left-grab, right-grab, top-grab — and executes it with a kind of crisp, biological confidence.

In short, this gives robots the decisive body that matches the VLA’s semantic brain.

The result is a dual-system architecture. One that looks/feels a lot like human mind, with System 1 and System 2 modes of thinking. And yes, it’s very similar to the concept you’ve probably heard from the book Thinking, Fast and Slow, by Daniel Kahneman’

System 1 (the body) is the the ‘fast’ diffusion policy. It’s reactive, and precise. It takes a strategy and turns it into the 50-millisecond motor adjustments needed to actually grasp a crinkled wrapper.

Systems 2 is the ‘slow’ brain, powered by VLA. It’s deliberate and semantic. It looks at the room, understands “I need to clean up that trash,” and generates the high-level strategy.

But even with this powerful combo, the robot is still just mimicking. It doesn’t truly know if it succeeded. To get closer to human-like intelligence, you need a closed loop system that can learn from its mistakes and upgrade itself on the fly (we’ll cover this further in Part II).

(2) New Data Regimes

Okay, so we now have this dual-system architecture, giving us the right ‘engine design’ for physical AI. Next we need fuel, aka data.

In the purely digital world of LLMs, fueling AI is relatively easy. You scrape the entire internet — billions of images, trillions of tokens of text — and feed it into a GPU cluster running frameworks like PyTorch or JAX.

But in the physical world, there is no internet to scrape. You can’t just download “how to fold a shirt” or “how to solder a circuit board”. You have to create it (although, heavy research is underway towards making YouTube videos digestible for robotics).

This is currently the single biggest bottleneck in Physical AI.

To solve it, the industry has made exciting progress in three key areas: data-crowdsourcing (The Community Pot), teleoperation at-scale, (The Grind), and simulation (The Infinite Well).

The Community Pot: Open X-Embodiment

For years, robotics was a fragmented discipline. A lab at Stanford would collect data for a Franka Emika arm and a lab at MIT would collect data for a Kuka arm. But the data was siloed, incompatible, and useless to anyone else.

That changed with the Open X-Embodiment Collaboration.

Think of this as the “ImageNet moment” for robotics. Led by Google DeepMind and 20+ other institutions, this project pooled data from 22 different robot types into a massive, standardized dataset.

The hypothesis was simple but powerful: positive transfer. They bet that a robot arm in California could learn better grip strategies by studying the data of a completely different robot arm in Zurich.

And they were right. Models trained on this collective “community pot” of data outperformed those trained on narrow, proprietary datasets. It proved that if we stop hoarding data and start standardizing it, we can bootstrap general intelligence much faster.

The Grind: Teleoperation Fleets

Community data is great for general skills, but for high-precision tasks, you need the “gold standard” data, aka human intuition captured at 50Hz.

Enter teleoperation fleets.

If you walk into the offices of the top Physical AI startups today, you won’t just see engineers coding. You’ll see rows of operators wearing VR headsets or using haptic controllers, “puppeteering” robots to do chores, assemble parts, or sort logistics.

This is the grind. It’s painfully slow and expensive (1 hour of human time = 1 hour of robot data). But it is currently the only way to capture the subtle “English” a human puts on a screwdriver, or the way we instinctively jiggle a key to make it turn. This data creates the kernel of knowledge that models need to imitate.

Fortunately, we now have a wave of companies like Scale AI, Sensei, and Deta who are industrialization this capability, standing up “Data Engines-as-a-Service” to collect thousands of hours of expert demonstrations.

Helpful and promising... but its not enough.

The Shortcut: UMI

To ease the TeleOp grind, a promising new idea surfaced back in 2024. It’s called Universal Manipulation Interfaces (UMI).

Instead of teleoperating a specific robot through complex rigs, UMI flips the model. Humans manipulate the world directly using a lightweight, handheld gripper with a wrist-mounted camera.

This captures rich, first-person visual and motion data—how objects move, how forces are applied, how tasks unfold in real environments—without requiring a robot in the loop at all. In effect, it decouples data collection from robot hardware, turning natural human interaction into training data.

The real unlock is generalization. Because UMI represents actions in a relative, hardware-agnostic way, these demonstrations can be transferred across different robot arms, grippers, and platforms with minimal retraining.

It doesn’t replace teleoperation fleets or simulation, but it meaningfully expands the funnel; lowering cost, increasing diversity, and capturing human intuition at scale.

If teleoperation is the gold standard and simulation is the infinite well, UMI sits in between: a faster, more portable way to turn human skill into robot competence.

The Infinite Well: Solving Sim-to-Real

While teleoperation and UMI capture quality, they both have a hard limit: human time.

You can’t hire a billion humans to teach a billion robots. Eventually, the robots must learn in the virtual world. Especially if we want to capture all the edge cases and complexity of the real world.

This is the promise of what the industry calls ‘Sim-to-Real’ (aka learn in simulation and transfer a policy to reality)

In the past, simulators were essentially video games with bad physics. If a robot learned to walk in code, it would often fall over the second it stepped into the real world because the friction was slightly off or the lighting was different.

The industry has started to solve this with a technique called ‘domain randomization’.

Think of this as the “brute force” approach. Since you can’t match reality perfectly, you just randomized everything, creating chaos across every possible dimension; lighting, floor lay outs, friction levels, temperature, sensor noise, etc.

The ideas is that if a robot can survive the chaos, the real world will feel easy by comparison.

This works to an extent, but it’s inefficient, lacks complete accuracy, and leaves ‘reality’ gaps.

But those gaps are starting to close. Three new technologies are maturing that can hep us clone reality rather than just guess it.

The first is neural rendering (aka gaussian splatting).

Traditionally, building a simulation meant hiring 3D artists to hand-draw every table, screw, and factory wall. This is slow, expensive, and rarely 1:1 with reality.

Gaussian splatting flips the script. It allows us to walk through a factory with a camera, scan the environment, and “splat” a photorealistic digital copy into the simulator. It captures the messiness of the real world: the rust on the metal, the grease on the floor, the weird reflection on the window. This matters because robots are easily confused by visual noise.

Now, they can train on the exact visual chaos they will see on deployment day.

Next we have ‘Differentiable Physics’ within the simulations. Old simulators were “black boxes.” If a robot tried to pick up a cup and failed, the simulator effectively just said, “You failed.” It didn’t explain why.

The robot had to guess randomly to fix it.

Differentiable simulators (like those powering NVIDIA’s Isaac Lab) are “glass boxes.” They provide mathematical gradients. Instead of just saying “Fail,” the simulator says, “You failed because your grip force was 10% too low for this friction coefficient.”

It gives the AI a roadmap to the correct solution, speeding up the learning process exponentially.

With better sim tools in hand, the next breakthrough is “Real-to-Sim-to-Real Loops”, allowing developers to fine-tune the virtual world to match the real world 1:1.

To do so, developers deploy the robot in the real world and wait for it to mess up.

When it fails, they take that log data and feed it back into the simulator to auto-tune the physics until the simulation perfectly matches the failure they just saw. So we aren’t just simulating the world anymore; we are calibrating a ‘physics accurate’ digital twin in real-time.

Now, imagine what happens when we combine these “digital twins” with Generative World Models (like NVIDIA Cosmos or Google’s Genie), which let us generate entirely new 3D training environments from a simple text prompt.

This will be the take off point, moving us from a world where data is scarce to a world where the only limits are the amount of compute we can throw at the simulation.

(3) New Training Recipes

We now have the right blue print and we’re starting to get more data. The final answer to ‘why now’ is all new training recipes, yielding pipelines that look more like a staged learning curriculum than just a single ‘lesson’.

For most of robotics history, you had to choose between two flawed religions: imitation learning (IL) or reinforcement learning (RL)

IL is the “monkey see, monkey do” doctrine. You’d teleoperate a robot through a task a thousand times, and it would replay a fuzzy statistical version of your motions. This has been safe and predictable, but it only scales linearly with human time/effort.

RL is the faith of trial and error. You give a robot a goal, a reward score, and then let it stumble through the problem until it figures out the rules. This is how AlphaGo shocked the world.

But in robotics, “trial and error” isn’t theoretical. It’s metal slamming into metal; motors burning out, drones flying into walls. And as mentioned, simulation doesn’t yet cover every edge case. It’s also just really hard for most teams to do well (requires a unique combo of dev talent across infra, sim tools, 3D dev, etc).

Historically, the industry was stuck between these two extremes. Today, that dichotomy has dissolved. The frontier isn’t about choosing one religion over the other. It’s about stacking every ingredient—imitation, RL, prediction, simulation—into multi-stage pipeline that take a robot from novice to expert.

Two distinct philosophies have emerged from this blending. Both are producing breakthroughs, but along very different paths.

Path 1: Simulation-Heavy

The first path — championed by Google, DeepMind, TRI, and NVIDIA — leans heavily on simulation and RL.

You start with a pre-trained foundation model (usually a VLA) that already understands objects, scenes, and basic motions.

You then add a small number of human demonstrations to shape this knowledge into a safe behavioral prior, aka a rough draft that keeps the robot from flailing.

With this baseline in place, the robot enters the simulator, i.e the “infinite gym.”

In sim, physics can be bent, lighting randomized, textures swapped, and time accelerated. Failure costs nothing. This is where RL thrives: thousands of attempts per hour refine the rough draft into polished skill, uncovering tiny efficiencies no human ever thinks to demonstrate.

Recent advances add one more layer: foresight. Instead of reacting frame-by-frame like a goldfish, World Models are starting to give robots an internal physics engine, letting them imagine how an action will unfold before committing to it; predicting slips, collisions, or ideal grasp points. Much like an athlete visualizing a race, the robot rehearses futures and picks the best one.

Put it all together, you get a system that understands, refines, and anticipates. But not everyone believes simulation is the best approach…

Path 2: The Real-World-First Curriculum

While simulation is powerful, it’s also expensive, brittle, and often suffers from the “sim-to-real” gap.

In response, companies like Physical Intelligence, Skild AI,, and 1X are proving that you can achieve general-purpose manipulation without heavy RL or sim. That is… if you have enough real-world data.

Similar to the simulation path, this journey begins with a Pretrained World Encoder. Whether it is a Vision-Language Model like CLIP or a VLA like π₀ (Pi-Zero), this gives the robot conceptual understanding before it ever sees a teleoperation demo.

The divergence happens next.

While sim-first teams rely on RL to discover skills, real-world teams bet on Massive Supervised Imitation. This isn’t just a few dozen demos. This is brute force at scale. Physical Intelligence utilizes ~50,000 teleop demos; Covariant leverages millions of manipulation attempts. This creates a massive prior: a raw instinct for how humans interact with the world.

From there, the accelerator is Self-Supervised Learning.

These companies treat every single frame of robot data (i.e. logs) as a lesson, mining camera video, gripper-camera views, failed grasps, and even passive background motion, all teaching the robot physics and causality without needing an explicit reward function.

Finally, once deployed, they use online adaptation, aka ‘learning on the job’ by tweaking the robots tactics in real-time based on sensor feedback. This allows them to handle slips, nudges, and new objects without needing a full RL training loop

Two Paths, One Destination

Despite their difference, both paths are converging toward the same ideal: machines that understand their environment, learn from experience, imagine the future, and refine themselves over time.

The future will likely blend the two. Either way, we are no longer teaching robots to copy us. We are teaching them to learn from us, practice without us, and ultimately, surpass us.

The Final Bottleneck

We’ve covered the brains (VLA), the bodies (diffusion), the fuel (data), and the training recipes (hybrid pipelines).

On paper, this is the formula for Physical AI, and after decades of tinkering, robotics is at an inflection point. But there is a final, unsexy truth standing in the way…

The bottleneck is no longer hardware. It’s not sensors, actuators, or even algorithms.

The bottleneck is infrastructure.

Robotics companies are all trying to do the same thing: build systems that learn from experience, improve with data, and become more capable with every iteration. But the workflow is fundamentally broken.

If you spend a week inside any robotics organization (humanoid, warehouse AMR, manipulator, or AV), you’ll see the same story: a bunch of engineers — some of the brightest minds in AI — spending 80% of their time fighting the cloud rather than solving robotics.

They’re building bespoke infrastructure from scratch, consistently reinventing the wheel, and often stuck in DevOps hell.

What they want instead is a fully automated robotics data flywheel — a system where robot logs ingest themselves, simulators spin up on demand, training datasets auto-curate, training pipelines retrigger on new edge cases, and updated models roll out safely across the fleet.

This is the problem space we’ll explore in Part II. Until then, enjoy these robot bloopers — a great reminder that until we can operate data fly wheels with ease, this is the extent of most robot careers: extremely expensive slapstick comedians.

On the dusty plains of Idaho, hundreds of scientists erupt in celebration; hugging, clapping, cheering.

They just had a breakthrough and their vision was vindicated. A vision that — even by today's standards — was entirely science fiction.

It was also polarizing. Because when we split the atom, we also split the world…

For some, nuclear fission was the key to human flourishing. For most, it was the ultimate weapon.

But the optimists in Idaho held their ground. They imagined a world in which energy was no longer a constraint. Where abundance wasn't theoretical. Where humanity's growth wasn't tied to a negative impact on the earth.

These dreamers weren't just building nuclear reactors. They were ushering in a new epoch in human history: the first atomic age. And their progress was legendary.

The Idaho National Lab (INL), under the purview of the Department of Energy, went on to produce 52 nuclear test reactors. Along the way, a singular debate echoed through its halls: when would nuclear power 100% of the earth's energy?

The scientists started placing bets, and at the time, most agreed — it'd be around the year 2000.

Needless to say, that's not what happened.

Nuclear remained misunderstood and Idaho National Lab became a shell of its former self.

The Second Atomic Age

The year is 2025 and those dusty plains are stirring, yet again.

Back at Idaho National Lab, the old dream is being reborn, but this time, the headwinds of the past have become the tailwinds of the future.

Regulatory bodies are creating modern frameworks for new reactors. Private capital, once allergic to nuclear energy, is now flowing in. And at long last, the technology is mature, safe, and ready.

A nuclear renaissance is underway and the race is on, with multiple startups setting their sails; each one taking a unique tack.

There’s Kairos Power, who just signed an MOU with Google to deliver 500MW of nuclear power for AI data centers via a small modular reactor (SMR).

There’s Radiant Nuclear, with $225M in funding for its ‘nuclear reactor in a box’, aka a micro modular reactor (MMR).

And then there’s the buzzy, Wall Street darling Oklo, who went public via a Sam Altman owned SPAC in 2024, valuing the company at $400M.

Oklo has since surged over 500% to a $10B+ valuation…

Oklo’s next big milestone? A prototype of a small, configurable nuclear power plant at Idaho National Lab (INL). They’re soon to break ground and the markets are watching with bated breath.

But Oklo isn’t the only game in town.

Less than half a mile away, a newer company has partnered with the INL and just secured its own plot of land; to build not just a prototype, but to invent an entirely new class of nuclear energy product.

It’s not a Small Modular Reactor (SMR). It’s not a Micro Modular Reactor (MMR). And it's not your traditional nuclear power plant. It’s something entirely new, filling multiple gaps between all three.

The company is called Aalo, and despite a later start and fewer resources, they’re vaulting ahead on all major fronts.

The rest of this essay is a deep dive into how and why.

Introducing Aalo

Relative to its competitors, Aalo has moved at a blistering pace.

Since launching in 2023, they’ve moved into a 40,000 sq ft factory space, built a non-nuclear prototype, received permission to pursue Department of Energy (DOE) authorization for their first reactor, secured land to build it at Idaho National Lab, and signed non-binding agreements with some of the world’s largest possible customers (most confidential, for now…)

This all just culminated in their two biggest milestones to date: First, a $100M Series B led by Valor Equity Partners, the world-class hard tech investor behind SpaceX, Tesla, and Anduril.

Second, Aalo’s selection by the U.S. Department of Energy as one of eleven companies in President Trump’s Nuclear Reactor Pilot Program—an initiative aimed at building and operating at least three advanced test reactors by July 4, 2026. This places them on the fast-track of America’s nuclear renaissance, with direct federal support to prove their design in record time and a spotlight as one of the few companies shaping the future of clean baseload power

During this time, Aalo benefited from those industry-wide tailwinds across technology, financing, and regulation. But, when they first launched, the market remained stagnant and speculative. It was still missing a key ingredient: a commercial catalyst, aka the right buyer with enough urgency, capital, and political power to pull projects through.

Fortunately, in an almost kismet fashion, that buyer has suddenly arrived: our new digital companions — artificial intelligence.

As AI surges ahead, energy has become the most critical layer of the AI stack.

No doubt, AI offers endless promise and hope, from growing out of a debt spiral, to curing diseases, to modeling climate change, to redesigning our material world.

But its future depends on how many electrons we can push through a wire. And this digital brain has a voracious, 24/7 appetite.

To give you a sense, the typical data center uses around 25-50 MW of energy, which is enough to power a small town. Over the last 10 years, hyperscalers have required around 100 - 300 MW.

But now with AI? They’re requiring 10-20X that… from 1-2 GW. Hence Elon Musk’s recent purchase of a 2GW gas-turbine power plant for Collosus: the 200k GPU cluster behind xAI.

To put that in perspective, 2GW is enough to power the electricity demand for nearly 40% of New York City and 50% of Los Angeles…

When you drag out this level of demand, AI is on pace to consume the majority of the US electrical grid by 2030.

And to think… AI is just one of many looming sources of enormous demand.

Include the electricity needs for EV charging, robotics, manufacturing, growing cities, the military, etc. and there’s no doubt… The future is arriving faster than we can power it and our aging grid — an ancient system that hasn’t effectively changed in 100+ years — can’t keep up.

Fortunately, the energy market isn’t waiting around. A new paradigm is emerging, characterized as ‘bring your own power’, with customers planning to leap frog the grid entirely.

This is Aalo’s opportunity and the kernel of their strategy.

But to fully appreciate it, we must first set context with the state of nuclear energy and Aalo’s origin story.

Not Your Grandpa’s Nuclear

Over the last decade, nuclear energy has quietly become the safest, most reliable, and most power-dense source of clean energy ever created.

Just a single, 1-inch pellet of uranium can replace a ton of coal.

And a single barrel of uranium? It can replace two million barrels of oil/gas.

At scale, for reliable base-load power, nothing else comes close. Which is why nuclear is the answer, not just to climate change, but to many of the world's most complex challenges; from rising costs, to food production, to water scarcity, to geopolitical tension; all of which boil down to a lack of cheap, accessible energy.

Aalo CEO, Matt Loszak, locked on to this problem space back in 2021. After building a successful HR software business (to 150 employees and 4,000+ customers), his roots in physics and engineering took hold; he had mastered the world of bits; it was time to conquer atoms. So as nuclear began to accelerate, Matt began to build.

With a degree in physics, Matt knew enough about nuclear to be dangerous. But he needed to gain an edge. He also needed a technical co-founder. So Matt set off on a global tour, meeting with the most renowned nuclear experts in the world. 100’s of them; gaining knowledge, looking for patterns, and seeking a partner in arms.

One of those experts was Yasir Arafat, the Chief Architect and project lead for one of the most significant and yet underrated nuclear power projects in the US: MARVEL.

MARVEL is a government-funded microreactor at Idaho National Lab – the first new reactor scheduled for construction. It’s also a test-bed built to unlock the next generation of nuclear innovation.

For decades, startups have been stuck in a catch-22: you need operating data to get licensed, but you need a license to collect the data.

MARVEL breaks this cycle, offering a safe, government-backed environment to test components, validate models, and show how advanced reactors connect to real systems like microgrids; all while providing the hard data required by regulators and customers.

For startups like Aalo, MARVEL is a force multiplier, de-risking their tech, speeding up deployment, and signaling that nuclear power is moving forward, yet again.

Upon learning about MARVEL, Matt decided to go all in. His first move?

Recruiting Yasir as his co-founder.

It’s hard to draw up a better profile for a nuclear energy CTO.

Yasir led MARVEL to achieve something no one else had done before: the first-ever DOE authorization for construction of a nuclear reactor.

Prior, he led the eVinci microreactor program at Westinghouse — one of the most influential names in the industry, responsible for the world’s first commercial pressurized water reactor (PWR), a design that still powers over half the world’s nuclear fleet today. It’s also behind the AP1000, one of the safest, most advanced reactors ever built.

In other words, Westinghouse defined nuclear’s past. Now, Matt and Yasir are setting off to define its future, with multiple rock stars joining in the mission, including Richard Williams as Director of Engineering (MARVEL’s former Director of Engineering), Jon Guidroz as SVP of Commercial (former Chief Strategy Officer for Energy at Microsoft), Scott Reynolds as VP Finance (former global head of structured finance at Bloom Energy) and Bryson Gentile as VP of Manufacturing (previously Head of Manufacturing at SpaceX on Falcon 9).

The X Factor

This is an A-List team. But nuclear energy is a modern day gold rush. The world’s best & brightest are flocking to win the prize. Top talent is table stakes.

What differentiates Aalo most is their product strategy. Particularly, their plan for achieving product market fit.

If I had to pick one deciding factor, this is where the race will be won or lost.

That may sound obvious. But the nuclear market is unique. The value chain is in flux and the ultimate buyer isn’t clearly defined— is it the power utility? The data center developer? The co-lo operator? The cloud hyperscaler? All of the above?

Despite this uncertainty, nuclear startups have to pick a design path and bet on a demand signal early.

Aalo’s bet is both clever and sound.

First, they’re working backwards from the most urgent and well-capitalized source of demand; AI hyperscalers (the Microsoft’s, Google's, Meta's, and Amazon’s).

Second, they’re designing for multiple potential buyers, as hyperscalers don’t operate in isolation, but within a complex ecosystem of developers, utilities, and partners.

Which raises an existential question: should Aalo be a power developer or just a reactor OEM? i.e. build & operate the full plant? Or just sell the core primitive to builders/operators?

The reality (and the fun part) is they have to be both, existing in a kind of quantum state, ready to collapse the wave function at the precise moment the market demands clarity.

So the prevailing business question isn’t simply, “What does the customer want?”

It’s “How do we meet demand that is still deciding how to express itself?”

Aalo's answer is two fold:

First, stand on the shoulders of giants.

In partnership with Idaho National Lab, they’re designing an entirely new reactor platform, inspired by learnings from MARVEL, EBR-II, AP-1000, and other well known historical reactors.

This approach helps de-risk the technology, smooth the regulatory path, and build confidence with future customers. And while Aalo-1 is inspired by these past reactors, it adds new engineering innovations, leveraging modern innovations in materials science and more, to make the design uniquely well suited for AI data centers. At the same time, it keeps the proven ingredients, e.g. a proven fuel supply chain with UO2 fuel type, a coolant with deep operational history, well proven safety features, and modern simulation tools, giving regulators and partners much needed comfort and conviction.

The second part of their answer — offer an a la carte menu, from Lego blocks to a full plug-in-play system, aka a nuclear factory-in-a-box.

This approach mirrors NVIDIA’s. While known for GPUs, NVIDIA also sells complete AI server racks, along with CPUs, networking gear, and cooling modules. Their customers can choose to buy a full-on ‘AI factory’, with multiple networked racks, or they can integrate individual parts into existing infrastructure.

Aalo’s offering is similar, and the first of its kind. It’s modular enough for multiple buyers, robust enough to scale, and flexible enough to serve the ‘Bring Your Own Power’ value chain emerging around AI hyperscalers.

It’s also a classic 'blue ocean strategy': avoid a crowded, legacy market (red ocean) by creating an entirely new one. I’m calling this uncontested space ‘the missing middle’.

The Missing Middle

The advanced reactor industry offers two primary options, neither of which is the ideal fit for data centers.

On one end there’s Small Modular Reactors (SMRs).

These are shrunken versions of traditional grid-scale plants, designed for utilities years before the AI boom. While promising modularity, they still follow the old playbook: large projects, long timelines, and high costs per megawatt.

For a hyperscaler who needs power in months, not years, SMRs are too big, too slow, and too tethered to the legacy energy model.

On the other end are Micro Modular Reactors (MMRs).

These are tiny, ~1-megawatt reactors designed for niche, off-grid uses. While highly portable and safe, they are a squirt gun for a wildfire; their power output is too small and their cost per megawatt is too high to be a scalable solution for AI's immense energy needs.

In hindsight, this product gap might seem obvious. But until today, filling it just didn't make commercial sense. A market didn't exist.

Now, an immense opportunity has emerged, to match the right product architecture to the data center's acute, time-sensitive demands.

Subscribe now

Aalo's Answer: The XMR

To seize this opportunity, Aalo is inventing an entirely new category: the XMR (Extra Modular Reactor). The "X" stands for the extra flexibility and adaptability, or offering the X-Factor for AI data centers by designing around their unique needs.

Their core product is called the Aalo Pod, a 50-megawatt power plant composed of five 10-megawatt, sodium-cooled reactors; powerful enough for a small city or medium data center and composable enough for gigawatt scale.

It’s designed around three main vectors:

Optimal Size and Scalability: The Pod delivers the significant power of an SMR but is built with the manufacturing efficiency of a microreactor. This allows data centers to scale power in 50 MW increments, mirroring how they build out their campuses.

Data Center Optimization: With five independent reactors providing N+1 redundancy, the Pod offers the extreme reliability required for mission-critical AI workloads. Its compact, 2.5-acre footprint and air-cooled design means it can be co-located directly on-site, even in arid regions, eliminating reliance on the fragile grid.

Speed and De-Risking: By using proven UO2 and low-enriched uranium (LEU+) fuel instead of waiting for novel fuel types, Aalo sidesteps one of the biggest supply chain and regulatory bottlenecks in the industry. This enables a target deployment cycle of just 52 weeks, from order to operation (a marvel in its own right, which we’ll cover later).

This is energy's version of an AI server rack. After a rapid on-site assembly, you drop it in, turn it on, and voila; the AI factory is humming.

Elegant, indeed, but the real beauty lies in its composability and a hierarchy of innovation that de-risks the technology at every stage.

The fundamental building block of this system is the Aalo-1, the individual 10 MWe reactor module. This is the core technology: a sodium-cooled thermal-spectrum reactor designed for safety and mass manufacturing.

By using liquid sodium as a coolant, it operates at near-atmospheric pressure; a key design choice that eliminates the risk of the high-pressure meltdown events associated with traditional water-cooled reactors.

Each Aalo-1 is a self-contained, factory-built unit. It’s the essential component that makes the entire Pod concept possible.

Before a single Aalo-1 is deployed, however, there is the Aalo-0. This is Aalo's non-nuclear, electrically-heated prototype. It is a full-scale physical twin of the Aalo-1, allowing the team to test, validate, and perfect every aspect of the thermal hydraulics and system performance without touching nuclear fuel.

This "test before you build" approach is critical— it proves the physics and de-risks the technology for regulators and investors, demonstrating a mature and responsible path to market.

The bridge from factory to field is Aalo-X, the first private advanced reactor demonstration being built in partnership with the U.S. Department of Energy at Idaho National Lab. This is the regulator and technical proving ground that unlocks commercial deployment.

This plan is rooted in clear logic: start with the customer problem, deliver a standardized product with the Pod, build it on proven core technology with the Aalo-1, and validate fast to de-risk future deployments with the Aalo-X.

It's also shaped for the urgent timelines of the AI era, while remaining sharp enough to slice through regulatory red tape and stigma.

From Strategy to Reality

To realize its potential, Aalo must compound this momentum across every part of the business, starting with its two strongest points of leverage: a factory that learns and a delivery model that radically compresses timelines.

The factory is inspired by playbooks from Tesla and SpaceX. It’ll begin as a lean “minimum viable factory” to prototype fast. They’ll then certify it to the NQA-1 spec: the gold bar for manufacturing safety and reliability. From there, it will scale into a gigafactory—flipping nuclear energy from decade-long one-offs into a repeatable machine where costs fall, risks shrink, and power rolls off the line like clockwork.

The magic behind it all is a digital twin: a full-stack simulation of the reactor, the factory, and the supply chain. This is not just a virtual model. It’s an orchestration layer; one that can spot bottlenecks, reschedule in real-time, and preempt delays before they surface.

This turns Aalo’s facility from a set of machines into a self-improving organism that can be cloned and deployed anywhere in the world.

Then we have the delivery. This is where Aalo bends reality, starting with a company-wide mantra: “order-to-electrons in 52 weeks”.

Contrast this with nuclear's current decade-long fiascos, and it’s not just a timeline. It’s the kind of maniacal mission behind the greatest companies in the world.

The key is treating deployment like a software-driven manufacturing workflow.

Aalo’s “order-to-electrons” clock starts the moment a customer signs. Three tracks begin in parallel: contracts and financing, AI-assisted regulatory filings, and factory production of reactor modules.

By the time site licensing is approved—roughly 24 weeks in—most of the system is already built.

With over 90% of the work done in the factory, the on-site labor is minimal. Modules arrive pre-fabricated and ready to slot into place. From there, there’s ten weeks of local assembly; followed by three months of testing, fuel loading, and final validation; and then… Power on.

The Path Forward

To go from this vision to electrons, Aalo has countless milestones to hit. But here are the most important:

In late 2025, they will break ground on the Aalo-X demonstration plant at Idaho National Lab and work toward gaining regulatory approval via the Department of Energy. This phase also provides data to fast-track an NRC application (i.e. Nuclear Regulatory Commission).

In 2026, they’ll achieve zero power criticality on Aalo-X. This means the reactor has achieved a self-sustaining nuclear chain reaction at an extremely low power output—essentially, near zero thermal power; a crucial step before the reactor begins producing significant heat or electricity.

In 2027, they’ll achieve full power at Aalo-X, which will validate the entire model and propel it towards commercial deployment in 2028, including NRC approval and construction of the first commercial Aalo Pod for a data center customer.

By 2029, the first commercial reactor will be powering a data center at full clip, setting the stage for a major financing event or IPO and a rapid, nationwide scale-up throughout the 2030s.

All of these objectives are geared towards a singular long-term goal: reducing the cost of electricity down to $0.03 per kilowatt hour.

In the US, the average cost is around $0.16 - $0.17, and rising fast, constraining countless plans to build, innovate, and grow. But if Aalo succeeds, those sci-fi dreams from the plains of Idaho become reality.

Imagine… the year is 2055. Electricity flows like water, powering not just homes and industries, but all new frontiers of human ambition.

Deserts bloom with desalinated water, city-based vertical farms feed millions, automated factories hum continuously, remote villages enter modernity, and reactors light up bases on the Moon and Mars. While back home… The air is cleaner, the climate is steadier, and prosperity is more accessible for all.

Yet abundant energy isn't just about raising the floor, it's about shattering the ceiling.

This starts with unleashing the potential of our most powerful new tool — artificial intelligence — which is woefully tethered to a short electrical leash.

While abundant energy won’t turn AI into a magic wand, it will allow the machines to run the trillions of simulations required to find a new drug, to model a planet’s climate with startling accuracy, or to design a material that was previously impossible.

It also lets us ask bigger questions; questions about our purpose, our origins, our destiny; because we can finally afford the computational cost of finding the answers.

This future will not be perfect. We will still be wrestling with our all-too-human limitations. But by removing the endless, exhausting struggle for energy, we are freed up to focus on everything else.

And while nuclear won’t solve all our problems. It will make solving the grandest of them profoundly more plausible; expanding the realm of the possible, and reminding us that the only true, lasting constraint on our future is what we dare to imagine next.

Which is why I’ve concluded — the world does remain split, but in an entirely different way: those who love nuclear energy, and those who just haven't looked closely enough.

Full transparency: I’m an investor in Aalo. But this essay came first. As I was writing and interviewing the team, my conviction grew — and when an allocation opened up in their Series B, I jumped all over it. Maybe it was luck, maybe it was timing, or maybe stories really do shape the future…

If you're just joining us — welcome! Excited to have you on this mind erasing bending journey.

That said, if you want this essay to truly land, highly suggest starting at the beginning with Part I. Links to each essay below:

• Part I

• Part II

• Part III

We've traveled far.

From the origins of this illusion, to wide-eyed babies, to how/why you 'have no head', to empirical evidence exposing the glitch in the Matrix.

The key takeaways?

You are not the thinker of your thoughts. You are not the pilot behind your eyes. You are not a permanent self riding around in a biological vehicle.

You're an ever adapting story, told in real time by a nervous system trying to keep you alive.

This might land intellectually. But if you're like me... it doesn't matter. Experientially, the illusion remains. And the more I poke at it, the feeling of self doesn't just remain... It rebels.

As if under attack, a self-defense mechanism is awakened. The whispers turn into screams,

"I'm real damnit! And I'm in control... All those desires? Success, money, power, sex.. we will and shall have it all. Onward!"

*sigh...

So what the hell is one to do? It all seems so... futile.

My first thought is to give up and just keep living my life and being... my self.

But then I see the progress of AI. I see how it's merging with augmented/virtual reality. I see how our sense of self — bombarded by virtual influence and mimetic desire — is soon to be swallowed whole, chewed up, and spit out.

I then turn back to my newborn daughter, Chloe. Her eyes are still too young to focus. But sometimes, her eyes lock onto mine. Or at least, they appear to... and in that moment of connection, I forget myself.

Not in the poetic sense. I mean literally: the “me” doing the watching fades. No inner narrator. No ego analyzing the moment for meaning or metrics. Just sensation. Soft skin. Warm breath. An open field of aliveness.

It lasts a few seconds, at most. Then my mind snaps back into its default groove— remembering all the things it wants to be. The roles. The performance. The problems to solve.

But that glimpse is enough. Enough to know that something deeper is possible. And not just possible—but necessary, especially in the face of exponential tech + change.

So what is that thing? And how do we hold onto it in spite of our inner tyrant?

We need a new perspective. A new mental model for reality; for what experience really is (and isn't).

And to achieve this, we need new tools. Or as I like to say, we need to use tech to combat tech. A form of jiu jitsu, if you will... using tech's momentum against itself.

Towards that end, we won't negate the self head-on. We'll first zoom out and move up stream of subjective experience.

We have to look at our environment and our relationship with it. Only then can we answer the ultimate question: if we're not a 'self', what are we? Because a mere 'story' feels... unsatisfying.

The answer is multi-layered. This essay will peel back each and expose the kernel of what makes the human experience so unique.

What I've found, is that the deeply human is paradoxical. It suggests we are beyond being just merely human...

Persons vs. Selves

So what are we?

The most direct answer I’ve found comes from modern day philosopher Jay Garfield.

In his his book, Loosing Ourselves, Garfield argues that we’re not fixed “selves” floating above the world—we’re “persons,” embedded in it.

What’s the difference?

A self is imagined as independent, essential, and constant. It's somehow... pre-existing, or prior to.

A person is none of those things. A person is a process—a pattern—a psycho-physical dance that only exists because of its entanglements with everything else; our biology, our social interactions, and our ongoing experiences.

The common metaphor in Buddhism is a wave on the ocean. A 'self' is the mistaken belief that you are a separate, independent drop of water, riding the wave.

A 'person' is the wave itself—a temporary form that is inseparable from the ocean it emerges from, shaped by the winds of culture and the tides of relationships.

As a pianist, I prefer the analogy of music: a person is more like a song—it only exists while it's being played. It is the interplay of notes and the instrument, not some hidden essence behind them.

In other words, we don't pre-exist and then decide to interact with the world; we emerge from it. We are a messy, dynamic, and beautiful tangle of our genetics, the language we speak, the culture we inhabit, and the people we love.

This isn't just a semantic game. It's a fundamental shift in our operating system. And this new OS matters, because the isolated 'self' is a fragile target for this next wave of tech/AI; easily hijacked by algorithms.

But a person?

A person is (as Bruce Lee would say) like water. It's fluid, adaptive, and finds stability not in separation, but in connection, with nature and with other people... Real people.

Spotlight vs Floodlight Consciousness

To further ground this idea, I turn to Alan Watts—a thinker who, in my view, revealed some of the deepest truths about modern affliction.

If Garfield gives us the academic language of “persons,” Watts gives us the poetic, spiritual framework for where we fit in. He tackles the same illusion but zooms out—from the mind to the cosmos.

In this lecture The Myth of Myself, Watts argues that our core delusion is the idea of the “skin-encapsulated ego”—that little ‘me’ we imagine trapped inside our heads, peering out at a foreign world. This hallucination splits “self” from “everything else,” casting life as a battle between a lonely subject and a cold, indifferent universe.

We feel like strangers here—confronting reality, facing facts, trying to conquer nature. Poet A.E. Housman said it best: “I, a stranger and afraid, in a world I never made.”

Watts traced this alienation to what he calls "two myths of the West".

First, is the myth of the universe as an artifact, i.e. a pot crafted by a cosmic potter, aka 'god'.

This is the religious view. And it makes us feel perpetually judged, like we’re on divine probation, perpetually proving ourselves worthy of existence (in this world or the next).

Then came the scientific view. This produced the myth of the universe as a cosmic fluke, i.e. an aimless probability machine, powered by blind energy. This view makes us feel like a meaningless accident.

One makes us sinners, the other specks. Both leave us feeling unfulfilled and like we don’t belong.

To rectify, Watts offers a third story. He argues that the universe isn’t a top-down creation, nor is it a bottom-up accident. Rather, it’s an intelligent, self-expressing organism.

And its form expression?

You, me, us.

We aren’t a fluke of the universe; we are a feature of it. Watts famously says, just as an apple tree “apples,” the cosmos “peoples.” We didn’t arrive in this world—we emerged from it. Like a leaf from a tree, we are functions of the universe, not anomalies within it.

So where Garfield’s “person” emerges from a social and biological context; Watts’ “you” emerges from the entire cosmos. It’s the same idea, just at a different resolution.

We are what the whole cosmos is doing at the place we call here and now. Each one of us is a unique "waving" of the entire universe.

But if this is true, why do we feel like a lonely pilot in the skull? Why the profound sense of separation? Of subject and object?

Watt's creates a bridge between cosmic truth and psychological illusion. He explains that our feeling of being a separate ego is a direct result of specializing in one particular form of consciousness, while ignoring another.

Those two forms are "the spotlight and the floodlight".

The spotlight is conscious attention. It’s the narrow, focused beam we’re trained from childhood to value above all else. When a teacher says, “Pay attention!” we fix our minds on one thing at a time. Our culture teaches us this capacity matters most. And so we believe, “I am my spotlight consciousness. That is my ego. That is me.”

But floodlight consciousness is always on. It is the vast, peripheral, holistic awareness that drives the car for miles while your spotlight is busy chatting with a friend. The floodlight is what beats your heart, grows your hair, and registers the entire field of sound and space around you without you “thinking” about it. Every nerve ending is its instrument.

The illusion of being a self is simply the habit of mistaking 'spotlight consciousness' for the whole show.

We’ve forgotten that we are also the floodlight. The floodlight is the waving cosmos, the entire field of being. The spotlight is just where the floodlight—the universe itself—has decided to focus its attention through you, for a mere moment.

Becoming aware of this is the mystical experience you hear about through meditation, psychedelics, and even states of flow. In these moments, you realize your real, deep self is not the fleeting beam of attention, but the entire field of awareness it moves through.

As Watt's states in his talk, you are not the headlight, unaware of the battery it’s wired to. You are the whole circuit.

Realizing this dissolves the ultimate fear... The fear of death. An isolated spotlight can be switched off. But the floodlight, the great field of being, simply transforms.

The wave returns to the ocean it was never separate from.

As Watts would say, you are the eternal thing that goes and comes. One day, you wake up, look out at the stars and realize, “Why, that’s me.”

Subscribe now

Neuro-Tech Buddhism

This might all sound a bit too hippy dippy woo woo for you.

It might also sound too abstract, if not entirely out of reach.

I felt the same way. These ideas tickled something deep in my being, but they remained slippery. And I struggled to see how to make them land for average Jane/Joe.

And then I came across a quote from one of my favorite authors, Ursula Le Guinn.

It echoes the same problem called out by Watts: the divide between humans and nature, and the resulting alienation.

Le Guin says:

"One way to stop seeing trees, or rivers, or hills, only as ‘natural resources,’ is to class them as fellow beings—kinfolk. Subjectify them, instead of objectifying them. I guess I am trying to subjectify the universe, because look at where objectifying it has got us. To subjectify is not necessarily to co-opt, colonize, exploit. It may involve a great reach outward of the mind and imagination."

A great reach outward... of the mind and imagination.

Well, if there's one tool capable 'subjectifying, and extending the mind... it's our favorite topic de jour: spatial computing, aka virtual reality, augmented reality, mixed reality, etc.

This brings us full circle, back to modern day philosopher, Thomas Metzinger.

If Le Guin calls for a new kind of perception—one rooted in kinship, not conquest. Metzinger suggests a way to build it, with spatial computing + AI.

I've explored similar use cases in my previous essays.

The first was the Ultimate Promise of the Metaverse back in 2021:

I think the key to mental resilience and joy are regular reminders of everything that exceeds us. Things that disintegrate the ego and remind us of the smallness of our everyday lives. Things that remind us we are mere dust in the cosmos, made of the stars themselves. That we are, as Carl Sagan said, “a way for the cosmos to know itself”. We need daily doses of something similar to the famous ‘overview effect’ that astronauts express when viewing the earth from space. What if the Metaverse could be littered with ‘overview effects’? On-demand experiences that would allow us to feel a connection to the grandness of the universe and the miracle of our own consciousness?”

I continued this thread in ‘The Ultimate Promise of Spatial Computing’, exploring the science of awe and its capacity to rewire us from the inside out:

“The ultimate conclusion? Awe shifts our focus from the self to the vastness of the external world, creating a sense of connection and well-being, while promoting greater generosity and cooperation. Towards this end, the researchers explore simple daily activities, such as taking an "awe walk" and intentionally noticing beauty in the world. Nature-based 'awe walks' will and should always be our first option. But 'awe on demand' via 'spatial/salient computing' could become the next best thing, with arguably more magic and tastefully curated forms of novelty, curiosity, and surprise. While virtually induced, I don't view these transcendent mind-states as disconnected from reality. They just might be the most real experiences we can have…”

Metzinger holds similar beliefs, viewing immersive tech as a way to hack our inner tech and reveal truths about the self; a kind of flight simulator for consciousness.

If you recall from Part I, Metzinger’s big idea is the "Phenomenal Self-Model"—the internal avatar your brain stitches together from a constant flood of signals: sights, sounds, memories, and bodily sensations.

Because that avatar is a construction, AR/VR can hijack and remix those signals, revealing the seams. A well-designed simulation, he argues, could grant ordinary people the kind of ego-softening insight that monks and mystics have pursued for millennia, but with a crucial twist: under controlled, reversible, lab-grade conditions.

He imagines a variety of tools for playing with the source code of identity:

A Dial for the Self: A virtual slider that lets you increase your sense of agency, until the entire scene feels like "you," then fade it out until you are nothing but a pure witness to the world.

Embodiment Hacks: The ability to body-swap into an avatar with elongated limbs, an animal’s form, or a different gender, showing just how effortlessly the feeling of "me" migrates to a new home.

AI Hijacking: You control a virtual body, but occasionally, an AI agent takes over your limbs. An action happens, but you didn't do it. The clean line between your intention and the world's action begins to blur.

Reality Faders: A simulation where the world’s textures slowly morph from photorealistic to overtly synthetic, allowing you to feel the precise moment your brain’s faith in an “outer” reality begins to crack.

The goal here isn't just a joyride. In pairing these experiences with brain-imaging technology, we can turn VR suites into engineering labs for the mind.

We could finally map how agency, body-ownership, and perspective click together—and potentially learn how to therapeutically loosen their grip in conditions like PTSD, depression, or chronic pain.

But like all frontier tech, this can cut both ways.

These tools would be like a digital psychedelic: potent, reality-bending, and profoundly double-edged. Without strict, open-sourced ethical guidelines, it could easily become a black-box for persuasion and addiction.

We would need to figure out the right measures of success/impact. Some way of separating a 'trippy novelty' from what ancient Greek's called 'eudaimonia', aka our capacity for well-being, flourishing, and realizing one's full potential.

If so, and if designed with wisdom, tomorrow’s headset may one day sit beside the meditation cushion as a core tool for waking up, proving that the wildest frontier isn’t outer space, but the inner cosmos of the mind itself.

Epilogue

Many people will resist these use cases and this future.

But the truth is… it’s inevitable. The train's far down the tracks. These simulations will exist, whether we like it or not.

The key will be to never forget: they’re still simulations; a means, not an end. A compass, not a destination. Perhaps technology can help here as well.

Regardless, the most powerful reminders of our true nature won’t come from code. They’ll come from something softer. Warmer. Human.

For me, that's now a baby, blinking up from her crib.

As I write these final words, Chloe sleeps peacefully, blissfully unaware that she's already living the truth I've spent thousands of words trying to uncover.

She doesn't yet know she's supposed to feel separate. She hasn't learned to hallucinate a solid self. She simply is.

Which makes me wonder...

Maybe the real revolution isn't in the technologies we'll build, but in remembering what we were before we forgot what we are.

Maybe the future of consciousness isn't about transcending our humanity, but about relaxing into it more completely.

Because as we've learned, the deeply human is yet another paradox. It shows that we are beyond being merely human.

As such, the illusion of self isn't a problem to be solved, but a game to be played more consciously—with more humor, more lightness, more love, and certainly... way less anxiety.

After all, if the self is just a feeling, and there's no one here to take credit for this essay, then there's also no one here to be worried about getting it wrong.

And that, perhaps, is the most liberating feeling of all.

THE END

If you made it this far… THANK YOU for making the time + effort.

I hope you enjoyed the journey and feel more prepared for this looming era of extreme change. If so, please consider sharing this essay with a friend or two. The more self-less 'persons’ out there the better ;)

In Part I, we defined the 'Self' and explored its origins.

In Part II, we explained the illusion and how to grasp it (by studying babies and realizing you 'have no head').

Here in Part III, we're taking a more empirical approach. It will make you question… well, just about everything.

If you haven't read Part I & II, highly recommend doing so, else this essay might not land 🙂

• Part I link here

• Part II link here

But I get it. Time is money and money is time, so here's an all-too-short recap: the self you think you are, that pilot behind your eyes, isn't what you think it is.

It's not a persistent, stable entity (e.g. a soul, an independent 'you' that exists across time & space). It's just a feeling, produced by a sophisticated model—weaving sensory data, memories, and social feedback into what feels like a coherent, persistent self.

Said another way... while the self is real as an experience, it is illusory as an actual object (in both our internal/external worlds). It's just evolution's biological user interface—helping a body navigate complexity without being crushed by it.

My favorite explanation comes from cognitive scientist Donald Hoffman, and his book The Case Against Reality.

Hoffman argues that evolution has not shaped us to see the truth, but to see what helps us stay alive and pass on genes.

His analogy is striking (if not a bit disturbing): all of reality is like a desktop interface. The icons on your screen don’t reveal what’s actually happening inside the computer—they give you a simplified, usable illusion.

The self is just one of those icons. It’s not real in the way it appears—but it helps you navigate the game.

This can be hard to believe. It implies our (internal & external) perceptions are some sort of lie. But as this essay reveals, at a fundamental level, that's exactly what they are. Lies. Or at the very least, white lies…

The Empirical Truth

Indeed, your brain hides the truth. It does not deliver raw data about the world. What feels like a live broadcast is really just a post-production, editorial suite (and sorry... but you aren't the editor).

I’ll explain with the most basic of games: a race.

Races don't start with a flashing light, they start with the crack of a gun.

But why? Light travels much faster than sound. Isn't it a better signal?

Nope.

Light travels faster but it takes longer to process through the neural cortex. In fact, all of our senses are on their own schedule; they hit our brains at different times, through different channels. Yet somehow, they seem in sync…

Neuroscientist, David Eagelman, has done multiple experiments on this front, revealing how our brain sorts and times our senses.

The first experiment is simple. Participants press a button and then see a light flash on a screen.

They continue to do so, but what they don't realize is that Eagleman is introducing a slight delay each time. Just 10 milliseconds at first. Then 20ms. Then 30ms, all the way up to a 200ms delay in the real world.

But as this happens, their brains don't perceive the delay. They re-adjust. Their brain tells itself, "I've done something and I should get something visual back, so let’s just adapt to this delay".

After a while, their brain gets used to it. But then suddenly, Eagleman removes the delay.

This time, when they hit the button they’re jostled with surprise.

The system glitched. They see the light flash before they fully press the button. As if the effect had caused the cause.

But that's not what happened. It didn't glitch, they did. In the physical world, the light went off as it should: after they pressed the button.

So what's behind this sensory flip?

Something called postdiction, i.e. your brain's tendency to finalize reality a moment after an event.

It quickly gathers recent sensory data, then retroactively constructs the most coherent story. Expecting a delay between a button press and a flash, its removal caused the brain's internal model to misfire, making the flash seem to precede the press.

This is not a bug in the brain—it’s a feature. The brain had rewritten its expectations and adapted to the altered world. When that world snapped back, it didn’t re-adapt fast enough.

Instead, it created an illusory reversal of cause and effect.

This illusion doesn't just happen with vision. It also happens with sound, touch, and even intentionality.

Indeed, we've found a rip in the Matrix; a window into how our brains construct reality—not as a live stream, but as a best-guess reconstruction, edited after the fact for narrative coherence.

More simply stated: your brain isn’t showing you the world as it is. It’s showing you a version of the world it thinks makes sense. And that feeling of "you" as a coherent self—acting with free will, in real time—is part of the constructed story.

The crazy part is that this is all by design. Evolution didn’t care about showing you the truth—it cared about keeping you alive. A coherent sense of self, like a coherent perception of a flash, is a useful shortcut. It helps you navigate the world without drowning in sensory chaos. But it’s not reality. It’s fiction.

And this shows how far your brain will go to keep the story consistent— even if it means bending the truth.

This brings us to perhaps the most dramatic evidence of your brain’s narrative prowess: studies of people whose brains have been split in half…

Subscribe now

One Skull, Two Selves

These editing tricks don’t stop with vision. The same narrative machinery shapes your sense of self, agency, and free will.

No experiment reveals this more clearly than the famous split-brain studies.

In the 1960s, neuroscientists studied patients who had undergone a rare surgery to treat severe epilepsy: cutting the corpus callosum, the thick neural bridge connecting the brain’s two hemispheres. As a result, two brain halves are now unable to communicate.

You’d expect total dysfunction. But strangely, these patients seemed fine. They could walk, talk, and go about life as if nothing had changed.

Until researchers looked closer.

They devised an experiment to send visual input to just one hemisphere at a time. The right hemisphere (which can’t speak but controls the left hand) was shown a snowy scene. The left hemisphere (which controls speech and the right hand) was shown a chicken claw.

Then came a test: the patient was asked to point to related images. The left hand picked a shovel (to clear snow). The right hand picked a chicken (for the claw).

When asked to explain both choices, only the left hemisphere could respond—and it had no idea the right hemisphere had seen snow.

You'd expect the patient to say something like, "Well, I picked the chicken because I saw a chicken claw, but I have no idea why my left hand chose a shovel."

Instead, the patient’s left hemisphere confidently said: “The claw goes with the chicken, and the shovel is to clean out the chicken shed.”

A complete fiction—but told with total confidence.

This is the brain’s default move. When it lacks information, it doesn’t stall or admit confusion—it fills in the blanks. Not to deceive, but to preserve the feeling that everything is part of one smooth, intentional, (you guessed it) story.

Neuroscientist Michael Gazzaniga, who led many of these studies, called this built-in narrator “the interpreter.” It’s like your brain’s PR agent—always spinning a narrative, even when it has no direct knowledge of the events. It values coherence over truth. Narrative over facts.

And this need for unity runs deep. In other split-brain experiments, the two hands—controlled by different hemispheres—actually fought. One hand would reach for a shirt, the other would swat it away. One hand would start a task, the other would try to stop it.

Two minds in one body, in complete disagreement. Talk about internal conflict…

All of this underpins our initial thesis: there’s no single self in charge. The “you” you feel is the interpreter’s creation—a tidy story woven from messy, distributed processes (or multiple ‘selves’).

This brings our journey full circle. Just as newborns reveal the self as a learned construct, and the Headless Way shows no solid "you" at the center of experience, split-brain experiments deliver our final blow to the myth of a single, indivisible self.

Your brain can operate like a divided government with multiple selves running in parallel, and the "I" you think governs it all is just one part of the system—often the last to know what's going on.

Which raises an even deeper question: if the self is a story, who—or what—is the author?

We'll explore this question and more in Part IV... stay tuned. Or, if you want to jump ahead, by all means. Hit this link here → Part IV | Future-Proofing Your Self.

In Part I, we defined the 'self' and explored its origins through the lens of science, philosophy and religion.

In Part II, we'll explore ways to see the illusion.

But first, let's align on the core argument here and why this effort matters.

When we say the self is an illusion, we are not denying that we exist.

Rather, we are attacking a very specific instinct — the feeling that there is a separate, unified "me" who owns a body, who owns mental states, and who acts independently (rather than causally) upon the world.

Our ultimate goal is to replace the mistaken idea of 'a self' with a more grounded understanding of what we really are: 'persons'. This idea comes from modern day philosopher and academic, Jay Garfield, via his book, Losing Ourselves.

Garfield defines persons not as pre-existing, independent selves, but as... "dynamic patterns constructed through ongoing relationships and social interactions."

Unlike the illusory “self” that seems to float above our lives, directing things from the outside, a person is more like a song — something that only exists while it's being played.

We emerge from the interplay of biology, culture, language, and experience, not apart from it.

Said another way… Illusions are not about complete non-existence; they involve something existing in one way but appearing in another. A mirage, for instance, is a real pattern of light that might appear to be water.

Likewise, a person exists as a real, socially and biologically embedded being. But it appears to be a separate, autonomous self.

The alternative is recognizing that we exist not as independent selves but as persons: physical beings embedded in networks of causes and conditions, social beings shaped through language and relationships.

We do not pre-exist and then interact with the world; we emerge from it, constructed through our biological bodies, our cultural context, and our interactions with others.

Our inability to grasp this is so natural, so automatic, that entire civilizations have been built upon it. As mentioned in Part I, The Greeks spoke of the "psyche," Christians of the "soul," Indians of the "atman" — all different ways of trying to name the mysterious "me" inside the machine.

But trying to define the self is like trying to measure how deep the water is in a mirage — the thing you’re seeing/feeling isn’t actually there.

The truth is, we aren't isolated pilots. We are more like waves on the ocean — shaped by the winds, tides, and other waves around us.

Like a five-dollar bill, we’re real not because of some intrinsic essence, but because of the roles, meanings, and agreements that give us form. To understand yourself, you don’t need to look within for some hidden core — you need to look around at the web of causes and conditions that make you who you are.

This reminds me of one of my favorite quotes.

"I am not who I think I am. I am not who you think I am. I am, who I think, that you think I am..."

Read that again. Chew on it. It’s this quote that sparked my curiosity on this topic…

And yet… even if this makes sense intellectually, the moment you stop thinking about it, you snap right back into the old operating system. The sense of “I” returns like a reflex.

So how do we stay rooted in this insight? How do we not just understand it — but see it, feel it, live it?

I don’t have the full answer, but I have uncovered a set of ideas, metaphors, and mental models that can help.

And it starts at the beginning, with how we all began... as babies :-)

Subscribe now

A newborn truth

I've spent the last couple years wrestling with all the big ideas here, spanning ancient philosophy, cutting-edge neuroscience, zen koans, etc.

And then last month, the clearest clue arrived: our newborn baby, Chloe.

Before language, before memories, before the world teaches us who we are, her experience reveals part of the answer: the self isn’t something we’re born with — it’s something we build.

According to developmental neuroscience, a newborn’s brain hasn’t yet developed the systems needed to separate “me” from “not-me.” Core abilities like proprioception (sensing where your body is), interoception (feeling your internal states), and multi-sensory integration (connecting sight, sound, and touch) are still maturing.

As a result, newborns live in what some scientists call an “undifferentiated soup of sensations.” Their vision is blurry. Their body map is incomplete. They don’t yet feel like a defined someone having experiences — they just are. That’s why one baby’s cry can trigger another’s: the line between self and other hasn’t solidified yet.

Even the brain’s Default Mode Network — the system responsible for self-referential thought and inner narration in adults — is mostly inactive in early infancy. It only begins to come online over months and years, reinforcing the idea that the self is a developed feature, not a built-in one.

Psychologists have long described this early stage as “primary narcissism” or the “oceanic feeling” — where the infant feels no clear separation from the caregiver. When a baby is held or fed, it’s not yet experienced as something done by someone else. It just happens. It’s only through repeated interactions — “when I kick, I see movement,” or “when I cry, someone comes” — that the brain begins to form patterns.

These patterns eventually give rise to a sense of agency and of self.

Milestones like recognizing themselves in a mirror around 18 months mark an early step in this construction, but even that is just the beginning.

This developmental arc aligns perfectly with the understanding that the adult self, despite its convincing feeling of solidity and permanence, is an emergent phenomenon; a "useful fiction" or "controlled hallucination," as Anil Seth suggests.

Newborns are the ultimate proof: they don’t "lose" a self or struggle with its illusions; it simply doesn't exist, yet.

The “I” we hold so dear, the inner center of experience, is gradually assembled through physical interactions, social mirroring, language, and memory.’

In other words, we aren’t born with a self; we learn to hallucinate one.

This might sound startling, yet it's validated by science. The boundaries we perceive between "me" and "not me" are not absolute givens. They're learned constructs, essential for navigating the world but not necessarily reflective of an inherent separation from it.

Why does this recognition matter?

Because it challenges our most fundamental assumptions about identity and liberate us from the confines of a rigidly defined ego.

If the self is a construct, it implies a degree of malleability and a deeper, perhaps forgotten, connection to the world.

Babies are the ultimate reminder that identity isn’t fixed. That we’re more fluid, more connected, more open to change than we think.

Beneath all the stories we tell ourselves, there’s still a trace of that original openness — that quiet, 'newborn truth' we came into the world with. And maybe, just maybe, we can find our way back to it.

Now, if you're like me, this might sound like a bunch of mystical mumbo jumbo — 'connection to the world', 'openness'. It's just all so hand wavey.

What does it really mean?

I used to write this stuff off. Until I stumbled upon something I couldn't deny…

That I have no head.

The Headless Way

If I told you that you have no head, you’d probably look at me like I have two.

I know I know, it sounds ridiculous. But there's a (disturbing) line of inquiry that makes it hard to ignore, if not plausible. It's also one of the more profound ways to think about the illusion of self, and to level set on what we really are…

The idea comes from Douglas Harding, a British architect-turned-philosopher who coined the “Headless Way.” His big insight wasn’t born from some ancient manuscript or psychedelic trip — it came during a walk in the Himalayas.

During his trek, he paused, looked down at his body, and then out at the mountains. In that moment something clicked: from his own direct perspective, there was no head. No face. No eyes. Just a wide-open field of vision, containing the world — his legs, the path, the sky, the peaks — but no “thing” doing the seeing.

The “me” he’d assumed lived behind his eyes was experientially absent.

His famous quip was, "I lost a head and gained the world."

What Harding realized is something most of us never question: we assume we’re looking out of a head, but we never actually see that head from our first-person perspective. It’s always inferred — never observed.

In other words... you can see your hands, your legs, your shoes, and the furniture around you. But if you try to see your own face—without using your phone’s camera or a mirror—you can’t. From your own point of view, your face is invisible. It’s just not there.

Rather, you’re just aware of everything in front of you. It’s like you’re a space or an opening through which the world appears. Other people see your face, but you never do directly.

This is difficult to intuit, so Harding created a simple experiment to help people (at least begin) to understand…

First, point at things around you—your shoes, your friends, the wall. You see them clearly.

Next, point back at your own face. What do you see?

Nothing—just the world in front of you.

The idea is that, at the center of your experience, you’re not a person with a head looking out—you’re more like a camera lens or a window: open, clear, and empty, with everything appearing in that space.

It's worth pausing here and letting that sink in…

When I first heard this, it hurt my brain. So here are a few metaphors that helped me understand.

Think about the nature of a window. The window doesn’t see itself; it’s just the opening through which you see everything else.

Similarly, think about a camera. The camera never photographs itself; it just shows what’s in front of it.

Now, consider the sky. It's open and empty, and all the clouds and birds just pass right on through.

Useful, I hope... But Harding wasn’t just being metaphorical.

He insisted this was a literal description of experience. What we see in the mirror is a construct — a few feet away, from another perspective. What others see is a socially agreed-upon “you.” But what you find at (what he called) 'zero distance', from your own center, is not a head looking at the world — it’s an empty space filled with the world.

So, what does this mean?

It means your true “self” isn’t a thing you can see or point to—it’s just an open awareness where all your experiences happen.

It’s a way of seeing yourself that’s very different from how you usually think about being a 'self/me' with a face and a head. Instead, you’re the space where the world shows up.

This 'space' sounds a lot like Garfield's notion of us as 'persons', not selves…

Indeed, Garfield and Harding are saying the same thing, but with different tacks.

Garfield says we're not selves separate from the world, but persons mediated by it and within it.

Harding would say... you are not a thing among other things. You are “No-thing,” and precisely because of that, you are the space in which everything appears.

This might just sound like a fun philosophical trick. But I assure you, as I spend my nights tending to a crying infant, changing diapers in a complete stupor, this has real world implications.

Seeing your “headlessness” disrupts the automatic belief that you are a separate, located ego trapped behind a face. It interrupts the habit of thinking of yourself as an object in the world, and reveals a more immediate, more intimate reality: that your true nature is open, borderless, and deeply connected.

This shift can bring psychological relief, (especially when mid diaper change, you suddenly yourself being both pooped and pee'd on).

You’re no longer a vulnerable little self perched behind the eyes, trying to manage a chaotic world. You are the space in which the chaos appears — and that space is untouched, undisturbed. It’s free.

Harding also noticed how this shift changes relationships.

When you see that you have “no face” here, you become space for the faces of others. Interactions become less confrontational — not face-to-face, but face-to-no-face. You’re more present, more available. Less busy protecting a self-image, more attuned to the world around you.

And the deeper you go, the more freeing it becomes. If the “self” you thought you were isn’t actually here, then what is there to defend? What is there to lose?

Well, for starters: the fear of death, the pressure to perform, the need to constantly assert your identity — all of it starts to loosen its grip.

This is what Harding meant when he said the Headless Way leads to “the peace that passeth all understanding.”

Not because you believe in some abstract truth — but because you looked, and noticed what’s always been right here; no head. No center. No thing. Just this wide, open space — quietly holding the world.

Making this applicable

If this topic interests you, check out Harding's book, On Having No Head. It's an esoteric gem and Harding wielded it for sixty years, trying to convince people to test this claim for themselves.

If only he was alive today... he would have known, this was his theory's moment.

Because that empty center he speaks of... it's the one dimension Silicon Valley can’t hijack.

Sure, algorithms can bend your preferences, curate your desires, and even clone your voice. But they can’t colonize a vacancy.

When you recognize the center as spacious, the latest mimetic frenzy on your feed loses sticking power. There’s no inner Velcro for it to latch onto.

Think of headlessness as a “psychotechnology", i.e. a perceptual trick you can deploy in the checkout line when your toddler erupts, or right before presenting quarterly numbers to a board of caffeinated VCs.

Pop the hood, notice nobody’s driving, and the nervous system resets to factory settings of ease and attentiveness.

To make this more visceral, here are are some personal 'day in the headless life' moments:

It's early morning. Too early... I stumble to the sink, baby monitor crackling on the counter.

Toothbrush in hand, I catch my reflection. A familiar father-face stares back, but here on this side of the glass? Vacancy. The mirror becomes a frame around the scene rather than evidence of a cramped identity.

Chloe wails; sound erupts inside the same openness. I respond, but the response arises unforced, like weather.

Now, the dreaded afternoon Zoom call. Ten rectangles float on the screen, each a curated persona. I toggle gallery view off and drop into headless seeing: colleagues speak; words appear; my own voice joins the mix; nowhere is there a solid epicenter absorbing credit or blame. Ironically, performance improves when there’s no one to impress.

The day's winding down. I'm on an evening stroller walk. Sunset flares across Austin’s sky. In place of “I’m under the sky,” the sentence flips: “Sky, trees, stroller, wife—all appear inside … this.” The boundary between inner and outer crumbles. I'm not zoning out; I'm tasting the scene without the usual packaging.

Objection handling

In closing, let's arm you with some objection handling. Because no doubt, they're going to come, be it from that little voice in your head, or a friend during happy hour.

Here are some of the most common…

“Isn’t this just escapism?” It would make for a strange escapism... given that headlessness drops you more fully into sensations than the normal selfie-centric mode. You’re not transcending life—you’re removing the tinted goggles.

“If there’s no self, who raises the baby or answers the email?” Tasks still get done. The spreadsheet edits itself the same way your heart beats itself. Agency functions, but minus the tight-fisted claimer of agency. It's responsibility without the migraine.

“Sounds cool, but doesn't it fade?” Yes. The default mind springs back like memory foam. Harding recommends dozens of micro-glimpses a day— a finger point, a mirror flip—to erode the reflex. He saw practice not as climbing a ladder toward enlightenment but remembering a joke you keep forgetting to laugh at.

But let's be honest, it's unlikely you'll find time to point at objects and then back at yourself, especially when it might be needed most, in public…

As such, we must go deeper into your programming, and hack it from the inside out.

Doing so starts with realizing the extent to which your mind is already an expert hacker in itself, keeping you from seeing what's actually happening, out there in the 'real' world (all for evolutionary benefit).

We’ll cover all this and more in Part III, by studying some scientific experiments that more empirically lift the veil. But if you want to jump ahead, go for it! Hit this link here → Part III | Future-Proofing Your Self

You've likely heard this idea before, i.e. the illusory self, nonself, nonduality, emptiness, etc. It's an ancient concept. One that has haunted and liberated the most introspective among us for thousands of years.

But like most ancient practices, it's woefully underutilized, under studied, and relegated to the realm of monks.

Fortunately, a resurgence of Buddhism, mindfulness, and meditation has put this illusion back into scope, at just the right time. A time when technology and AI is about to warp our sense of self, including all of its inputs: identity, agency, even free will.

As such, the illusion of self is no longer just a mystical inquiry. It’s a survival skill; a precondition for psychological sovereignty in the age of AI.

This distortion will bring many oddities and risks, some knowable, most not... But fortunately, they all rest on a single assumption: that beneath it all, there’s even a solid “self” to begin with; a persistent 'center' of being in the cross hairs.

This essay will help you challenge this assumption.

It's a collection of ideas, exercises, and experiments to help you not just understand the illusion intellectually, but to feel it experientially, and ultimately, live from the truth and freedom it reveals.

To be clear, I’m no guru. I’m far from an expert on this stuff. I’m just a guy trying to become a better father, friend, and leader. I’m also trying to become a more independent thinker, unmediated by the wants and needs of the outside world. Towards that end, I’ve tried all the things; all the self help books, the plant medicine, and the therapy. Each was useful in its own right. But this is the thing that has grabbed me most. It’s the furthest upstream, hitting the roots of all suffering, and of most all our modern day plights.

In the end, you’ll leave realizing this illusion isn’t just theoretical. It's structural, empirical, and becoming increasingly validated by science. And in an age of infinite avatars, curated identities, and AI companions, it's also becoming a dangerous trap.

Now, I'm far from free of it (hence the reason for this essay). But when I encounter those who are —people who radiate a certain stillness, clarity, and responsiveness—it’s clear that dissolving the illusion doesn’t detach them from life. It roots them more deeply in it. They move through the world with a grace we’re all quietly yearning for. A grace that will be critical in the exponential age.

Because one thing has become certain. This new era will indeed bring abundance. But largely within the material world. Our inner world faces a scarcity of meaning, purpose, and groundedness, largely due to a sense of self that will be maximally malleable, programmable, and monetizable.

The time to start preparing for this future is now. Doing so will involve a seemingly strange but profound set of perspectives and tools, from seeing that you have no head, to not wanting to ever trust your eyes again, to embracing your lack of free will.

So with that, let's begin, starting with a life update that sparked this whole pursuit.

A Wake Up Call

Life just changed in the most meaningful way.

We had a baby girl!

Her name is Chloe and she's a warm, wiggly, cooing bundle of joy, tucked into the pouch of my new 'kangaroo' shirt as I write this essay.

She's also a wake up call; to get out of my head and become more selfless.

No small task... I've always been more self-centered than I care to admit; lost in my inner world and tormented by a tyrannical ego; whipping me incessantly towards a better version; smarter, richer, funnier, more accomplished, more... admired. Psychologist call this 'the idealized self': a mask built not from who we are, but from who we thought we had to be to earn love and escape shame. This result is a collage of childhood pain, cultural ideals, and personal distortion.

Perhaps you know this feeling. It's a constant inner competition with yourself. But win or lose, the result is often the same: tension, guilt, exhaustion, and a burning frustration that these feelings even exist.

In our youth, this tension is useful. It fuels ambition as we carve out a place in the world. But as we get older, it starts to backfire, especially as other 'selves' begin to matter more than just our own; a life partner, a child, an employee. These people need us to show up in a different way.

Yet more often than not, we remain lost in the labyrinth of our own becoming.

Quite the paradox... how the act of becoming becomes the very thing keeping us from who we want to be.

This tension is a tale as old as time. But now, the labyrinth is evolving. Technology is warping it into a black hole. Tiny screens and algorithms fuel the 'act of becoming' on the grandest of scales, in the most profound of ways.

The net effect? We get what we want on demand, but rarely what we 'want to want'.

Philosopher René Girard called this mimetic desire — the idea that we don’t create our own wants/desires, we unconsciously borrow them, copying what others around us seem to want; their ambitions, their preferences, their ideals. More often than not, we don't intrinsically value these things. Our unconscious psyches just see someone else getting love and attention for having them, and decide to pursue the same.

Mimetic desire has always been part of the human condition, but it's inflamed by social media and influencer culture, and now being super charged by AI. Hell, the influencers are becoming AI's, leading us to crave the fullest forms of fabrication.

Needless to say, we're hurdling towards a strange new world, defined by virtual worlds and avatars, AI agents and AI companions, brain computer interfaces and gene editing.

When any person can be a curated projection, and every digital space invites you to perform a new persona, the question of “who am I?” isn't just philosophical— it's practical.

So... who are you? What exactly is this feeling of a self? Here’s my working definition and a target for our inquiry.

Subscribe now

Understanding the Self

For most of us, 'the self' is the main character of our story. It's the feeling of 'me' at the center of experience; a fixed entity who thinks, feels, decides, and acts. It's the pilot living in your head, with a personality, wants, dreams, and desires.

This feeling is so intuitive, so innate, that questioning it almost feels absurd. Of course you are you, and I am me, and well... that's just that. End of story.

But modern neuroscience offers a different story. According to cognitive scientist Dan Dennet, our sense of self is just a 'useful fiction', a mere narrative we tell ourselves, about ourselves. And to be fair, it's very useful, indeed. I need to think of myself as a father, a husband, a business partner— if only to make it through the week, much less excel at each.

As such, it's important to clarify: this is not the sense of self worth challenging. What we're targeting is more fundamental and subtle.

It's also the greatest source of suffering. It's the feeling of being a subject internal to our bodies; a mini-you behind your eyes. This version of self — an ego both produced by and identified with thought — is where the burden lies. Fortunately, it's also not a solid, concrete thing. It's a simulation. Or rather, to draw an eerie parallel to our new AI friends, it's a generative model.

Philosopher Thomas Metzinger calls it the Phenomenal Self-Model — a kind of internal avatar your brain assembles to unify experience and track itself in the world. And it works beautifully, stitching sounds, colors, smells, sensations into a coherent tapestry of “subject object"—instead of a random chaos of disconnected inputs. Neuroscientists call this 'sensory integration'.

But—and here’s the uncomfortable part—this model doesn’t reflect reality directly. It constructs it.

Take color: there’s no green “out there” in the world, only light waves bouncing around. Your brain interprets those waves and gives you the ‘feeling’ of greenness—what philosophers call qualia, aka the subjective, felt qualities of experience; the "what it's like" aspects of mental states.

As for the ‘self’, this feeling is what neuroscientist Anil Seth calls a 'controlled hallucination'. And it's entirely convincing because it’s transparent — we don’t see it as a 'model'. We just see it as me. One major reason for this is memory. It convinces us there's a stable 'me' who persists over time.

Now, by this point, some of you might be nodding along. “Sure,” you might say, “I get it. The self is fluid. I’m not the same person I was ten years ago. I’m a socially influenced, ever-changing mix of biology and psychology. I’m fine with that.”

And yes, that’s a perfectly valid view.

But even if you intellectually accept that the self is a construct, notice what still lingers beneath: a quiet but persistent sense of being someone—a distinct “me” behind the experience. A self who has a body and mind, but is somehow separate from both.

This is embedded in our language. In the West, we don’t say “I am a body.” We say, “I have a body.” That subtle phrasing reveals everything.

As a quick thought experiment, let's play with our innate capacity for imagination and desire. Close your eyes and imagine being your favorite athlete or super star, say Michael Jordan or Taylor Swift.

How'd that go? Could you imagine having MJ's jump shot and spraying champagne after a championship win? Did you envision a glitzy outfit and blonde curls bouncing in your face while 'shaking it off' in front of 100,000+ screaming fans?

But notice something subtle: you didn't imagine and desire being MJ or T Swift. That wouldn't make much sense. They've already lived those experiences. What you imagined/desired was being you, in their body with their talents.

This tiny twist... this possibility to form such a desire, it shows how we don't identify as a body or mind, but rather, as something beyond... something that has a body/mind, and in principle, could have another one.

This is just one example of many showing how deeply the illusion runs. Its purpose isn’t to argue about the power of imagination, or to prove or disprove the existence of a self. It’s to just highlight how our ability to even form such desires—and to imagine a “me” swapping out bodies like outfits—suggests that, on some deep, automatic level, we believe ourselves to be 'a self'.

And this implicit belief doesn’t stop with imagination. It finds its most enduring home in religion.

Because if we can imagine inhabiting different bodies, it’s not a huge leap to imagine the self surviving the loss of this one altogether.

Across cultures and traditions, the belief in a soul—a self that outlives the body—has been the default setting for most of human history. Whether it travels to heaven, hell, or into another life entirely, the soul is often treated as the real “you,” somehow untouchable by death.

Ancient traditions like Hinduism call in an Ātman — an eternal, unchanging self identical to the divine. This Atman survives bodily death and is central to the cycle of rebirth.

Islam calls it Ruh and Nas. Ruh being the "divine spirit breathed into humans by god". Nas being the sef or ego, portrayed as "the sea of base desires that must be purified".

Christianity evolved this into the immortal soul — the true “you,” distinct from the body, judged by God after death.

So whether through cultural inheritance or cognitive instinct, we tend to experience ourselves as selves. We are wired to believe in a self the same way we are wired to fall for the Müller-Lyer illusion:

Even when we know the lines are equal, they still look unequal.

So, if we hope to see the lines as they are... it helps to ask:

Did we arrive at the idea of the self or soul through a first-principles investigation of reality?

Or did we invent it—because it was socially and emotionally useful? A mere patch to manage fear, morality, mortality?

Also, if this ‘feeling’ of self is just an evolutionary survival strategy, what role does it play in our future? How can this newfound awareness support our next evolutionary leap?

We'll answer all these questions and more in Part II. But if you want to jump ahead, by all means! See this link here → Part II | Future-Proofing Your Self

This feels like history in the making. And if you're a spatial computing enthusiast (AR/VR/XR) , it also feels like hope…

In case you haven't heard the news: OpenAI just acquired Jony Ives AI hardware startup, ‘io’ for $6.5B+.

The internet is now a buzz with speculation. Everyone is asking the same question — what exactly are they going to build?

My bet?

OpenAI is going to (eventually) build category defining AR glasses.

And in pairing with Jony Ive, they're not just trying to compete… they're trying to change the world.

This could yield the "iPhone moment" for AR that many of us have been waiting for, but with the AI-first twist this form factor can't live without.

The thesis is clear: AI needs a better way to understand and interact with our world, to break free from the confines of the 2D screen. It needs eyes, it needs context, and it needs to be with us, not just on a device.

And while that exact nature of that device remains shrouded in mystery, one thing is certain: when you fuse the world’s most potent AI brain with the planet’s most revered design sensibility, you’re not aiming to create a slightly more elegant chatbot interface or a me-too hardware product (e.g. speakers, earbuds, phone, etc).

You’re aiming for a revolution.

What could be more worthy of such a leap?

AR glasses will be a full circle evolution in human computer interaction, surfacing information in the way our brains have evolved to interpret the world. They’ll also bring our eyes back up to the world and to each other.

Imagine… a ‘generative UI’ that doesn’t just overlay information, it injects your perceptual system with maximum agency; an AI that moves beyond mere information retrieval to become an intuitive guide, an amplifier of your own curiosity and creativity.

The ultimate result? Machines that conform to us, rather than us conforming to them (hunched over, distracted, restless, addicted).

This is the vision that’s kept me in the industry for all these years, despite all the ups and (mostly) downs.

The implications for how we learn, work, create, and connect are profound and hard to imagine, especially if you’ve never tried really, really good augmented reality. I’d reckon less than a thousand people have. On the entire planet.

As for our wider industry, this should be a wake up call. Apple, Meta, Google, the whole AR/VR/XR/Spatial Computing alphabet soup – it’s time to kick things into gear and up our game.

And if you’re just a passive observer…. get your popcorn out. Because the AR + AI race just got a whole lot more interesting.

Okay… Easy there cowboy

I know what you're thinking. Pump the brakes, Evan, you're way over your skis.

There's zero guarantee OpenAI will get into AR. In fact, Sam Altman just told the WSJ they aren't making glasses.

What we do know is that Sam has a prototype, and he’s told OpenA staff it’s “the coolest piece of technology that the world will have ever seen.”

So far, the rumor mill points to some sort of little puck-like speaker thing that you can put on your desk, in your pocket, around your neck, etc.

Something like this…

Call me crazy, but this (or anything remotely close) would be far from “the coolest technology we’ve ever seen”.

I’m not buying it. I stand by my thesis, and here's why.

(1) AR Patents: First, OpenAI has filed numerous patents for AR.

Sam’s also one sly cat, and one of the last people I’d want to face at the poker table… Do you really think he’s going to show all his cards?

I could end my case here but let's keep going.

(2) A family of connected devices: Both Sam and Ive said they're going to make a family of devices.

Jony Ive has also suggested he's on a mission to rid the world of screens. Most notably, during this interview with Patrick Collison at the Stripe conference. It's an incredible conversation and will give you an inside glimpse into his motives. You can hint feelings of remorse for what the screen/iPhone has done to the world, reducing out attention span, creating all new forms of addiction, inflaming our insecurities, the list goes on...

He then said in the announcement video,"people have an appetite for something new, which is a reflection on a sort of unease with where we currently are..."

Now, I completely agree with getting rid of screens. But are we really going to get rid of the visual elements of computing?

(3) Seeing is believing: We are visual, experiential creatures. We need to see it to believe it. We need to see the inside our AirBNB, to fully inspect our new car, and to watch (360) videos from our loved ones.

I just don't see a world in which Ive doesn’t embrace our visual nature, and doesn’t embrace the world as our new desktop background.

What are we gonna do insteead… carry a puck/little box with a projector, point it at a bevy of surfaces, and hopes it pans out?

Me thinks not...

4/ AR = Ultimate Fun & Delight: In that same video, Ive talks about his design thesis and the ethos that drives him.

He believes product design should be all about eliciting delight, and creating more pure joy and fun in the world....

Again, most people haven't seen what truly good AR looks. I have, and I cried.

It was from trying an actual demo of this experience below, which we built with Nike back in my days at (OG) Meta:

This experience is what drives me to this day, and I’m telling you… it was the pinnacle of delight (within the realms of creativity & productivity).

The Strategy

I could keep going with my speculations, but I'll stop there for now.

Equally as important to what they build, is the how & why... aka their strategy. After all, what they build won't matter if they can't compete.

So, given who they're up against (Apple, Google, Meta), you have to ask the question... is this even the right strategy? Or is it a distraction?

Because in many ways... they're putting themselves into a big tech quantum state of superposition, trying to be a bit like Apple, a bit like Google, and everything else in between.

On one hand, you could argue OpenAI needs to focus on supplanting Google, and take a similar tack: building the OS/software/killer app (e.g. search) and have their apps on every device, in every ecosystem, in order to maximize scale.

And when Sam founded the company, it indeed was in direct opposition to Google. his catalyzing thesis was that Google was poised to run away with the AI race, and someone needed to compete.

But on the other hand... competing head on with Google is terrifying, especially now (did you see the last Google I/O? Mind blowing). Red ocean blood baths abound.

Now Apple? A different story. They're limping out of the gates in the AI race. Heck, you could argue they're still at the starting line. Their effort to date has been nothing short of disastrous, mired in politics and bureaucracy (as this recent Bloomberg article confirms).

In tandem, the iPhone hasn't meaningfully changed in generations, the Apple Vision Pro is a public R&D project (which I fully endorse, for the record), and developers continue to sour on Apple's App Store philosophy and mechanics.

In other words… Apple has cracks in its armor. Google is getting its mojo back. So going after Apple actually makes sense. And since we're obviously living in a simulation, OpenAI now has who Steve Jobs called his 'spiritual partner', making the onslaught now all the more fun and dramatic.

Regardless, things just got much, much more interesting.

Call it speculation, call it wishful thinking, call it hopium: AR glasses are coming at some point.

It might not be the first device, in fact, considering the technical hurdles that remain for AR, it almost certainly won't. But I'm betting you my bottom dollar: its on the mind, its on the roadmap, and its coming.

As such, I'm updating our AR + AI Racecard with OpenAI and Google.

You'll find below my 'pillar-based' analysis below.

For a similar analysis on Meta & Apple, check out my last article: The AR + AI Race Non-finale

With that, get your popcorn ready. The outcomes are uncertain, but the drama is sure to be first rate.

Oh, and if you're so compelled, tell me your thoughts in the comments below!

Who do you think is going to win? Where are the gaps in my thinking?

The AR + AI Racecard

The Contenders

1. Apple: The incumbent king of premium hardware, software integration, and a fiercely (but increasingly less) loyal ecosystem.

2. Meta: The relentless metaverse visionary, betting big on social VR/AR and open ecosystem development

3. OpenAI-IO: The AI-native, design-led disruptor, poised to redefine AI-human interaction.

4. Google: The re-awakened giant of AI and information, with deep pockets, vast data, and significant (if sometimes fragmented) AR/AI initiatives (think Project Astra, ARCore, Lens, etc.).

We analyzed Apple & Meta in our last essay (pasted further below). So let’s now breakdown our new entrants across the same critical battlefronts:

Software: AI Agents Will Redefine the OS

OpenAI-IO

• Forget app grids and traditional UI/UX. If my hunch is right, OpenAI-IO isn’t just building AR glasses; they're crafting the native interface for AGI.

• This means an OS designed from scratch around AI agents and a truly generative UI. Think less about swiping and tapping, and more about natural language interaction, with the visual interface materializing contextually, precisely when and how you need it.

• Why browse for an app when an AI agent can anticipate your need or summon the exact information/tool in a visual whisper? This is the ultimate "clean slate" advantage – no iOS or Android legacy to protect, just a relentless pursuit of the most intuitive AI-human interface. The "OS" becomes the AI itself, orchestrating experiences

Google

• Google has been telegraphing its AI agent ambitions for years (think Assistant, Lens, and the recent Project Astra demo).

• Their XR software play will undoubtedly leverage this deep expertise. Expect an Android-derived (or perhaps a new, lightweight, AI-centric) OS where AI agents are first-class citizens, deeply integrated with Google’s vast knowledge graph and services (Maps, Search, Workspace).

• The challenge for Google? Making it feel like a cohesive, new paradigm, not just Android shoehorned into glasses, and navigating the innovator's dilemma of how this new OS interacts with their existing Android dominance. But an AI that can "see what you see" and proactively offer assistance through AR? That’s Google’s sweet spot.

Innovator’s Dilemma: Who’s Free to Disrupt?

OpenAI-IO:

• This is where OpenAI-IO shines. They have zero existing hardware cash cows to protect. No iPhone sales to cannibalize, no dominant mobile OS to tiptoe around.

• They can be ruthless in their pursuit of the optimal AI-first AR experience, even if it upends current computing paradigms.

• This freedom is a massive competitive advantage. Their only "legacy" is cutting-edge AI, and these AR glasses are being built to serve that master.

Google

• Google faces a more complex path. While not as hardware-centric as Apple, their Android ecosystem is vast, and their primary revenue driver is advertising, fueled by data from services like Search.

• How does a deeply personal, always-on AR device fit into this? Will they create a truly open spatial OS that might compete with Android partners, or a more controlled experience to safeguard their service ecosystem?

• Their history shows a willingness to experiment (and sometimes abandon), but a full-scale AR push will require navigating these internal tensions. How do you truly innovate when you are the current paradigm in so many ways?

AI: The Engine of Spatial Intelligence

OpenAI-IO:

• OpenAI isn't just using AI; they are defining the frontiers of AGI. Their AR glasses won't just have AI features; they will be an AI, an embodied intelligence.

• Expect foundational models running (perhaps with clever on-device/cloud hybrid approaches) that offer unparalleled reasoning, personalization, and generative capabilities directly within the user's perception. The world itself becomes the prompt.

Google

• Google’s strategy? Unmatched data, powerful models, pervasive AI

• Google's AI prowess is legendary, fueled by unimaginable datasets from Search, YouTube, Maps, etc., and world-class research from Google AI and DeepMind.

• Their strength lies in contextual understanding, information retrieval, and services like real-time translation or visual search (Lens). For Google XR, AI will be about delivering Google's information and services in a more ambient, spatially aware manner. The key will be harnessing this power into a cohesive, delightful user experience in AR without feeling intrusive.

Hardware: Design Ethos and Go-to-Market Approach

OpenAI-IO:

• With Jony Ive at the design helm, expect nothing less than exquisitely crafted hardware that prioritizes user experience, elegance, and perhaps a minimalist aesthetic.

• The focus will likely be on a premium, aspirational device where the technology feels almost invisible, seamlessly blending with the user.

• The challenge? Manufacturing at scale and hitting a price point that, while likely premium, doesn't relegate it to a Veblen good. But Ive's involvement practically guarantees the product will be desirable.

Google

• Google’s hardware play will be more open and partner-centric

• Google's hardware history with XR is... varied (RIP Daydream, ahem, Glass). They might not aim to be the sole, vertically integrated hardware provider like Apple or potentially OpenAI-IO.

• Instead, we might see them focus on creating a core AI-XR software platform and reference designs, empowering a broader ecosystem of hardware partners (think their Pixel strategy, but for AR, or their renewed partnership with Samsung).

• This approach accelerates reach but risks fragmentation and inconsistent user experiences. Their "secret sauce" will be the AI and services powering these diverse endpoints.

Founder Vision & Leadership:

OpenAI-IO:

• Sam Altman is driven by a singular, audacious goal: achieving AGI.

• Jony Ive is driven by an obsessive pursuit of perfect design and user experience.

• This combination is electric. Altman isn't playing for incremental gains; he’s playing for a paradigm shift. Ive ensures that shift is human-centric. This is conviction-driven leadership at its finest, focused on building something genuinely new.

Google

• Sundar Pichai has clearly stated that AI is the core of Google's future, infusing every product and service. Google XR will be a key expression of this.

• While perhaps not with the same singular, public-facing "bet-the-company" XR fervor as Zuck, the leadership commitment to AI as the enabler of new experiences is undeniable.

• The question is whether XR hardware itself becomes a top-tier strategic priority or remains primarily a vehicle for their AI services.

Philosophy: Open vs. Closed Systems

OpenAI-IO:

• This is an unknown. Will OpenAI opt for a more controlled experience, or will they finally live up to their name with a more ‘Open’ platform?

• Given the tight integration of AI and the Jony Ive design ethos, the initial hardware/software experience will likely be relatively controlled to ensure quality and coherence.

• However, OpenAI's broader strategy involves making its AI models available through APIs. We might see a future where the glasses are a premium conduit to an increasingly open AI platform, allowing developers to build "skills" or "agents" for the AR experience.

Google

• Google will likely continue the Android legacy – Openness with guardrails

• Google’s DNA is rooted in Android’s openness, which spurred massive ecosystem growth. They’ll likely aim for a similar model in XR to encourage developer adoption and hardware diversity.

• However, access to Google's core AI services and data will undoubtedly come with Google's terms, creating a "semi-open" environment.

• The challenge is fostering true innovation while maintaining the quality and integrity of the user experience tied to their services.

Developer Trust & Traction:

OpenAI-IO:

• If OpenAI-IO delivers on the promise of AR glasses as a direct interface to their cutting-edge AI models, developers will flock.

• The opportunity to create applications powered by AGI-level intelligence in a spatial context is a greenfield of immense proportions.

• Trust will be built on the power and accessibility of their AI tools and a clear value proposition for developers.

Google

• Google will be aiming to leveraging the existing Android Army, while principally rebuilding the XR Faith

• The existing Android developer base is massive. The key is providing them with compelling tools, consistent platform support (their XR efforts have been a bit start-stop), and clear monetization paths to translate their mobile success to spatial. Project Astra and advances in their AI services are powerful carrots.

Fashion & Culture

OpenAI-IO

• Jony Ive isn't just a designer; he's a cultural icon. His involvement alone lends AR a level of design credibility and "cool factor" it has struggled to achieve.

• If anyone can make face computers fashionable and desirable, it's Ive. This could significantly shift public perception.

Google

• Google certainly has tougher path here due to the cultural missteps of Google Glass (aka the Glass Hole legacy).

• They’ll need to lean heavily on sleek partner designs (if they go that route) or develop an incredibly compelling aesthetic internally, perhaps focusing on minimalist, almost invisible tech, to win hearts and minds from a fashion perspective. Their focus will likely be more on utility first, fashion second.

Product Iteration & Consumer Comfort

OpenAI-IO

• Ive is known for striving for a perfectly polished V1.

• OpenAI, however, comes from a research background where rapid iteration is key. Finding the balance will be crucial.

• The AI will evolve constantly, but the hardware will need to feel "right" from day one to gain consumer trust.

Google

• Google is comfortable launching products in beta and iterating publicly based on user feedback.

• This can lead to faster learning but also a perception of products being perpetually unfinished.

• For AR, where comfort and reliability are paramount, they'll need to ensure a high-quality baseline experience.

Distribution

• OpenAI-io

• Given the likely premium nature of an Ive-designed product and OpenAI's current standing, a direct-to-consumer model, perhaps with select high-end retail partnerships, seems probable for initial launch.

• Scaled distribution will be a new muscle for OpenAI to build.

Google

• If Google focuses on a platform/software approach with hardware partners, their distribution is instantly global through the existing Android device ecosystem and retail channels.

• If they launch their own "Pixel-for-AR" device, distribution will be more controlled but can leverage their existing hardware channels.

Product Portfolio: The Ecosystem Driving AR Use Cases

OpenAI-IO:

• OpenAI's "portfolio" is its suite of world-leading AI models.

• The AR glasses become the prime delivery mechanism for these models to provide value across countless applications – from hyper-intelligent assistants to creative tools to powerful analytical interfaces.

• The use cases will be defined by what their AI can do spatially.

Google

• Google's immense portfolio – Search, Maps, YouTube, Workspace, Assistant, Translate – provides an almost endless list of powerful services that can be integrated into an AR experience.

• The AR glasses become a new, more contextual way to access and interact with the Google ecosystem you already use.

Initial Readout (Not a final verdict, just a summary)

OpenAI-IO

• Poised to deliver massive disruption by redefining the experience of AR through an AI-first, design-led approach.

• Their path is to create something so compelling and intelligent it carves out a new premium category.

• Their biggest challenge: scaling hardware production and distribution from a (relative) standing start.

Google

• Has all the ingredients for a dominant AR play – AI, data, an existing OS footprint, and vast services.

• Their path is likely to make AR an ambient extension of the Google services ecosystem.

• Their biggest challenge: a historically fragmented XR hardware strategy and the innovator's dilemma of how AR fits with their existing Android dominance.

This sets the stage for a truly fascinating four-way race.

Each player brings unique strengths and philosophies to the table. The coming years won't just be about who builds the best device, but who crafts the most compelling, useful, and ultimately indispensable experience at the intersection of AI and our perceived reality.

If you’d like to dive into a similar analysis on Meta and Apple, check out my last article here: The AR + AI Race Non-finale.

The AR + AI landscape has since shifted dramatically, rendering this essay series obsolete, at least in its original spirit & form. It was going to be a four-part series, predicting the outcomes of the race between Apple and Meta. It took you on a meandering journey up and down the tech stack, analyzing their strength & weaknesses at each layer; from hardware, to software, to AI. It also accounted for leadership, culture, and business philosophy.

Here is Part I and Part II if you’re curious. Each received a solid response from the community and I was eager to crank out the rest… but then a variety of things happened:

1/ Google pulled a Michael Jordan, rocking #45 and bursting back on to the XR scene with AndroidXR and an acquisition of HTC’s XR engineering team. Leaving Google out of the equation suddenly felt silly (although some would argue they never left).

2/ Apple apparently cancelled their AR glasses project (per this Bloomberg report).

Then they apparently didn’t (per a variety of articles like this).

And then I realized who the hell knows. Apple is more secretive than the CIA and any predictions involving their most veiled ambitions are rife with speculation.

My stance: any AR-pessimism from such speculation is overblown and far from indicative of Apple’s plans. There’s plenty of evidence that AR/spatial remains central to Apple’s long term strategy.

3/ Next, I (conveniently) decided predictions between just Apple & Meta would be a disservice to the industry. Niantic is certainly in the race, Snap could carve out a piece of the pie (especially amidst GenZ/GenX), Microsoft has plenty of IP and software/cloud opportunities, and the list goes on.

It’s also a misrepresentation of what spatial computing truly is (far more than just AR glasses).

See this rant to grasp what I mean.

4/ And then… the real hammer came down. OpenAI, Perplexity, and Grok all came out with their ‘deep research’ GenAI products.

These tools spit out a comparable research/analysis report within minutes. The level of depth and the predictions blew me away. They were spot on, and like most writers in the world today, I fell into a state of existential despair.

This then forced a deep inquiry… What is the point of this newsletter? Do I really want to compete head-to-head with AI? Or with all the people who are going to just copy/paste ‘deep research’ outputs and claim them as their own?

We’re about to experience a deluge of content like this; re-mixes of information that already exists across the internet (from S-1 filings, other newsletters, media outlets, etc).

I then came to my senses, which included a sense of relief; I was thankful for a (real) excuse to not finish this series.

I don’t want to write industry analysis or report the news. You also have a thousand options for this type of content. Perplexity or ChatGPT can spit out the latest/greatest within a blink, turning research and analysis into a commodity.

No, I started this newsletter because I wanted to move up the value chain; I wanted to stoke your imagination, collectively future cast, and create more optimism about the future.

Ultimately, I wanted to inspire and reveal how these new tools can make us more human not less; by increasing our capacity to feel, connect, and find meaning/purpose.

And so, I’m officially deciding to zig where most of the content world zags; classic blue ocean type of stuff (see Blue Ocean Strategy).

The precise aesthetic of these zigs will be emergent. But safe to say, it’ll include science fiction mixed with some education, opinion pieces, and philosophical musings.

This essay is the best corollary. 2042: A day in a metaverse life.

It bounces between a sci-fi ‘day in the life’ narrative and present-day explanations of the tech. And while the term metaverse has since become cringe, I do still believe in these core ideas, i.e. the power of a more experiential, contextual, collaborative, and intelligent internet. And the promise of digital ownership, internet-native value, and digital capital formation,

That essay was the most fun I’ve had writing since starting Medium Energy. It also received some of the most moving feedback.

And so, as David Deutsch likes to suggest, we’re going to follow the fun; one of the most uniquely human things we can do/feel.

Let the machines ‘think’ and process ‘tasks’. Let us ‘feel’ and process ‘experience’.

I explored this idea at length in this shorter essay: “Finding Solace in the Age of AI”.

In the spirit of letting AI do tasks, here’s a ChatGPT summary of the core thesis:

In "Finding Solace in the Age of AI," Evan Helda reflects on the rapid advancements in artificial intelligence and their implications for human creativity and self-awareness. Drawing inspiration from a 1974 interview with author Ray Bradbury, Helda emphasizes the importance of feeling over thinking in the creative process. Bradbury suggests that overthinking can stifle creativity, advocating for a more intuitive and emotion-driven approach to creation. Helda extends this idea to the modern context, proposing that as AI takes over more analytical and data-driven tasks, humans should focus on nurturing their unique capacity for emotion, intuition, and personal truth. By doing so, we can find our distinct place alongside intelligent machines, leveraging our innate abilities that AI cannot replicate

Couldn’t have said it better myself (ironically enough…)

This was in early 2023. AI for writing has gotten much better since. What was already a painfully daunting craft has become entirely overwhelming, for an entirely different reason. My most sinister inner voice calls it futile.

If AI can produce essays, news articles, and poetic prose at the push of a button, then what does it mean to be a writer? What is left over for the human creator?

These questions have been writhing within the pit of my despair. But I’ve since come to realize… This discomfort—this feeling of being outmatched by an infinite, tireless machine—is also an opportunity for clarity. It forces a deeper reckoning: Why does writing (or any creative effort) matter? What makes it worth doing?

I think the answer starts here: as AI erodes the scarcity of these skills, value accrues in the scarcity of meaning, intent, and originality.

In other words… AI's presence forces writers, artists, and creators to find the essence of why their work matters. It raises the bar.

Towards that end, and to help save me from myself, I’ve created some ‘writing tenets’ to guide this content going forward.

Perhaps you’ll find them useful as well.

The Medium Energy Tenets

1. Writing as an expression of lived experience

• AI cannot have a personal history, unique struggles, or firsthand perspective.

• Readers don’t just want facts—they want stories, insight, and vulnerability.

• The question becomes: What can only I say?

Example: An AI could write about "the experience of loss," but it cannot recreate the specificity of your grief—the little details, the precise way it changed you. It cannot tell a story about how it felt in your body, how it changed your relationships, how you made sense of it.

2. Writing as provocation, not just information

• AI excels at answering questions but struggles to ask the right ones.

• The best writing doesn’t just provide information—it challenges, provokes, and invites participation.

• AI may summarize Nietzsche, but it will not wrestle with a philosophical contradiction in real-time, questioning itself, evolving its stance mid-sentence.

Example: Imagine an AI writing about the impact of AI itself—it can aggregate knowledge, but can it wrestle with the existential anxiety of being replaced? Can it capture the precise feeling of watching technology erode the thing you thought made you unique?

3. Writing as a transmission of human connection/empathy

• People don’t just read for knowledge; they read for communion with another mind.

• The most compelling writers make you feel like you're seeing the world through their eyes.

• A great book or essay is not just a collection of words—it’s a portal into someone else’s interior world.

Example: When you read Ayn Rand, you don’t just absorb facts about 1950’s-60s America—you feel her presence, her worldview, her frustration, and her hope for a better future. AI can imitate her tone, but not her being.

These tenets aren’t just for writing—they’re for anyone creating in a world where AI is rapidly automating skills and commoditizing cognitive inputs.

In music: If AI can generate endless symphonies, what makes music valuable? Live performance, artistic intent, and cultural movement.

In entrepreneurship: If AI can automate a business, what makes a company thrive? Brand, human relationships, authentic mission.

In art: If AI can paint in any style, what makes an artist matter? Perspective, rebellion, emotional urgency.

The common thread: What AI commoditizes, humans must transcend.

In conclusion: this shift is not a death sentence for creativity. It is a purification. AI eliminates the predictable, the formulaic, the interchangeable. What remains is what was always worth doing: the work that only humans, with our contradictions, desires, and histories, can produce. AI does not make writing or music or business meaningless—it raises the bar for what is meaningful.

With all that said, I feel obligated to give at least some ‘finality’ to this non-finale on the AR + AI Race.

So, here’s an easy way to consume the key ideas & opinions from my jumble of rough drafts.

In the spirit of feeling & fun, these are the takes that elicit the most emotional responses in my daily convos. These will also be fun to look back on in 5-7 years and see how things played out.

If any of these strike a chord with you too… good! Let's hear your objections or thoughts in the comments below.

Thanks for taking the time, and see you on the other side.

The AR + AI Race | Summary of Predictions

Bottom Line Up Front: If I had to pick a winner right now, from a scale and adoption perspective… my money is on Meta.

Why Meta Has the Edge

Software: AI Agents Will Redefine the OS

• Apple thrived in the mobile era with direct human interaction (app UI/UX, touchscreens). But that’s not the world we’re heading towards.

• We’re heading towards a world of AI agents. How much will that old iOS UI/UX matter? Do I really need to swipe & search for apps, answers, and data?

• Or… can I just summon it, and get bits and pieces of visual cues if/when needed? Better yet, what if the UI changed in real-time based upon my use case and context (where I am, who I’m with, what I’m doing)? Aka a ‘generative UI’; one that could turn the world into my desktop background and display information all around.

• Point being… AI agents have leveled the OS playing field. The OS and mobile app paradigm needs to be redesigned from first principles.

• Meta has no legacy OS baggage and can build AI-native UX from scratch. Traditional software moats (UX/UI) are eroding—data and AI models now define competitive advantage.

• Meta’s social data dominance (Instagram, WhatsApp) provides AI with unparalleled context for AR applications. Apple’s privacy-first approach may appeal to high-end users, but Meta’s ability to personalize experiences at scale will likely win the mass market.

Innovator’s Dilemma: Apple is Handcuffed by iPhone Success

• Apple’s entire business is built on iPhone + App Store revenues.

• Success in AR, or with ‘generative UI’ could cannibalize its core products, making them hesitant to disrupt their own cash cow (e.g. trying to use the iPhone to power glasses creates subpar tradeoffs & risks)

• Meta, with no mobile OS baggage, is free to rethink spatial computing from first principles.

AI: Meta’s Unmatched Scale and Infrastructure

• Meta is building the largest AI infrastructure of any consumer tech company:

  • 600K GPUs by the end of 2024, powering Llama 3 and other cutting-edge models.

  • Meta’s GenAI tools (video editing, 3D reconstruction, Hyperscape) push AI beyond text/image generation into AR/VR environments.

  • AI-first products like Meta Ray-Bans provide real-world training data for AI assistants.

• Apple, by contrast, focuses on privacy-preserving AI via on-device models—good for security but limits scalability and AI’s real-world utility.

Hardware: Meta’s Multi-Tiered Approach vs. Apple’s High-End Strategy

• Meta is playing a long game, starting with the low-cost Meta Ray-Bans, then bridging to full AR glasses.

• Apple’s Vision Pro is premium ($3,500) and closed—limiting adoption.

• Meta’s hardware strategy is modular, with Quest, Orion (AR glasses), and Ray-Ban Smart Glasses feeding into a broader ecosystem.

• Apple’s integration strength (hardware + software) is legendary, but their hesitancy to release until "perfect" may slow their AR adoption curve.

Founder Vision & Leadership:

• Mark Zuckerberg is leading from the front, making high-risk, long-term bets on AI and AR. He’s just feeling himself, in full on Super Saiyan mode (if you know, you know).

• This is in contrast to Apple’s Tim Cook. While Tim is playing it safe and optimizing existing product categories, Zuck is sprinting towards an entirely new computing paradigm—driven by personal conviction rather than short-term financial pressure.

Philosophy: Open vs. Closed Systems

• Meta embraces openness, iterating in public with regular R&D updates, while Apple’s secrecy limits developer inspiration & engagement.

• AR is too nascent to be locked down—developer feedback and rapid iteration will dictate success.

• On the more technical front, open platforms (PC, Android) have historically enabled faster ecosystem growth vs. closed systems (Mac, iOS).

Developer Trust & Traction

• Meta’s open philosophy and more horizontal platform approach will earn more developer trust & enthusiasm.

• Meta already has a head start here. They’ve been cultivating an AR/VR developer ecosystem for years with Quest devices, while Apple’s restrictive ecosystem is frustrating devs, not to mention a lack of community/dev ecosystem investment.

• Quest’s accessibility (lower price, open tools) means developers can experiment freely—Apple’s Vision Pro is a walled-garden premium product with limited sensor access.

• A thriving developer community = more innovative applications, which is critical for AR’s to find product/market fit in the early days.

Fashion & Culture: Ray-Ban > Apple in the Glasses Market

• Apple is a world-class design company, but Luxottica (Ray-Ban’s parent) owns the eyewear industry—from brand cachet to global retail distribution (18K+ stores vs. Apple’s 520).

• Meta’s partnership with Ray-Ban positions them as the "cool" AR player from Day 1, while Apple struggles with making AR glasses fashionable.

Product Iteration & Consumer Comfort

• Meta is learning in real-time with Ray-Ban Smart Glasses, refining AI + AR interactions in a natural form factor.

• Early exposure builds consumer trust—Apple, by contrast, risks waiting too long and launching a product that feels unfamiliar.

• Privacy concerns won’t be a major differentiator—most consumers prefer better experiences over strict data protection.

Distribution

• Meta’s Luxocitta/RayBan partnership is underrated from a distribution perspective.

• They have over 18,000 stores globally and one of the most recognizable brands in the game.

• Apple has 520 stores. This does attract the higher/more premium end of the demographic spectrum, but I see a world where Meta, with a cheaper and more accessible product, introduces more people to AR glasses, and sooner.

Product Portfolio: Meta’s AI & Social Ecosystem Will Drive AR Use Cases

• Meta controls the most engaging social networks (Instagram, Facebook, WhatsApp)—perfect for AR-driven communication and content.

• AI + AR will thrive on personalized, real-time contextual awareness, and Meta’s unmatched social data enables next-gen AI-powered AR assistants.

• Apple has strong AI privacy protections, but lacks the scale of Meta’s training data and ‘social distribution’ channels.

Final Verdict: Meta is better positioned to win (for now…) Key reasons being:

• Founder vision (Zuck is all-in, while Cook optimizes existing products).

• Philosophy (open & iterative beats closed & secretive in early markets).

• Developer trust (Meta is enabling experimentation, Apple is limiting it).

• AI at scale (Meta’s AI-first approach will define AR interactions).

• Hardware accessibility (Meta is making AR more affordable and consumer-friendly).

Apple is not out of it by any stretch. This race is JUST beginning. There also can (and likely will) be two winners—just like iOS vs. Android. But in terms of scale and adoption, the odds are currently in Meta’s favor.

Before you scoff, hear me out.

There’s certainly a long list of other wildly exciting frontiers—semiconductors, nuclear power, biology/chemistry, crypto, quantum computing (to name a few); all things that will also ride the AI tidal wave, create immense value, and transform society.

But how many of them will be directly experienced by the average person? On a daily basis and global scale?

How many of them will impact the things that make us most human, such as consuming and making sense of information? Communicating and connecting with others? Telling stories and transferring knowledge?

Sure, these other breakthroughs will play a role. But they’re ‘behind the curtain’ innovations, multiple layers removed from most consumers.

As for Spatial + AI?

This is a direct shift in human-machine interaction, something all of us do, all day every day.

It’s also a direct shift in experience (of both the digital and physical world), and in turn, an evolution of human behavior and culture.

Does it get much more fundamental than that?

The cherry on top is how spatial will accelerate AI. This merger will move machines from probabilistic guessers of the next letter/pixel (Large Language Models, aka LLMs), to machines with a complete understanding of our world (Large World Models, aka LWMs).

The result is ‘spatial intelligence’, i.e. machines that can model the world and reason about objects, places, and interactions in 3D space and time.

The ultimate result?

True AGI.

With that backdrop, we’re here to ask ourselves… who will be the winners in the Spatial + AI race?

Here in Part II, we’re exploring the main character of this drama — AR glasses — and the two clear market leaders — Apple and Meta.

I know, I know. There are numerous other companies in hot pursuit of this vision.

Google, Snap, Niantic, to name a few, along with a flurry of Chinese players. But as of today, Apple and Meta are the ‘Vegas favorites’, with the most public facing progress and the most apparent strategies. They’re also the closest to home (for most).

(Although, if you’re playing attention, you’ll know Google is a meandering juggernaut. See this Project Astra video. Also see Google Maps + 3D, AR Core + Spatial Anchors, Waymo Open Dataset Challenge. All things worthy of a future essay)

If you haven’t read Part I, check it out here. It covers the impact of Meta’s big reveal, Orion: the first AR glasses we’ve seen worthy of main stream adoption.

This created a wave of enthusiasm and hope across a weary ecosystem. It also sparked a new era of very real, very intense competition. The most intense being between Apple and Meta.

The rest of this series will break down this showdown and predict a winner. We’ll do so via a variety of vignettes. Each one will analyze advantages on critical battle fronts, spanning hardware, software, AI, content, developers, distribution, leadership, and philosophy.

This will also give us a blue print for analyzing future players to come, and for analyzing the industry writ large.

With that, let’s get into Part II, starting with hardware.

AR Hardware

The natural instinct is to give Apple the clear edge here.

From design mastery to economies of scale, Apple dominates in creating sleek, mass-market devices. It’s easy to assume this advantage translates seamlessly into AR.

But I’m not so sure this edge will hold…

Yes, Apple’s hardware expertise is legendary, built on decades of refining mass production through vertically integrated supply chains.

They also excel in key areas like displays, chips, and battery life—critical components of AR devices.

Most importantly, their ability to produce at scale drives down costs, and as Meta readily admits, Orion is far too expensive today. It would cost upwards of $10,000 per unit to produce. And while Apple almost certainly has a similar prototype in a lab, bringing that price down without significant technological compromises is going to be a massive challenge.

The best shot at doing so will be serious economies of scale; something Apple does in its sleep, at levels Meta hasn’t even sniffed.

Regardless, I think it’s a mistake to discount Meta’s hardware progress and trajectory.

Their Ray-Ban glasses, built in partnership with Luxottica, are affordable, well-designed, and gaining meaningful traction. Everyone I know who owns them loves them, including myself.

They’ve also shipped millions of Quest VR/MR headsets, giving them valuable experience in developing out the right supply chain and refining hardware for mass-market adoption. Even the now-defunct Meta Portal (RIP) taught them hard lessons about manufacturing and consumer preferences.

And let’s not forget the looming, great equalizer: AI + robotics.

Meta’s manufacturing prowess will be further accelerated by advances in robotics, AI-driven design, and simulation technologies. Armed with these innovaitons, they’re poised to pull of something similar to Tesla.

In less than a decade, Tesla went from an underdog with little manufacturing experience to leading the industry, leapfrogging traditional automakers in areas like battery efficiency and production scalability, mostly powered by automation & robotics; the great equalizers.

I predict a similar journey for Meta with AR hardware, propelled by their willingness to innovate and a lack of inertia from legacy operations & products.

But this game doesn’t reside with the AR glasses alone… The other critical dimension is a device for offloaded compute.

Meta’s Orion comes with a small puck for running heavy workloads that impact battery life, heat, weight, etc. Most experts agree this will be the standard for consumer AR.

In which case… Apple should have the edge here as well.

The iPhone (and/or Macbooks) could become the de facto "edge computer" for AR, handling heavy workloads for rendering, positional tracking, room mapping, and object recognition.

This is where Apple’s custom silicon will also be a major advantage—year after year, their chips outpace competitors in power and efficiency, making the iPhone a natural candidate for this role.

But here’s where things get tricky: the iPhone is Apple’s crown jewel, its most profitable product, and the backbone of its ecosystem.

Repurposing the iPhone for high-performance AR workloads would require significant changes to its design, battery life, and heat management—potentially undermining its appeal as a general-purpose device.

This is a classic innovator’s dilemma: will Apple risk its cash cow for a future that is still speculative?

History suggests otherwise. Think of Kodak, which clung to film cameras while digital photography surged ahead, or Intel, which delayed its move into mobile chips and GPUs, allowing competitors like ARM and NVIDIA to dominate.

Apple could hedge this risk by introducing a specialized "iPhone Pro++," catering to AR enthusiasts while preserving its core smartphone market. But even then, they would need to confront operational trade-offs and internal politics to execute this strategy effectively.

Meta, by contrast, faces no such legacy constraints. They can innovate with the offloaded compute model without worrying about cannibalizing an existing product line. Their relative freedom to experiment positions them well to iterate quickly and find solutions that work for consumers, unencumbered by the bureaucratic inertia that often hampers established players.

There’s one last variable that is underdiscussed. We’ll tease it out with a question…

Is this really an AR glasses battle? Or… is it a ‘wearable computing’ battle?

Despite my/our industries bias for AR glasses… It’s hard to see glasses being a general purpose computer (similar to the smart phone today).

It’s likely going to be a companion device, in a world of many companions: your watch, your ear buds, your phone, and for some, a chip (in your brain, as we explored in this podcast episode).

This next paradigm isn’t about one or two screens sharing a common operating system and common interface. The touch/cursor interface is dissolving and becoming dynamic. It will be a mixture of audio, light visuals, heavy visuals, all controlled by a variety of inputs: gestures, voice, eyes, and yes… even thought.

In this world, the winner will be the company that can stitch all these things together into a seamless experience, such that they all work in harmony, with a level of contextual awareness. This is the idea of ‘ambient computing’.

Meta has some amazing IP here with their wrist device that can read EMG signals. This allows you to control an interface by just thinking about a gesture. Meta could certainly make this a smart watch, either homegrown or via partners. The partner route is the most likely, rinsing & repeating the Luxottica/Ray Bans success.

But its hard to argue against Apple’s strength here: iWatch, iPhone, Air Pods, etc… the fusion of Apple’s hardware ecosystem will be very hard to beat. Although not impossible…

If Meta can build a compelling ‘spatial/ambient’ operating system, and then deploy it in a similar fashion to Android…. then ecosystem innovation abound.

This just might be the winning strategy: let the companies who excel at wearables duke it out on top of your software platform. This would allow Meta to effectively crowdsource their wearables ecosystem. May the best brand/team win.

The critical risk here is quality control (at which point, an acquisition could bridge the gap).

Final Prediction

The hardware race will be much closer than people think, but it’d be overly speculative to give Meta the advantage here.

Apple is *the* hardware company of our generation. And I think their ability to make numerous devices work/sing in harmony is going to yield the ultimate user experience. This, combined with innovations at the chip layer, give Apple the edge.

That said… don’t get too distracted by the hardware battle. This won’t be where the war is won or lost.

The UI/UX will come down to software, and ultimately, AI… which is where we’ll be going next in Part III.

Subscribe below and stay tuned!

What are the implications? Why did Meta show its cards? Who is going to win? Most importantly, will anyone even care?

Meta revealed Orion at Meta Connect, their last developer conference in September.

It was a provocative big tech flex, a proper 'I told ya so' to the Wall Street haters, and a bold warning shot over Apple's bow.

Real bold.

It was also the first time the world has ever seen AR glasses worthy of mainstream adoption (and worthy of our sci-fi imaginations). What was deemed impossible with today’s tech was proven possible, moving consumer-grade AR from sci-fi to sci-fact.

And now… the (real) spatial computing race is on. Everything up until now was a warm up (yes, including the Vision Pro).

With the dust settled, here are my unfiltered thoughts and predictions from the spatial computing front lines.

In Part I, we’ll hit the three major implications: market timing, ecosystem acceleration, and the emergence of AR’s budding romance with AI.

This sets the stage for Part II, where we’ll predict a winner by analyzing the 7 key battlefronts: hardware, software, distribution, AI, developers, philosophy, and leadership.

As for Part III? TBD. I’ll probably make this an ongoing series, checking in along the way to see where I was right, wrong, and/or entirely delusional.

Regardless, two things are certain.

First, this is going to be one of the most fascinating tech battles of our time, with the potential to not just transform, but also heal our relationship with technology.  

Second, after 8 years in this space, I can finally say with confidence: the time to build is now.

Here’s why…

Timing

For the first time in history, we have a timeline for consumer-grade glasses.

What’s consumer grade? It’s a goldilocks zone between numerous variables; the combo of which is the spatial computing equivalent of Elon landing a rocket back on earth.

 With out getting too technical, here are the (oversimplified) big ones:

• You can actually see the real world: it’s not pass through mixed reality like the VisionPro, in which the world is displayed through a screen (aka MR). The display is embedded into lenses, allowing you to see the real world and make real eye contact).

• It’s not too heavy: Industry consensus is that AR glasses need to be under 100 grams. Orion snuck just under at 98. For comparison, VisionPro is around 600 grams, and Snap’s new AR glasses are 226 grams…

• The field of view isn’t tiny or obstructed: Orion has a 70-degree field of view. That probably means nothing to you, but without getting too technical, just trust me: it’s a very big deal, and very impressive with this smaller form factor.

• They don’t look ridiculous: they look/feel like a pair of glasses you’d wear in public without a sense of insecurity. They’re relatively sleek, with a hint of style (why Meta’s RayBans/Luxocitta partnership is underrated).

• A reasonable battery life: you don’t have to recharge every 2 hours

• The input is natural: you can use your hands & eyes to more naturally and intuitively interact with the content (requiring all kinds of advanced sensors and computer vision software). No hand waving, no controllers, no external tracking systems.

I haven’t tried the glasses myself yet, but in talking to people who have, all the boxes above have been checked, except for one: battery life.

I’ll take it. Of all the technical challenges to address, this one is the most manageable, requiring the least amount of invention.

Pre Orion, most experts thought this goldilocks zone was numerous technical breakthroughs away, needing new science and inventions across displays, batteries, cooling, etc. Many experts thought it could be 10+ years, others said 20, some wondered if it would ever happen at all. I was in the 8-10 year camp. But who am I kidding: that was pure hope. The horizon stretched as far as the eye could see, and I must admit, my faith was wavering

Post Orion, my faith has been restored. Land ahoy! You might have to squint, but its there, and unlike VR, this market won’t be niche…

VR is a ‘destination technology’. You have to set aside time to disconnect and go ‘elsewhere’. And if the VisionPro taught me anything, it’s this: it doesn’t matter how incredible the experience is, most people just don’t want to get fully immersed.

AR glasses, on the other hand, are an ‘always on’ technology, and at a minimum, the ultimate smart phone complement; paradoxically allowing technology to fade away into the background.

If done right, it will bring our eyes back up to the world and to each other, while conforming to how we already operate and exist in a 3D/spatial world, not the other way around (i.e. staring down into a screen, doom scrolling, pitter pattering with our thumbs).

I know what you’re thinking… let’s not count our golden geese; it's still TBD when Orion can be productized and manufactured at scale.

True, but that’s not the point. The point is we now know the tech exists, and we’ll be getting the iPhone 1 of AR within the next 5 years.

The implications? Historical investments in 3D/XR will be fortified, future investments are going to accelerate, and the ecosystem is going to get a second (third?) lease on life.

Ecosystem Acceleration

We’ve felt this acceleration/hype before, but it lacked a critical tail wind: real competition.

Meta has forced Apple’s hand, and now, the gloves are off between two of the most formidable companies of all time.  

Meta’s also forced the hand of its employees. An internal fire has been lit and the pressure is on to ship. No more hiding behind the R&D veil.

We all know what this means: better products, better developer programs, better marketing, better sales motions, and increased investment writ large. Most importantly, a roadmap with incentive to build.

At last, the spatial money train is a comin’, and not just into R&D.

Some might say this effect already happened with the Apple Vision Pro (AVP). But I’d disagree.

First, as mentioned, the AVP is not real AR, and while technically superior to the Meta Quest 3 on almost every dimension, it’s not a ‘market creating’ product. It’s a ‘me too’ product in a niche category.

Second, the AVP was great marketing and a huge credibility boost for our industry. But, despite my overall Vision Pro bullishness, I have to admit: the excitement and momentum fizzled almost as quickly as it began, including my own.

Even Apple’s follow through felt half-ass, from the content, to developer enablement, to enterprise go-to-market. Sure, they’re doing these things in spurts, but these motions don’t have the gusto you’d expect from a company like Apple.

In Apple’s defense, I don’t think they’ve fumbled and lost their mojo. It’s likely calculated. As I stated in this essay, ‘The Fate of the Vision Pro’, the AVP is a ‘get-in-the-game’ strategy; a mere dipping of the toe and a mechanism for learning and inspiration (for both Apple and their customer). The AVP is the Lisa to their future Macintosh: more art & marketing than product.

I think this was the right approach, but also ironic, as the Vision Pro might have benefited Meta more than Apple.

Zuck is bringing his Jiu Jitsu skills into the corporate realm, and using the AVP hype to his advantage.

How? By throwing a more practical and established sail into the AVP tailwind, kicking off a potential leapfrog effect. That sail being a cheaper yet comparable device (Quest 3), a broader dev ecosystem, better developer economics, product market fit with the RayBans + AI form factor, existing enterprise penetration, etc.

We’ll dive deeper into their strategy in Part II. For now, the main point is this: the big tech equivalent of Godzilla vs. Kong is underway, and we all get to benefit as a result.

AI + AR

And finally, the biggest reason to start building now: the romance between AR and AI; a classic case of “you complete me”. Because without AI, AR just can’t become the best version of itself.

Why? Because if you’re going to ask people to put a computer on their face, there has to be a really, really good reason.

In the enterprise, those reasons are aplenty. But for your average consumer? It will have to yield something 10x more magical, useful, and compelling than the rectangle in their pocket.

Fortunately, AI will do exactly that.

The power of GenAI is mind numbing. But when I use it, I can’t help but think: this simple text box UI is f’ing limiting, especially for consuming GenAI’s outputs.

To be sure, the sentences, the images, the videos; they’re a mesmerizing portal into our sci-fi future. But as I stare deep into it, I find myself yearning for deeper access to the abyss of knowledge bubbling, frothing, and heaving behind the 2D veil.

AI is capable of showing us so much more, across so many dimensions, with so many different mediums. And it’s capable of doing so in a more intelligent way, a more… generative way, with just the right amount of information, in the right place, at the right time.

This is the idea of a generative UI, one that adapts to what we’re doing, where we are, who we’re with, and what we’re seeking to understand. It’s the right UI for the task at hand. It’s also the right UI for AR glasses.

All of this becomes possible in the age we’re now entering: the age of ‘agentic’ applications; apps in which AI agents work in concert to do things on your behalf (i.e. no more swiping, tapping, and scrolling to get shit done. Things just get done for you via basic commands and contextual awareness).

Why get lost into a screen and a medley of app icons, lists, and buttons… when with a quick verbal prompt, I can cut straight to the core information I need for the task at hand, see some visuals or a list of final recommendations, and be on my marry way?

Or… based upon additional context cues and semantic awareness, AI agents are anticipating and showing me exactly what I need before I even know it?

This marks a notable shift in the software-hardware relationship, moving it from a push effect to more of a pull.

Meaning… for decades, we’ve crammed software into boxes based upon the limits of chips, displays, memory, etc.  These constraints have led to human-computer interactions that, while powerful, often require a steep learning curve to extract maximum value from the machine (e.g. having full agency in the digital realm; writing code, creating content, analyzing data, being productive… not just watching TikTok).

Now, innovation at the software layer is creating a pull effect at the hardware layer, demanding something entirely new. We have software approaching our equal, worthy of eyes, ears, mobility, and semantic understanding. Worthy of perhaps the greatest human ability at all; storytelling.

Storytelling in context, at its fullest capacity (with visuals, simulations, data, etc), and in all its forms; for knowledge transfer, for inspiration, for empathy, for meaning, for preserving the past, for imagining a better future.

I don’t think we’re even close to wrapping our heads around what this means… especially for the moment when AI comes to know us better than we know ourselves, both mentally and physically. This is coming via the combo of biometric sensors + AI, and in the not-too-distant future, brain computer interfaces + AI + AR, aka the complete merging of man and machine, aka the singularity moment.

While it’s hard to believe, most of us will see this within our lifetime. Don’t believe me? Check out this recent podcast episode with the CEO of uCat, Sam Hosovsky: who’s building ‘mind controlled avatars’ and various missing ingredients up and down the tech stack. Here’s a sneak peek.

But I digress, this is an entirely different topic for a future essay.

Conclusion

Coming back to the present, the immediate ‘so what’ is this: startups and developers are re-energized, enterprise customers are doubling down, and investor confidence is on the mend; largely because the right destination is in sight.

This effect is most tangible in the enterprise: the first and most important battle ground, as this is where most consumers will have their first really good experience with AR (just like in the phase between mainframes and personal computers).

While enterprise AR/VR has struggled to achieve meaningful scale, the savvy executives didn’t throw in the towel.

They realized AR/VR headsets were just one end-point of many, and that interactive 3D can be impactful with traditional interfaces: browsers, tablets, laptops, etc.

One of my customers has a very succinct way of explaining why: 3D just provides a more visual way of working. It gives users a better understanding of complex things and maximizes the bandwidth of communication between experts and laymen. The net result is better/faster decision making, which is creating real business impact, and in some scenarios, saving lives (e.g. training in high-risk environments or quality control when building/planning dangerous facilities).

And this is just the ‘human in the loop’ benefit… These customers are also realizing that real-time 3D is a massive unlock for training AI to understand, simulate, and navigate the real world (e.g. teaching robots to navigate a factory, using to AI optimize numerous assembly line configurations).

These steadfast execs are now gaining internal credibility and unlocking investments in foundational 3D content platforms, complete with the back-end plumbing, the talent, and the workflows to make 3D easier to use across the business (what I call democratizing access to 3D).

And now, with AI + AR on the horizon, those bets are poised to really pay off. Enterprises can continue investing with confidence, knowing they’ll have right foundation to triple down on when glasses arrive. The companies doing this will be miles ahead of the competition. Those ‘3D apps’ (and VR/MR apps) will slot seamlessly into glasses and AR will feel like an ‘overnight success’.

This is not dissimilar to what we’re seeing in AI. Many companies have decided the risk of under investing is much greater than overinvesting; a classic case of paddling well before the wave. If you placed your bets a bit early, you can always play the longer game and let the market catch up. Playing catchup when the wave is beneath you is much harder, with much more dire consequence.

Companies that start building the bridge today between 3D and AR will have a major advantage throughout the 2030s. Fortunately for all of us, I’m seeing many of the largest, most advanced companies in the world starting to do exactly this.

For those enterprise that haven’t started, fret not. You have at least 3+ years. There’s plenty of time to get those 3D-first backends in place and 3D workflows ironed out.

But the time to start is now…

Stay tuned for Part II, where we’ll analyze the 7 key battle fronts in this race: hardware, software, distribution, AI, developers, philosophy, and leadership.

Until then, if you enjoyed… please subscribe via the button below :-) More to come on the future of spatial computing, AI, and how these tools will make us more human, not less.

This time, that place was Mongolia. The Mongolian Steppe to be exact; where Genghis Khan was forged, where wild horses run free, and where (the OG) nomads prove what we all know yet tend to ignore; that less truly is more.

It's hard to put this place into words. When you first arrive, it feels entirely alien. Entirely untouched by the modern world. It’s a place of pure simplicity, raw beauty, and ancient wisdom.

It’s also the perfect place to unplug and fall entirely off the grid. 

In that quiet, I found myself reflecting on the core questions we explore here at Medium Energy: how do we retain our humanity in the age of exponential technology? And not just retain… but enhance, i.e. how can we build/adopt these tools such that they make us more human, not less?

Mongolia, of all places, holds some answers.

It’s a place that feels miles away from modern life, where nomads live off the land, grounded in tradition and surrounded by nature. But even here, technology has crept in. The difference is, they’ve managed to avoid its downsides while capturing its upsides.

Somehow, the Mongolian nomads have found the right balance. They’ve embraced technology without letting it consume them (aka ‘medium energy’). Understanding how feels more important than ever. 

The most obvious reason is AI. The recent breakthroughs are bringing our sci-fi dreams to life at a breakneck pace. And in its wake, the interface to AI and our digital world is rapidly evolving. 

I was shocked to see the maturity of Meta’s Orion glasses this week, paired with ‘Her’ level AI and ‘Harry Potter’ grade UI/UX (aka the CTRL labs acquisition finally coming to life). 

I thought we’d be waiting at least 2-4 years before seeing a glasses form factor that sleek, that performant, and that close to consumer grade. My timeline for mainstream AR just collapsed dramatically (we’re probably 4-6 years out).

Perhaps more concrete and current is the backlash against the former darlings of tech: smartphones and social media.

Books like The Anxious Generation by Jonathan Haidt are bestsellers, and people are flaunting new-age flip phones as symbols of modern enlightenment, proof that they’re above it all. Meanwhile, neighboring China is the ultimate cautionary tale—an Orwellian reality where algorithms, social credit scores, and surveillance limit freedom.

Then there’s the Mongolian Steppe. Upon arrival, you feel like you’ve stepped back in time

But upon closer examination, that’s not quite the case. There’s an illusion and paradox here worth studying, and it starts with studying the children.

These kids were mature, confident, and poised beyond their years. I met numerous 8–10 year-olds that I would follow into battle. They were little Ender’s in the making, minus ‘the Game’.

One in particular stood out upon our arrival.

He expertly rode his horse through our camp, chin held high and still. He was adorned in ornate, traditional Mongolian garb: a finely woven robe with a stiff collar, a little hat with the folded-up wing tips, and weather torn leather boots.

This kid meant business. He was a relic of Mongolia’s powerful past and a reminder of youthful competence; that children can be more and do more than just bury their heads into a screen.

And then suddenly, he reached into his robe, pulled out a smartphone, and started to scroll.

Illusion shattered.

At first, I was saddened. The thought of these little generals breaking out into TikTok dances and calling each other ‘so brat’ was not something I was ready to accept. 

I then became curious: were these kids indeed suffering the same fate as our Western youth?

When I asked this question to our camp’s host, his answer was a resounding no. He said they’re too grounded by responsibility and tradition. Failure has real consequences and the past holds real meaning.

From a young age, these kids are forced into the family business: tending to their most important and only real asset; herds of horses, sheep, goats, cows, and yaks.

These crops of critters can range from the hundreds into the thousands. And to the nomads, they’re everything. It’s their primary source of sustenance, warmth, and money (largely as Mongolia’s primary export: fur + cashmere). Everything they do, every move they make, is in service of preserving these herds.

This gives their children an extreme sense of responsibility and accountability. From a young age, they’re forced to take care of something, to nurture something, and to take from it only what they need: fur, plenty of milk, and the occasional slaughter of an unlucky goat or two.

Sounds easy enough. Effectively a bunch of ranchers out on a prairie. How hard can it be?

From June-August, not too hard at all. The Mongolia Steppe is a slice of heaven. 

The weather is warm and calm. The blue skies are crystal clear and crisp. The green and mountainous hills roll on and on, as far as the eye can see. The green that covers this vast and expansive landscape is strangely uniform. It’s like someone stretched a singular carpet of grass across the horizon, or if the planet Arrakis from Dune was terraformed and just beginning to sprout a fuzzy layer of green.

Amidst this backdrop, the nomads expertly ride horses across the fuzzy expanse, and through meandering rivers. They chase their herds and zip around on motor bikes. They socialize and drink with their neighbors, playing games, playing music, wrestling, and dressing proudly in traditional Mongolian garb; hopping from Yurt to Yurt, each with an open-door policy. Come one come all. It’s like an Asian version of the Shire, minus the Hobbits.

Subscribe now

But then suddenly, it all comes to an end. 

Winter comes, and for the remaining 8-10 months of the year, its pure survival mode. This is not your casual winter wonderland. It gets down to -30 to -40 degrees F, with winds that tear through the thickest coats and can uproot the sturdiest of Gers (aka Yurts). The snow can become so dense and the winds so fierce that visibility drops to near zero, turning the vast openness into a disorienting, white void.

Between these bouts of wintery chaos, movement is life. These nomads must continually shift their herds to new grazing grounds, searching for pockets of exposed land where their animals can feed. During the worst winters, survival becomes a delicate balance between maintaining the warmth of the Ger/Yurt, keeping the animals alive, and ensuring there is enough food for the family.

Life is stripped down to its essentials: food, warmth, and shelter. The steppe offers no luxury, no reprieve. It is a test of endurance, where the only certainty is the severity of the cold and the unforgiving nature of the wind.

To live through winter on the Mongolian Steppe is to embrace hardship as an everyday reality. Now you see why failure is not an option, and why a lack of responsibility has real consequence, aka accountability.

Amidst this seemingly ancient lifestyle, there’s a stark contrast. They use drones to find and shepherd their herds. Cell service is abundant and the kids can easily jack into the grid. Social media and mobile games are always just one click away. But the responsibility of daily life seems to have produced a psychological and emotional shielding. The trite elements of social media become laughable and addiction to games, inconceivable. 

They see the nonsense, and they get the dopamine hits, but the weeds don’t have the same fertile ground to take root.

You might think this is an extreme case or that it’s erroneous; that this immunity is a product of circumstances we’ll never experience in the West.

Fair. I’m not saying we must face life or death scenarios to offset the downsides of tech.

But it does beg a fair question when it comes to raising our youth: how to simulate the right levels of responsibility and accountability to similar effect? Even if just in bursts?

There are certainly ways. During the Summers, my dad used to rip me out of bed in the early morning, throw me on the construction sites of his commercial real estate projects, and put me to work: picking up trash, stacking bricks, or my favorite… manning a jack hammer in a dark and damp elevator shaft, chipping dried concrete chips off the walls. I can feel the violent chatter of my teeth to this day. Lazy Summer mornings be damned.

At the time, I hated it. In the long run, it worked. Although when my time comes to raise a kid, I’ll certainly strive for more creative and fulfilling ‘simulations’ (by then, maybe that’s exactly what they’ll be… with complex virtual worlds rich with narrative, wonder, and problem solving).  

I’ll also think deeply about instilling traditions; the other anchor Mongolians deploy to avoid getting swept up in the digital fray. 

Mongolian nomads sprinkle traditions into many aspects of daily life. And their youth embrace it in wonderful ways.

They wear the same traditional gowns, hats, and boots as their ancestors.

They practice the same forms of song and dance; with traditional instruments, throat singing, and movement.

Their favorite sport, wrestling, also remains frozen in time, with the same traditional outfit, the same rules, and the same pre-match dance routine.

Even the micro-moments hold traditions, including the average exchange. When handing off items/goods/gifts of any sort, each person places two fingers on their forearm and extends an open hand; a relic of the past when exposing the opposite hand proved you weren’t carrying a weapon or trying to poison the other with a concealed vile. Yes, the ancient Mongolian Steppe was a rather hostile place, especially pre-Ghengis Khan’s reign of order.

Some people might see these things as antiquated. But therein lies their hidden power; because these traditions evolved in a slower, less frenetic world, they seem to possess some sort of counterbalance to the pace of modern life.

In a world where algorithms relentlessly shape our habits and routines, traditions offer something richer, and increasingly rare: intentionality. 

They also offer what technology often strips away: a sense of rootedness, connection to something larger, and the ability to sit with life as it unfolds, rather than constantly striving to control or curate it from tiny rectangles in our pockets.

Snapping us back to the future… This is why I’m so excited about the combo of AI and AR/spatial computing. It’s going to allow technology to dissolve into the background, intelligently displaying just the right amount of information, at just the right time, in just the right place, in just the right context (where we are, who we’re with, what we’re doing).

This is a paradigm in which technology conforms to us, rather than us having to conform to it. 

But with this, comes an inevitable reality: we will become technology, and technology will become us.

Heck, it already has. As I look around in the cafe where I’m writing this… every other person on a laptop is hacking away into ChatGPT. We’re already offloading our thinking, our judgment, and our creativity to algorithms. And as for the hardware; smartphones have already made us cyborgs by definition; they’re direct extensions of our minds, our spirit, and our identity.

As this fusion accelerates and hardens, the primary message here is this: we must work to harden the most human parts of ourselves. If Mongolia taught me anything, it’s that we can throw down anchors to our humanity. They do so with anchors to each other (accountability), and anchors to their past (traditions).

What are your anchors? 

Here we go again. Yet another chance to nail that fateful question.

"Spatial computing? So... you put computers in space?"

…

I stare back blankly as my mind races through my options:

Option 1: "Exactly!" ... and just go on living my life.

Option 2: Capitulate, take the conversationally safe route, and god forbid, fall to the lowest common denominator within common parlance: virtual reality. Or worse... the metaverse.

…

No. I know how this ends. I leave feeling dirty and impure, knowing I've done our industry, no, the world, a disservice. I can't become part of the problem.

Option 3: Expand the scope a bit. Go with AR/VR.

But we know where this leads... they hear the A and immediately associate with one thing.

"Oh cool, AI. Like ChatGPT?" 

(hands in face emoji)

"No no, augmented reality and virtual reality.

"What's the difference?"

*Sigh. That'll be the the day. When I no longer have to explain the distinction, my job here will be done.

Until then...

"Well there's actually a spectrum of immersion." I can see it now, her eyes glazing over as I hit her with the sci-fi version of Bubba explaining shrimp recipes to Forest Gump.

"So VR puts you into an entirely virtual world, and then AR brings virtual things into our world, and then XR covers the full spectrum of immersive experience, which is some times interchangeable with MR (mixed reality), which is also just a fancy version of AR, and, and, and."

No, I'll spare myself yet another reminder of how early we still are, and how commercially/socially irrelevant (relative, that is, to our new dominant friend whizzing up the Gartner hype cycle, armed to the teeth with millions of users, billions in capital inflows, and trillions in total addressable market. Must be nice, AI!)

Option 4: Stand my ground, fight the good fight, and give her the good ol' fashion 'Ode to Spatial' spiel.

"Not quite... You see, spatial computing is human-computer interaction coming full circle, mapping itself back to its original creators and back to nature.

It's the complete evolution of computer science, crawling out of the primordial goo of basic one and zeros, dusting off the inanimate blink of the command line, denouncing the abstract symbology of the GUI, and coming to its final resting place as a mirror of the mind; a mirror that can either recreate or conform to this reality, and in doing so, conform to the way our minds have evolved to understand the world; in three dimensions, with a sense of space and a sense of time.

Space and time. The fundamental building blocks of reality; at least the one we see, experience, and most thoroughly understand.

Together they produce one of our few inescapable truths: gravity.

Yes, indeed, gravity = spacetime and spacetime = gravity; that oh so stubborn and invisible fabric, incessantly reminding us of the limitations of this world and our place in it. Which brings us to our third variable: location.

Space, time, and location. The inputs of all inputs. The ultimate computational trio, holding the key to computing's final frontier: artificial general intelligence. For what is spatial data but 'world data', and what is true intelligence without a complete understanding of the world?

With world data we get context and with context we get to inject perceptual systems with maximum agency; displaying just the right information, at just the right time, in just the right place.

We're talking perceptual systems of all types, from humans, to robots, to cars, to the inevitable array of embodied machines that sprout up in between.

For us humans, spatial computing levels the playing field with our digital companions. We can properly hold their hands and let their whispers guide us, their musings inspire us, and their nudges remind us of who we really are and what we really want; for will the exhaust of our digital lives not empower them to know us better than we can possible know ourselves?

Most certainly. Self-image and self-delusion be damned.

Terrifying? Perhaps. But dare we fight the inevitability of evolution? Or do we flip it on its head and realize... this is how we get back to our tribal roots; to the traits and experiences that make us most human.

You see, spatial turns the screen from a barrier into a bridge; a bridge towards more connection via higher bandwidth communication, towards more knowledge via direct interaction with the thing itself, towards more creativity via limitless expression and imagination, towards increased saliency in any given moment; more deeply encoding newfound knowledge, new memories, and new relationships.

Perhaps we should also call it ‘salient computing’ and really throw people for a loop…

Regardless, I can blabber until I’m blue in the face. But as well all know, seeing is believing. You won’t understand until you try it for yourself. And when you do you will see… spatial computing is not about disappearing into a digital world. It's about digitally enhancing moments within the real world we all so adore.

As for our machines, well... they now have a bridge between silicon logic and human intuition. They also have a portal into our shared hallucination, which just might be our best shot at solving one of the grandest and most important mysteries of all: the mystery of human consciousness and its ultimate source.

Option 5: Snap out of the day dream and just give her the layman's version

"Haha no, it's not putting computers in space. Spatial computing is simply..."

And... too late. She's gone. Swept into another conversation and back to living her life.

Damn. Should have just said metaverse...

Thanks for reading! If you enjoyed, please consider subscribing below and sharing with a friend (or three…). More fun rants to come on tech and how it can make us more human, not less :)

The wave of exponential technology is upon us and things are changing... fast. If you’re building a business, few things matter more than finding the right team to ride this wave & build your future.

Enter CultureMill Recruiting: a recruiting agency focused on gaming, AI, and web3. 

CultureMill understands the pulse of innovation and the unique talent needed to bring your vision to life. From software engineering, to product development, to design and art... CultureMill partners with founders & leaders to not just scale a team, but to build a culture that inspires.

If you’re growing a team in gaming, AI, or Web3 startup, contact CultureMill via the link below.

Contact CultureMill Recruiting

This is a deep dive into our favorite topic here at Medium Energy — how technology can hack our ‘internal technology’ to change how we think, act, and feel.

Particularly, feelings that are the essence of being human, e.g. awe, curiosity, surprise, and flow; each representing a powerful lever for mental & emotional wellbeing.

Anecdotally, these states make us feel more present, more empathetic, and more alive. But empirically, their health benefits have been relegated to pseudo-science, lacking academic rigor, evidence, and institutional support.

Fortunately, this is starting to change.

With advances in tech and neuroscience, we can now prove how these experiences rewire us for the better, improving our health and helping us flourish in all kinds of ways.

In the wake of these findings, a new field within neuroscience is emerging to study what sparks our 'inner tech' most. Turns out, it's one of the most human things we do: the arts, and more broadly, aesthetic experiences.

This new field is called neuroaesthetics, or for the more romantically inclined, the 'neuroarts'. In a sentence, neuroarts is the study of how the human brain and body responds to aesthetic experience, and how those experiences can be applied to mental health.

Upon researching, I have a new favorite thesis...

Spatial computing will be the ultimate unlock for the neuroarts. One of the most shining examples I've seen to date is a startup called TRIPP.

First and foremost, TRIPP is a wellness and meditation company. But they're also a technology company, using spatial computing and artificial intelligence to help us prioritize mental wellbeing and become the best version of ourselves.

At a surface level, you can think of TRIPP as the Headspace or the Calm of spatial computing. At a deeper level, and when you try the app for yourself, you quickly see that it's so much more...

Their progress to date reflects another core Medium Energy thesis: that we can harness the power of tech to combat its own afflictions. Which is where we'll start this journey— with the problem at hand.

The Problem

It's official.

We’ve arrived at the knee of the exponential curve.

This ascent holds so much promise: abundance, prosperity, the cosmos; the holy grails of our compounded intellectual intelligence.

Yet, our intellectual progress contrasts starkly with our emotional progress. This curve is flat and we remain as emotionally illiterate as our ancestors 5,000 years ago.

The divergence between these two lines is unsustainable. We need a way to bring them closer together; to innovate not just technologically, but emotionally, for the balance between heart and mind is no longer a nice to have. It's become essential. Without it, we're heading towards a consequence we can't yet grasp.

Sadly, we're already well on our way... We’ve all seen these stats and trends. Mental health is one of the defining plagues of our time.

So many of us are walking around in a fog, gripped by existential angst and searching for hope within a tiny rectangle in our pocket.

Perhaps the answer to all our problems will arrive in that next text, that next email, or that next tweet. Perhaps we’ll wake up to riches in Coinbase or thousands of new followers on TikTok. Or perhaps that next swipe will produce the life partner of our dreams... Oh please, won't this damn screen give us something, anything to reaffirm some progress? Some connection? Some relevance in this noisy digital-first world?

Sure, ‘information technology’ offers opportunity and hope in so many forms. But it’s also causing forms of self-hypnosis; trances of anxiety and depression, incessant mental loops powered by obsession with self, conceived of made up stories about our individual problems and abilities, or about our futures and perceived pasts.

Why? Because we’re over stimulated, over connected, and drowning in a deluge of (mostly unnecessary) information. Our favorite apps act now as real-time leader boards of who (apparently) matters and who doesn’t, creating a lens of perpetual competition and comparison.

This malaise reminds me of a quote from author Walker Percy:

“The search is what anyone would undertake if they were not sunk in the everydayness of their own lives. To become aware of the possibility of the search is to be on to something, and not to be on to something is to be in despair.”- Walker Percy

Amidst the digital cacophony, we've become ‘sunk in the everydayness’ of our own lives, forgetting who we are, what we’re capable of, and what makes us truly happy. Our awareness of ‘the possibility of the search' has been dulled...

While the consequences have been dire, they're sure to pale in comparison to what will come next if we don't adapt. This is the defining challenge of our time: the pursuit of new methods for navigating & shaping the landscape of our inner cosmos.

Fortunately, numerous companies have emerged to pursue exactly this, and they're attacking it from numerous angles; from biometrics and wearables, to wellness & meditation, to communities & retreats. While each has its merits, I find TRIPP to be the most compelling, especially over the long term. Largely because it has an opportunity to unify pieces from all of the above.

To understand how, let's take a stroll into the future...

The Vision

It's been a long day.

You finally get home and plop down on the couch, exasperated from all the ups and mostly downs. Pick your affliction: a work project gone awry, a sick and aging parent, a child struggling in school, financial woes. (We'll go with the most broadly relatable: work)

As you settle in, a faint light starts pulsing on your smart watch: a reminder to check your 'mood score'.

The charts have gone haywire. Your stress & anxiety levels are spiking and your mood score is at a monthly low. A soothing voice purrs from the AR glasses in your shirt pocket.

"Welcome home. Seems like you had quite the day... How are you feeling? And what's on your mind?"

You lay it all out. Just vocalizing it seems to help.

"I understand. Based upon what I'm hearing, I think I know exactly what will help. Why don't you join me in your sanctuary?"

You slip on the sleek glasses and switch into VR mode.

Suddenly, you're immersed. Not in an algorithmic, time sucking, social media doom scroll. But rather, a virtual room. It's a beautiful, expansive library, with floors & furniture made of glistening wood.

Your favorite books, art, and family photos adorn the walls around you, creating a sense of comfort, warmth, and ease. Except for the wall straight ahead. It's missing. In its place is an open balcony, overlooking a lush jungle canopy. The sounds of birds, monkeys, and critters of all types create a symphony of cheerful chirps and playful squeals.

This is just one of your many virtual retreats, AI generated based upon inputs from your own imagination and the data in a digital wallet; reflecting your values, your aspirations, and your dreams.

This place facilitates solitude and provides time to pause and process the storm of emotions, not numb them.

Within these initial minutes, time doesn't disappear into a black hole of diffuse attention. Time becomes an ally, producing a narrowed attention filled with intentionality and reflection.

Once you settle in, you click the TRIPP app. The library & jungle scene fades and you find yourself floating towards a pitch black horizon.

Some faint stars twinkle in the distance.

As you get closer, they expand into colorful galaxies, filled with rolling clouds of star dust: mesmerizing nebulas reflecting every color imaginable.

As you float through this cosmic array, you become awash in waves of soothing music, surrounding you entirely via spatial audio, wrapping you with a sense of calm. The music is tuned to high vibrational frequencies proven to heighten emotional states and soothe the nervous system. The melody is beautiful; a blend of ancient hymns and modern instrumentals.

The star dust then begins to spiral and concentrate into a sphere.

As the sphere takes shape, other users start to materialize around you; fellow road warriors with similar 'mood data' facing similar challenges. Just like a group fitness or yoga class, their presence creates a sense of belonging, accountability, and connection.

And now the session begins. A pleasant voice starts to guide you through a breathing exercise, instructing you to follow the rhythmic pulse of this sphere; slowly expanding and collapsing. It's in sync with the music, giving your breath just the right cadence, to produce just the right effect.

A subtle gong rings out, signaling the end. Your physical room slowly materializes and you glance at the clock. What felt like an hour was only 15 minutes. And what felt like an unbearable, existential angst, is now a hundred pounds lighter.

A message materializes from your partner, "Dinner is ready :-), XOXO"

Before heading downstairs, you think about your colleague at work, who is bearing the brunt of this disaster. You save the recently generated experience, navigate to the 'Community' page in the TRIPP app, and tap 'share with friend'.

You type out a note to go along with it, "This saved me today... Enjoy, and remember, it's just work :)"

That was the cherry on top: the feeling of paying it forward and helping someone else in need; digital altruism at its finest. As a reward, a little badge pops up and floats into your digital wallet icon: an acknowledgment of your gift and contribution to the TRIPP community.

You head down to dinner with your partner and kids, energized and eager to present a better, calmer, and more engaged version of yourself, successfully preserving the joys of family dinner.

And let's face it, it's these moments that are the real-world sanctuary we all want and need.

The Mission

This is TRIPP's end game. A world in which technology doesn't manipulate us for the worse, but shapes us for the better. This vision may seem 10+ years away, but it’s not. Experientially, most of it is here and now.

Sure, the AR glasses form factor could take that long. And yes, both digital wallets and personalized AI need a few years to mature. But the TRIPP app today offers these experiences in spades, spanning numerous categories, including Focus, Calm, Breath, Sleep, and Ascend. My favorite is Ascend, with content designed to shift the way you look at the world.

Much of this content is also customizable, which creates some real differentiation from alternative mindfulness apps. For example, you can create your own ‘TRIPP’ by mixing & matching your favorite audio/visual elements with your preferred breathing exercise. My go-to? Box breathing paired with an underwater experience, in which your surrounded by neon corral reef, glowing plant life, and the distant, echoing cry of a humpback whale.

These visuals and sounds gave me something to latch on to. Something to distract me from my sporadic thoughts. They helped me focus, maintain my breath, and feel more present; a stark contrast with my more bare-boned meditation experience: a black void of nothingness and the ultimate playground for my neurotic monkey mind to wreak havoc, unencumbered.

TRIPP's focus with these experiences is on the more... surreal. Other apps might provide personal sanctuaries like the library and jungle scene, but the more realistic sets + settings make it difficult to fully hack our 'inner tech'. Our brain isn't easily fooled by a virtual beach, waterfall, or mountain top. The lack of certain senses encourages the sense of disbelief (e.g. the smell of the ocean). This inhibits our ability to fully escape and become swept away by novelty, wonder, and awe.

But when you blast into the other worldly; into the unknown, the brain doesn’t have anything to compare it to. And that's when the magic happens.

But perhaps the real magic is just on the horizon, with the power of AI.

TRIPP just launched an AI companion that aims to know us better than we know ourselves, objectively and without bias. They call it Kōkua, which in Hawaiian is a spiritual word for support. More deeply, it means a selfless expression of care, where one person reaches out to lift another.

This AI is unique because it’s trained by 'mood data' from the wider TRIPP community. Today, this data is provided voluntarily by users before and after a TRIP session, of which they've recorded over 10 million 'TRIPPS' to date.

Tomorrow, this data will include biometric data, be it from your smart watch, headset, or other future wearables. These devices are already gathering a bevvy of signals about our mood/emotional state, including heart rate variability, body temperature, galvanic skin response, and blood volume pulse.

What I find most interesting, is that each time you do a session, you're contributing to a wider intelligence that will help support others with similar needs, taking the idea of a 'support group' to a whole new level.

As I write this, I can sense some eye rolls from the metaverse skeptics. And listen… I get the hesitation. But it's important to understand — these immersive experiences are not designed to pull us away from the real world we so adore. They're designed to help us better navigate our inner world and re-emerge as better versions of ourselves.

Versions with more resilience, more gratitude, and more empathy. Versions with more time for reflection, and in turn, lives lived with more intention.

To fully appreciate TRIPP's mission, it's also important to understand why these experiences matter, and how they impact our bodies and our minds. To do so, we'll turn to a budding field of neuroscience called Neuroaesthetics.

The Neuroarts

We've all felt the power of aesthetic experience: the sense of wonder from an artistic masterpiece, the raging curiosity during a magic show, or the dizzying awe from an explosive sunset.

Some way, some how, these moments hack our 'inner tech', i.e. the miraculous wiring and firing of our biology, physiology, and neurology; the milieu of feeling & subjective experience.

For most of our existence, these feelings were the stuff of mystics and artists. Too soft and too mysterious for the hard sciences.

But thanks to the Neuroarts, perhaps we should add an A to the acronym that is STEM. We can now prove that aesthetic experiences can improve mobility, memory, and speech. They can relieve pain and PTSD. They can enhance mental health and learning outcomes. They can even build resilience and prevent disease. (If you want to dive into the data & research, see here, here, and here).

At the helm of this movement is the NeuroArts Blueprint, a new organization formed by the Johns Hopkins International Arts & Mind Lab and the Aspen Institute. Leading this new organization is academic and author, Susan Magsamen. She’s their co-director and one of the world's leading neuroarts evangelists. Susan is also the founder and director of the International Arts & Mind Lab, which sits within the 'Center of Applied Neuroaesthetics' at Johns Hopkins School of Medicine.

If you want to explore further, here's an awesome podcast with Magsamen. She also wrote a terrific book with Ivy Ross, called "Your Brain On Art: How the Arts Transforms Us".

The book is well worth the read, but if I had to leave you with just one takeaway, it's the relationship between neuroplasticity and saliency. Particularly, how we can wield saliency to mold & knead our mind.

Neuroplasticity + Spatial Computing = Salient Computing

At the core of neuroarts is the study of how the aesthetic impacts neuroplasticity, aka the brain's ability to reorganize and adapt by forming new neural connections (or circuits). These neural circuits power our movements, emotions, and memories, from playing the piano to recalling knowledge, to developing our sense of self.

The strength of these new connections is determined by their saliency—the more emotionally or cognitively engaging the experience, the more potent the impact, underscored by the release of neurotransmitters like dopamine that cement these pathways. Moments like a first kiss, getting a dream job, or birthing a child are etched into our memories precisely because of this chemical release, heightening our ability to "know" and "remember."

Neuroarts has proven that aesthetic experiences are major conduits for saliency, rewiring our brains in profound ways. The more immersive and sensory the experience, the greater the impact. Enter spatial computing – a tool for saliency on-demand, i.e. a personalized interface for brain development.

This is why spatial computing matters and why TRIPP is on to something special. I believe spatial computing can be the ultimate saliency-producing tool, hence its power for use cases such as education, training, communication, and in this case... mindset & mood. Perhaps we should call it... 'Salient Computing'.

TRIPP: The Neuroarts in Practice

While the science is young, the Neuroarts is giving us the knowledge to turn the aesthetic into a tool.

TRIPP's spatial computing application is just one approach, but I'd argue it will become the most powerful, and over the fullness of time, the most accessible. In this future, medication, therapy, and self-help books will still have their role. But Tripp has figured out how to package up and deliver something more profound: moments.

These moments hold the key inputs for activating the aforementioned neurochemistry. The most potent being curiosity, novelty, and awe.

As important as the science is, we don't need data to convince us of the power of these feelings. Regardless, thanks to the neuroarts, that data is trickling in, starting with curiosity.

Psychologist and author, Todd Kashdan, wrote a book on the topic called, "Curious? Discover the Missing Ingredient to a Fulfilling Life." The primary takeaway, per Kashdan... "Humans find intense, lasting fulfillment in seeking new knowledge, new experiences, and in embracing uncertainty. Choosing to explore the unknown rather than avoid it is key to a rich, meaningful life." In support, the book reveals data showing that when curiosity is satisfied, our brain releases dopamine, the neurotransmiter associated with pleasure and reward. This reinforces our desire to seek new knowledge and new experiences, something that spatial computing + AI can serve up in spades.

Closely linked to curiosity is the feeling of novelty & surprise, both of which stimulate activity in the hippocampus by releasing dopamine, as indicated in these two studies (Frontiers, Molecular Brain). They’re a fascinating glimpse into how dopamine conducts the hippocampal regions to adapt, learn, and thrive amidst the new and unknown; a critical skill in this new exponential world.

Perhaps the most profound feeling TRIPP experiences produce is awe: the expansive feeling of belonging to something greater than ourselves.

Humans are hardwired for awe. It's the sensation we all feel when we gaze up at the stars or get lost in the beauty of a rainbow.

From 'Your Brain on Art': "Awe can induce physical effects, such as a warmth in our chest or tears in our eyes, and trigger a flood of neurotransmitters that create ideal conditions for forming new neural connections. There is an evolutionary importance to awe. It encourages us to move forward with new ideas, with purpose and a sense of possibility."

Dacher Keltner, a leading expert in the science of awe, eloquently said, "A little dose of awe is transcendent."

This is no longer just mystical handwavey voodoo. It's being studied and quantified. Two research efforts standout. The first is this study from UC Berkely in Psychology Today.

Their key findings are as follows:

• Awe decreases activity in the brain's default mode network (DMN, that orchestrator of self-focus and rumination).

• This reduction in DMN activity suggests awe can quiet self-talk and calm the nervous system, similar to the effects of meditation and flow states.

• Awe can also decrease sympathetic activity and increase parasympathetic activity, indicating a physical relaxation response in the body.

• Awe contributes to a greater sense of well-being and fosters prosocial behavior, which further enhances individual and communal well-being.

This ultimate conclusion? Awe shifts our focus from the self to the vastness of the external world, creating a sense of connection and well-being, while promoting greater generosity and cooperation.

Towards this end, the researchers explore simple daily activities, such as taking an "awe walk" and intentionally noticing beauty in the world. Nature-based 'awe walks' will and should always be our first option. But 'awe on demand' via 'spatial/salient computing' could become the next best thing, with arguably more magic and tastefully curated forms of novelty, curiosity, and surprise.

The power of awe has also been quantified by researchers like Beau Lotto, who measured the neurobiological state of awe in audience members during  perhaps the most immersive, spell-binding, awe-inspiring live show on earth: Cirque du Soleil.

Over ten shows, Lotto and his team recorded the brain activity of more than two hundred audience members, correlating their data with pre and post-performance surveys.

Their findings were remarkable. The brain activity across audience members consistently aligned with the neurobiological state of awe. So much so, that Beau and his team were able to train an artificial neural network to predict whether people were experiencing awe with an average accuracy of 76 percent.

Lotto's study uncovered additional insights. From 'Your Brain on Art' (and this terrific TED Talk):

"People who are actively experiencing awe have less need for self-regulation and a higher tolerance for uncertainty. Their tolerance for risk also increased. 'They actually seek risk, and they are better able to face it' Beau recounted in a popular TED Talk in 2019. “Something that was really quite profound is that when we asked people, ‘Are you someone who has a propensity to experience awe?’ they were more likely to give a positive response after the performance than they were before.”

These elements – curiosity, novelty, and awe – they collectively contribute to what I think will be one of the first mainstream use cases for spatial computing: creating states of flow.

'Flow' has become a buzz word, but it remains the optimal human experience, where challenges and skills are perfectly balanced and we operate at our peak potential.

It's the state we've all experienced during a deep conversation, a lights out performance, or a burst of productivity. These moments spur what flow researcher/expert Steven Kotler's refers to as STER: Selflessness, Timeless, Effortless, and Richness (from his book on flow states called ‘Stealing Fire’, which is one of my most recommended reads).

To me, this is the ultimate promise of TRIPP; using cleverly designed environments and technologies to strategically trigger the 'flow circuitry' in the brain - hacking our neurochemistry to unlock dormant reservoirs of creativity, emotional intelligence, and psychological flexibility.

While virtually induced, I don't view these transcendent mind-states as disconnected from reality. They just might be the most real experiences we can have.

Facing our reality

Speaking of 'real'... we can also use the aesthetic and spatial computing to confront the challenging and uncomfortable parts of our collective or individual reality.

As Anjan Chatterjee, a neuroscientist and expert in the field, notes, "The arts and aesthetics encompass far more than just beauty. They offer emotional connection to the full range of human experience. The arts can be more than just sugar on the tongue. In art, when there's something challenging, which can also be uncomfortable, this discomfort, if we're willing to engage with it, offers the possibility of some change, some transformation. That can also be a powerful aesthetic experience."

In 'Your Brain on Art', the authors point to Picasso's "Guernica" and Lorraine Hansberry's play "A Raisin in the Sun"; both powerful examples of how art can confront difficult themes like war, racism, and discrimination, while also offering profound emotional connections and opportunities for personal growth.

Moreover, spatial computing will be the ultimate storytelling machine, allowing us to explore and rewrite the narratives we tell ourselves – arguably the most important story of all.

As Tyler VanderWeele's research at Harvard has shown, one of the keys to a flourishing mindset is imagining one's best potential self by shifting personal narratives toward more positive frames.

These stories determine how we contextualize our lives and experiences. But unearthing and reframing them can be a challenge; yet another opportunity for spatial computing and a potential future use case for TRIPP.

Virtual worlds might not be for everybody, but they will offer something fundamental we can all benefit from: the ability to embody different avatars and roles, hacking our sense of identity and perspective through the power of immersive roleplaying.

As Meryl Streep eloquently stated, "Acting is not about being someone different. It's about finding the similarity in what is apparently different, then finding myself in there."

Falling back on science, according to this study on ‘perspective taking’, the act of inhabiting such a role can result in "neural changes in networks associated with perspective-taking, empathy, and identity shifts",

As a fun example, imagine showing up to a virtual gathering as a stick of butter.

No seriously. Close your eyes and imagine it. How would you feel? How would you behave?

You'd probably feel a bit more carefree. A bit more loose, silly, and light. And that's exactly what a real person reported during a virtual PTSD support-group meet up in VRChat. They turned their avatar into a stick of butter and it transformed their ability to let go of their trauma, connect with others, and show up in a more open and maleable way.

This is just a glimpse into how spatial computing and apps like TRIPP can become powerful tools for personal growth and self-discovery.

Conclusion

So, whether it’s drifting through outer space, or embodying your favorite edible accoutrement, the combo of spatial and AI is going to open up a limitless canvas for transformative experiences.

In the same way we meditate to create a sense of calm, or hit the treadmill to boost serotonin/endorphins, we'll be able to easily tap into curiosity, novelty, and awe; all by simply slipping on glasses for a 10/20 minute aesthetic experience, combining the best of meditation, mindfulness, and perhaps one day, even physical movement and play.

This will be possible from any place, at any moment, with anyone... no matter their location in the world.

And herein lies spatial computing's endgame: the ability to have these salient experiences together.

Because after the neurochemicals, the next best thing they can produce is a conversation… a deeper, more meaningful conversation; about what comes up, what it means, and how to change, all while supporting each other along the way.

Because only one thing about our external world is certain... Not only will change remain a constant, but it’s about to get an exponential multiplier. Of this, there is no doubt.

Our internal world will need a massive upgrade to keep up, but this time, we'll do so from the inside out.

If you made it this far… thank you for reading! I’m beyond grateful for the time and effort. And if you enjoyed, please subscribe below and consider sharing with a friend or two… Appreciate your support in helping us spread a more positive vision for the future!

The mind boggling hardware, the enabling software, the widening moats, the competitive advantage, the profit, the cash flow, the AI frenzy, the timing…

It’s breaking both mental models and financial models alike, forcing everyone to rethink what’s possible. Alas, the power of exponential progress, now personified and tangible.

Much of the world was caught by surprise.

But if you know NVIDIA CEO, Jensen Huang, and happened to follow his journey, you probably aren’t that surprised.

You’d have seen the decades of patience, positioning, and planning. Decades of being misunderstood.

I mean, does it get more prescient than this video?

Some notable quips:

• “I don’t need to change the world overnight. I’m gonna change the world over the next 50 years.”

• “Having simpler ideas that you can execute on perfectly is sometimes better than grandiose ideas that your company can’t execute on”

• “I don’t need to build a killer product overnight, I just need to build a winning product. And the goal of winning is so you can play again.”

He kept it simple in the early days, compounded wins, and eventually created a secular tail wind for the ages.

In my day job, I had the good fortune of spending 1-1 time with Jensen Huang back in early 2022, just before their ridiculous ascent.

He’s easily the most impressive CEO I’ve ever met; unbelievably humble, poised, thoughtful, and bold (in all the right ways). If there’s one leader I strive to emulate, it’s Huang.

He’s since blasted into the stratosphere. As Jim Fan said, he’s now the tech bros Taylor Swift: part rock star, part business guru, part philosopher for the exponential age.

In which case, consider me a… Huangy? (okay we’ll workshop that one)

But despite it all, his humility and poise remains. He hasn’t let the moment get the best of him.

My favorite Huang’ism to date is the video below. It’s been making the rounds (and ruffling the feathers of the overly sensitive).

If you’ve suffered any missteps or setbacks, if you feel weighted down by any regrets… take the two minutes and watch this clip.

It will help shift your pain & suffering from a liability to an asset; past, present, or future.

A few notable quotes:

• “People with very high expectations have very low resilience. Unfortunately, resilience matters in success. And I don’t know how to teach it to you other than… I hope suffering happens to you.”

• “In my company, I use the word pain & suffering with great glee. I often say ‘Boy this is going to cause a lot of pain & suffering’, and I mean that in a happy way. Because you want to refine the character of your company. You want greatness out of them. And greatness is not intelligence, greatness comes out of character. And character isn’t formed from smart people, its formed by people who have suffered.”

Now, this message isn’t new. It’s a spin on the idea of antifragility, and we’ve all heard some semblance of it before; from parents, teachers, coaches, etc.

But I’ve been wondering… despite its poignancy, why is it so hard to internalize and put into action?

There’s the psychological reasons: humans are wired to minimize regret and maximize pleasure.

There’s also the social reasons: many of us are raised to play it safe and avoid unnecessary risk.

We also know delayed gratification is a thing, and we know that our greatest triumphs are always on the other side of hard work + risk.

Yet, here so many of us remain; stuck, trepidatious, aimless, and unsatisfied.

So how do we burst through the dam? How do we just… begin?

On that note… some more Church of Jensen programming, and a fun paradox for us to contend with.

The Acquired guys (awesome business podcast btw) ask him what company he’d start if he was 30 years old today.

Huang says he simply wouldn’t do it.

It was just too hard, too painful. It was “a million times harder” than he expected it to be, and had he known that… there’s no way he would have even taken the first step.

He says, “At that time, if we realized the pain & suffering, and just how vulnerable you’re going to feel, and the challenges you’re going to endure, the embarrassment and the shame, and the list of all the things that go wrong. I don’t think anybody would start a company. Nobody in their right might would do it. And I think that’s the superpower of the entrepreneur. They don’t know how hard it is. And they only ask themselves… ‘How hard can it be?’ And to this day, I trick my brain into thinking… ‘How hard can it be?’”

Appreciate the honesty, Jensen, but now that the secret is out… if we’re an aspiring entrepreneur or builder, how the heck do we develop this superpower?

I don’t know what Jensen would say. But I have one idea…

I think the answer is solitude.

This is the most upstream, fundamental thing we can do to positively impact everything else.

It’s also one of the few things in our complete control; the ability to be alone with our thoughts, to go deeply inward and not just ask… but to sit with the difficult and troubling questions that being human throws our way. Am I doing the right thing with my life? Do I believe the things I was taught as a child? Am I happy? If this was all for not, would I still do it?

A must read essay on this idea is ‘Solitude and Leadership’ by William Deresiewicz.

It’s one of the best things I’ve ever read. If you haven’t, just trust me — save the link and read it this week/weekend. It’s… stirring.

If you’re short on time, the principal message is this: if you want to do things that matter, and you want other people to follow, learn to be alone with your thoughts. Especially when those hard questions & moments arise.

Some highlights from the article:

“It’s perfectly natural to have doubts, or questions, or even just difficulties. The question is, what do you do with them? Do you suppress them, do you distract yourself from them, do you pretend they don’t exist? Or do you confront them directly, honestly, courageously? If you decide to do so, you will find that the answers to these dilemmas are not to be found on Twitter or Comedy Central or even in The New York Times. They can only be found within—without distractions, without peer pressure, in solitude.”

He then goes on to magnify the dangers of our all too scattered attentions and bias for multi-tasking; the afflictions of a life orbiting around personal dopamine machines: our phones.

In this context, he leans heavily into how to think… (or rather, how not to think).

“Multitasking, in short, is not only not thinking, it impairs your ability to think. Thinking means concentrating on one thing long enough to develop an idea about it. Not learning other people’s ideas, or memorizing a body of information, however much those may sometimes be useful. Developing your own ideas. In short, thinking for yourself. You simply cannot do that in bursts of 20 seconds at a time, constantly interrupted by Facebook messages or Twitter tweets, or fiddling with your iPod, or watching something on YouTube.

I find for myself that my first thought is never my best thought. My first thought is always someone else’s; it’s always what I’ve already heard about the subject, always the conventional wisdom. It’s only by concentrating, sticking to the question, being patient, letting all the parts of my mind come into play, that I arrive at an original idea.”

The author brings the piece home as it began, with a section from the timeless novel, Heart of Darkness. This is my favorite part of the essay:

“But let me be clear that solitude doesn’t always have to mean introspection. Let’s go back to Heart of Darkness. It’s the solitude of concentration that saves Marlow amidst the madness of the Central Station. When he gets there he finds out that the steamboat he’s supposed to sail upriver has a giant hole in it, and no one is going to help him fix it. “I let him run on,” he says, “this papier-mâché Mephistopheles”—he’s talking not about the manager but his assistant, who’s even worse, since he’s still trying to kiss his way up the hierarchy, and who’s been raving away at him. You can think of him as the Internet, the ever-present social buzz, chattering away at you 24/7:

“I let him run on, this papier-mâché Mephistopheles and it seemed to me that if I tried I could poke my forefinger through him, and would find nothing inside but a little loose dirt. . . .

It was a great comfort to turn from that chap to . . . the battered, twisted, ruined, tin-pot steamboat. . . . I had expended enough hard work on her to make me love her. No influential friend would have served me better. She had given me a chance to come out a bit—to find out what I could do. No, I don’t like work. I had rather laze about and think of all the fine things that can be done. I don’t like work—no man does—but I like what is in the work,—the chance to find yourself. Your own reality—for yourself, not for others—what no other man can ever know.”

“The chance to find yourself.” Now that phrase, “finding yourself,” has acquired a bad reputation. It suggests an aimless liberal-arts college graduate—an English major, no doubt, someone who went to a place like Amherst or Pomona—who’s too spoiled to get a job and spends his time staring off into space. But here’s Marlow, a mariner, a ship’s captain. A more practical, hardheaded person you could not find. And I should say that Marlow’s creator, Conrad, spent 19 years as a merchant marine, eight of them as a ship’s captain, before he became a writer, so this wasn’t just some artist’s idea of a sailor. Marlow believes in the need to find yourself just as much as anyone does, and the way to do it, he says, is work, solitary work. Concentration. Climbing on that steamboat and spending a few uninterrupted hours hammering it into shape. Or building a house, or cooking a meal, or even writing a college paper, if you really put yourself into it.”

At the end, the essay takes an unforeseen turn, reflecting on friendship as a form of solitude. Sounds counterintuitive, I know, but read on…

“So solitude can mean introspection, it can mean the concentration of focused work, and it can mean sustained reading. All of these help you to know yourself better. But there’s one more thing I’m going to include as a form of solitude, and it will seem counterintuitive: friendship. Of course friendship is the opposite of solitude; it means being with other people. But I’m talking about one kind of friendship in particular, the deep friendship of intimate conversation. Long, uninterrupted talk with one other person. Not Skyping with three people and texting with two others at the same time while you hang out in a friend’s room listening to music and studying. That’s what Emerson meant when he said that “the soul environs itself with friends, that it may enter into a grander self-acquaintance or solitude.”

Introspection means talking to yourself, and one of the best ways of talking to yourself is by talking to another person. One other person you can trust, one other person to whom you can unfold your soul. One other person you feel safe enough with to allow you to acknowledge things—to acknowledge things to yourself—that you otherwise can’t. Doubts you aren’t supposed to have, questions you aren’t supposed to ask. Feelings or opinions that would get you laughed at by the group or reprimanded by the authorities.”

So, whether its in conversation with yourself, or that one person who matters to you most… let’s embrace solitude as our best tool for building the resilience and super powers we need to identify and attack the hard things that matters to us most.

Because again… “how hard can it be?”

The Info Diet #7

And with that… on to edition #7 of ‘The Info Diet’ by Medium Energy: a simple list of content that has grabbed me most (articles, podcasts, videos, or books).

For the new comers… this ‘information diet’ is broken into three buckets:

(1) Technology- news & trends around all things cutting edge tech, with a focus on AI, spatial computing, and blockchain

(2) Being Human- all things that promote well-being and self-improvement, e.g. psychology, leadership, mental health, neuroscience, fitness

(3) Tech + Being Human- examples of all the goodness that arises when we properly merge buckets #1 and #2, aka: the upside from finding the right balance, or healthy tension, between tech and being human

Enjoy!

Technology

Sora + Luma for 3D | Video: We all know about OpenAI’s Sora: GenAI for high-fidelity video. But did you see how these videos can be used to create 3D assets/worlds with Luma? This is where things get wild...

Figure.AI raises $675M and now… this | Video: In partnership with OpenAI, Figure’s robot can: describe its visual experience - plan future actions - reflect on its memory - explain its reasoning verbally… Humanoid robots aren’t coming, they’re here.

AI + Math | Essay: AI’s ability to do math is the biggest hurdle to true AGI (artificial general intelligence). And Google is making huge strides… their DeepMind’s AI system surpassed the state-of-the-art approach for geometry problems, advancing AI reasoning in mathematics

Being Human

Crisis in Higher Ed and Why Universities Still Matter | Podcast: A great podcast from A16Z on why high education is failing us, and what we can/should do about it.

India Eliminates Extreme Poverty | Article: New data and new method suggests India has practically eliminated extreme poverty. A big step towards perhaps becoming the worlds next great superpower, backed by an at-scale-prowess with technology that never ceases to amaze me (as this great video/pod suggests)

Tech + Being Human

Government Debt | Post: I’ve written quite a bit lately about our current debt spiral and how to protect ourselves against it (bitcoin). This tweet from Balaji does a great job summarizing the problem with visuals and concise prose. It also hints at how this all might play out… aka: moving from a ‘physical state’ to a ‘network state’.

Customer support jobs… cooked | Post: Klarna released a blog stating that they are using AI to replace 700 customer service rep workers. Their ChatGPT-powered chatbot handled 2.3M conversations in the last month and average time to resolution dropped by 9 minutes.

This has led to $40M in additional profit in 2024.

Some see this and think humanity is doomed. I see this and think… A company now has more free capital to go do more stuff, invest in more things, and hire people for higher order, more creative work. The most immediate being moving support reps up the ladder to provide ‘Level 2 support’, creating a better customer experience. But this will also enable new classes of work. Prompt engineering is just one obvious example, but I think we’re going to see entirely new lines of business emerge.

Crypto appears to be mounting a comback. Not just in price, but also in stability and utility. Apps like Farcaster are capturing consumer attention, DePIN (Decentralized Physical Infrastructure Networks) is having a real moment, Web3 games are maturing and poised to launch, and the king, Bitcoin, is gaining a formal foothold within traditional finance.

Perhaps most importantly, we’re seeing a beautiful marriage emmerge between AI and crypto. If there’s one thing that will give Web3 a ‘raison d’être’, its AI. As Fred Wilson succintly said, “AI will help make Web3 usable for mainstream apps, and Web3 will help us trust AI.” (we’ll explore this further in a future essay).

All that to say… the timing feels right to refresh ourselves on cryptos promise and the role it can play within the ‘metaverse’ tech stack (along side spatial computing + AI).

This piece is part sci-fi and part non-fiction, bouncing between futuristic ‘day in the life’ scenarios and explanations of the how-what-why behind these new tools.

Hope you enjoy, and if so, please do consider sharing with a friend or three! ;-)

2042: A day in the life

The year is 2042. Your alarm goes off, but fret not. There is no where you have to be. Nothing you have to do. You roll out of bed with a sense of enthusiasm because of all the things you get to do. The hardest part of your day is deciding what to work on first.

When you enter the kitchen, a ruby red smoothie pops out of the fridge, freshly made with fruit from your robot-tended garden. Oh, a hint of cilantro? The culinary AI has outdone itself, yet again. You sit down at the table in your breakfast nook, put in your ear pods, and toss on your glasses. A holographic carousel materializes on the table with digital spheres representing your 'early morning' applications. Not social media, not email. Just a quote of inspiration, a reminder that its you and your partners anniversary, and a new meditation module from your favorite network of mindfulness content creators.

With a flick of the wrist, you select the 'meditation' sphere. You're suddenly transported to the edge of a cliff, overlooking a luscious rain forest and a roaring waterfall creating a shroud of mist below. Blanketed by the sounds of nature, you close your eyes, focus on your breath, and disappear.

A light bell rings and brings you back. Your breakfast nook slowly re-materializes and a text box floats into your field of view. "Congrats on your 100th session! You've reached Serenity Level 5." There's a list of perks: a new series of meditations, +15 Mindfulness tokens, and a SerenityDAO Membership NFT. Finally! You can now access their network of physical spaces for co-working, yoga, networking, events, and healthy food. Your partner is on Level 8 and has been raving about this membership for years.

Feeling calm and light, you take a shower, kiss your partner good morning as they lazily roll around in the sheets, and head into your office space. Upon entry, your voice assistant asks if you'd like the ambiance to be set to 'intense focus' or 'playful creativity'. You have a play date with your youngest kid later, might as well get in the mood now.

The light shifts to a turquoise blue hue, and the various 3D displays around the office come to life with the digital art pieces you tagged in your wallet as #play. They make you smile every time. They're all NFTs of course. Your favorite piece has a shining twinkle in the top right corner. A notification. The AR glasses track your eyes as you focus on the twinkle and you flick your wrist to select. It evolves into a message; an offer to buy the NFT from you at 10X what you paid. Thanks, but no thanks. On to your work.

You sit at your empty desk. No monitors, keyboards, or chords. Leaning back into your chair, you summon up your virtual workspace through your glasses. "Launch DAO dashboards". Three virtual screens appear and hover over your desk, each representing the digital HQ for the DAOs of which you're a member.

The first dashboard is YoloDAO. It's a small crew of your twelve closest friends who all happen to share a passion for music, artisan tequilas, and baking reality TV (and the associated baking stars, of course). Your squad originally formed the DAO to pool funds and invest in up-and-coming creators/entrepreneurs/bakers within each domain. It has since evolved into so much more. A place and a tribe where making money and having fun are one in the same.

You can see that eight of your friends are in the virtual house you all bought in Decentraland. Four of them are bowling, a couple are playing pool, and a few others are getting their sweat on in the virtual boxing ring. You'd love to jump into this immersive instantiation to hang out and catch up, but you're here today to make a bit of coin.

The first thing you check is your flash loan requests within a DeFi application connecting investors/patrons with creators. Your team put up $500k into a smart contract that acts as a loan pool. Creators looking to borrow crypto (BTC or ETH) to fund projects can get a loan from this smart contract that is guaranteed against their streaming revenue from existing copyrights, IP royalties, or business cash flows, all held as collateral. YoloDAO has five existing loans outstanding, each collecting 12% interest. Not bad. You cycle over to a list of open loan requests. Eighteen outstanding. Five of them stand out as promising, with existing traction and fan bases (according to the on-chain metrics of their tokenized content/IP). Next, the DeFi app scans the on-chain activity from each creators connected wallet to generate their on-chain credit scores. You select the top three and create a DAO proposal for the group to vote on their favorite creator to authorize a loan.

As you exit the DeFi app, a new notification appears. It's a holo-message from an upstart band that the DAO fell in love with last week. Your squad bought 5% of their recently released social token supply, giving you a stake in their future revenue streams. They're going places, you can just feel it. A volumetric capture of the band appears on your desk, each member a doll-house size representation. The lead singer steps forward.

"Thank you for attending our album launch party last week! We've airdropped you an NFT to commemorate the evening and the new album. Each NFT is a slight variation of the various sound tracks and album cover art. And each combo is algorithmically generated, evolving over time as our number of music downloads grow. It also gives you VIP access to all of our upcoming concerts for the next 5 years, along with invites to any of our private shows. We look forward to seeing you on the road!"

Context: Everyone is an investor 

Tokens have the potential to change the world. It sounds silly, doesn't it?  I naturally associate 'tokens' with my heroic feats at Chuck E. Cheese, acts of squirt gun marksmanship at the carnival, or items for barter in fantasy video games. It's easy to be dismissive of these nebulous 'digital thingies' (shout out mom). Names like Dogecoin, FlokiCoin, or the infamous (non-existent) Mongoose Coin don't exactly help. But let me assure you. This new asset class has the potential to accomplish something that has evaded humanity since the dawn of civilization. Part engine for enterprise, part great equalizer, part tool for fair governance... tokens just might, for the first time in history, give capitalists and socialists a reason to hold hands and skip off into the sunset with glee.

Why? The reasons are nuanced, but I think we can boil it down to this... For most of modern history, access to lucrative investment opportunities have been reserved for the 'in-crowd'. The good ol’ boys clubs of venture capitalists, record labels, art auction houses, and Hollywood studios. Not an accredited investor? Sorry. 'Don't have money, can't make money'. Forget your ability to self-educate, do your own due diligence, and manage your own risk. And they wonder why the wealth gap continues to widen...

With digital assets/tokens, everything changes. Everyone becomes an investor, anyone can access or provide capital with ease, and almost anything can be turned into an asset. The most important of which might be culture (to be explained later).

You've likely heard of this new paradigm dubbed as the Creator Economy. It often goes hand in hand with the 'Ownership Economy'. This is a world in which creators and their patrons/fans are no longer beholden to gate keepers, erroneous regulation, and centralized platforms that extract most of the value.

In this new paradigm, the supporters of a creator can coalesce as a community, own a piece of the project's success, and gain increasing rewards for adding value (rewards that are both virtual and/or redeemable for something in the real world). In turn, the creator is empowered with an army of evangelists (what I like to call a ‘marketing swarm’), and the ability to bootstrap any project they imagine, no permission required. They will also have a direct relationship with their fans, controlling how they choose to engage and transact, and even allowing fans to influence and shape a project. The veil of corporate interest between the creator and their community will be removed, opening up an entirely new design space for mutual participation.

It's difficult to imagine the creative possibilities and all the fun to be had when intermediaries no longer set the terms and control the narrative. It's going to bring about a cultural renaissance like we've never seen before. And I think we tend to discount the impact culture has on society. It's the operating system for everything we do, how we think, and what we say. We're going to soon see an explosion of niche, superior, and far more original projects and cultural contributions. Ones with second/third order effects that may lead to new forms of action, thought, and speech for society as a whole.

This isn't a far-off imagined future. It's already happening today. In its wake, venture capital as a distinct industry is slowly starting to disintegrate, eroded by empowered individuals and small groups who are deeply ingrained, connected, and knowledgeable within their niche realms of expertise. These groups are early experiments of a new concept in cryptoland called 'squad wealth'.

As defined in this seminal (must read) article, squad wealth is the ‘collectivization of finance, bringing investors together to support each other and a project. In so doing, the probability of success is increased and the downside diminished. Collectivization is about the group working together towards a shared objective by giving each other opportunity, leverage, and education, rather than individuals going at it alone'. Within these squads, Discord and Twitter are the new board rooms, DAOs the form of coordination, smart contracts the means of execution, and blockchains/crypto the rails and engines for value transfer and accrual. All of which can be brought to life with an internet connection and some clicks. Pretty powerful stuff. Who is your squad? How would you work together to achieve wealth? And what's stopping you?

Subscribe now

Back to the future…

Okay, time to create. You switch over to your pseudonymous identity and wallet, ‘CosmicTrance’, and select the corresponding avatar. It's subtle, but you feel your psyche switch gears. Day to day, you are a parent, an investor, and a writer. But as CosmicTrance, you tap into a whole other side of yourself. One you wouldn't reveal in a boardroom, with your family, or even with your friends. This is your escape. How you unleash your inner child and exhaust the lighthearted mischievousness that has built up within.

Your glasses switch to VR mode, and you're dropped in front of an all glass building. The top of the entrance to this virtual office says, SerendipityDAO, where you (or should I say, CosmicTrance) are part of a small team specializing in immersive story telling, complete with 3D artists, game engine developers, producers, and writers. The team's particular focus is 'choose your own adventure' experiences, complete with various narratives, characters, and mini-games.

Most of the team's success has come from creating experiences within the Space Odyssey NFT ecosystem. This is a series of NFTs that in aggregate effectively act as an open database of 'space loot'. Individually, each NFT is a list of various items: space craft, skills, planets, minerals, alien races, and attributes. These text based primitives act as building blocks with which anyone can build all kinds of things on top: video games with the space craft, comic books on those planets, movies about the alien races, or immersive art exhibits based on those space items or minerals. The more things built on top, the more value these base layer NFTs accrue.

The savvy business titans you all are, you've used most of the DAOs treasury to buy up the NFT primitives that you use in your experiences. This allows the team to make money from both the NFT value accrual and the royalty streams from the experiences you build on top. For this current project, you're acting as a subDAO within the much larger MeowWolfDAO; the leading immersive experience creator in the metaverse. They're eager to tap into the Space Odyssey loot fan base and your team is the best in the business.

CosmicTance's realm of expertise? Narrative and character development. Prior to joining SerendpityDAO, you/CosmicTrance wrote a series of sci-fi novels, also based on the SpaceOddysey loot NFTs. The series recently took off and people fell in love with the various characters, particularly Wade Johnson, a maverick star-fighter pilot and savior of the galaxy's outer realms. With the use of Epic's MetaHuman tools and the latest GPT-8 machine learning tool, you were able to feed in the text and dialogue from your novels to train the AI and bring your novel’s virtual characters to life as 'non-player' avatars. Fortunately, you personally own the IP for each of these characters, each one existing within a smart contract on chain. Anyone can use your characters, and when they do, it produces royalty streams for you in return.

You recently bumped into an AR hologram of your favorite character creations at last years Art Basel event, Timeless Tim. He was acting as an AR virtual tour guide for space inspired art exhibits. Who would have thought he'd make for such a great art connoisseur. A proud moment, and a nice $35k royalty check from that event alone.

Context: Ownership Economy 

For most of modern history, only a very small group of people could meaningfully impact culture. I'm talking about your celebrities, the record companies, Hollywood moguls, agencies, and certain brands. The internet has started to change this.

With social media, now anyone can contribute to culture. But the threshold for any one individual to capture meaningful amounts of value is very high. Most of the value is captured by the platforms (YouTube, Spotify, Medium, Facebook, etc) and a very small percentage of creators earn enough to self-sustain, much less thrive. Crypto has a proven track record of allowing both the short and long tail of creators to better monetize their contributions to culture, while allowing N number of external participants to invest and treat cultures as an asset class.

But the fight doesn't end there. Value capture is just one side of a two headed beast. The other is control over the means of production and distribution, of which intermediaries and platforms dominate today. What creators also need is a way to challenge that control and change who owns the means of production. DAOs and other forms of collective ownership might hold the answer.

DAOs make it possible for creators to work collaboratively without an external mediator dictating the terms of engagement. To steal from a great DAO article I read recently (shout out mystery author), "In a DAO, governance systems are decided by the members, and there are no external shareholders pressuring for profit extraction. Instead, in a creator DAO, the owners are the participants: those who make the content, distribute it, and consume and value it."

Media entrepreneur, Roy Price, wrote a Twitter thread about these ideas, particularly focused on the TV and film industry. Paraphrasing here... he discusses how over the last few years, some of the best content has come from outside the traditional Hollywood system. These are your Parasites, Squid Games, Atlanta, and Curb Your Enthusiasms of the world. All made by creators who were/are largely autonomous, and avoided pressure from the powers that be to edit their message and conform for a mass audience. Rather than air on the side of caution to make something 'good', something the majority would give a 6 of 7, they were able to take risks.

In the world of centralized, bureaucratic media development, Hollywood execs have a strong bias towards 'average', creating shows that follow the rules and appeal to the masses. Content that is contrarian and original might get a 10 from 30% of the audience, but a 3 from the remaining 70%. All too often, these shows just don't get made. But these are the shows that are rare, break new ground, and change the game. They're also the shows that change culture. Thanks to extreme persistence, Squid Games eventually saw the light of day. But sadly, most of these maverick creators/shows remain overlooked, ironically, making the best type of content all too rare.

Now imagine a pseudonymous, DeFi powered media system. One in which these 'rare' shows can be financed by anonymous wallets, with no social norms or pressures to conform holding them back.

Creators can use EVM (ethereum virtual machine) compatible currency to fund the media, while providing NFTs to fans, allowing them to guide the wider investing public by publicly endorsing projects. Roy Price likens these type of NFTs to a visible 'character trait' tied to your metaverse identity (a Game of Thrones fan, or a 'super sci-fi fan' as a pseudo-badge. Yet another interesting way to play with identify, value signaling, and tribe identification/formation in the metaverse).

The process would look like a NASDAQ of projects seeking funding, with DAOs submitting the projects. In Web2, you watch shows. In Web3, you watch shows you own and influence. Eventually, says Price, the 'head of programming' will just be a smart contract powered by some machine learning algorithms. With that same smart contract dividing up the shows revenues, distributing first to the original creator DAO, and then to individual wallets from all over the world. I don't know about you... but the inevitable creative and cultural explosion that would result from such a system excites the hell out of me.

Subscribe now

Education of the Future

You put the final touches on the script for the MeowWolfDAO choose your own adventure experience. A few character dialogue tweaks here, a few plot development edits there, and you upload the text into the characters personality database. To double check your work, you summon Wade into the virtual space.

He's on edge and grumpy, rambling on about some woman who tricked him, stole his journal and galactic travel logs, and is no where to be found on-planet. He needs your help to find her. Will you join the cause? Nope, too busy. He throws up his hands with exasperation, stomps his feet, and starts to tremble with tears. Whoa, okay, a little weepy and dramatic for the Wade we all know and love. But you'll have to tweak that later. You're getting a holo-call notification. It's your oldest calling from boarding school. You accept the call and she materializes in 3D next to a frozen and mopey Wade.

"Geeez, what'd you do to him?"

"Welp, not quire sure yet. Love is complicated I guess... Never mind him, what's up?"

"My governance proposal is about to pass! 95% of the teachers and students are on board for the MAPS curriculum. Yeeee! I knew people would want to take it with me!" She said, bouncing with excitement.

"That's awesome honey! You better take extensive notes, I want to learn everything with you along the way!"

"I will I will. People said what really pushed them over the edge was the Mycelium Network AR game. Everyone loved it! Thank you so much for pushing me in that direction. Whoop, I'm late to lacrosse practice. Gotta run!"

She blows a kiss, producing a pair of virtual lips that flutter towards you through the air. The 3D lips explode upon arrival into thousands of tiny digital butterflies, swarming you before they slowly disappear. Your eyes start to mist over once your daughter leaves. Creators Journey is starting to fulfill its promise.

Developing this next generation high school has been a passion project with your closest friends in the creator economy for years. It's the educational institution you wished existed as a kid. A boarding school that is both physical and virtual in the metaverse, powered by a DAO, and owned and operated by the students and teachers. The school's mission is to help students find their 'zone of genius' at an early age. The teachers are all successful creators themselves, working together to build curriculum of all types. The result is a vast inventory of digital courses and experiences. VR field trips to explore exotic countries, all new cultures, deep sea caverns, moments in history, the list goes on. There are also AR lectures that drop your favorite musicians, athletes, artists, or entrepreneurs directly into your living room for a 1-1 masterclass. There's a job board with a seemingly endless list of internship opportunities across the metaverse, with new projects and businesses popping up everyday. Students can tap into this inventory to customize their curriculum and cultivate their own innate interests and passions. Or, like your daughter, they can propose entirely new curriculum that yet to exist.

The metaphorical apple that is your daughter did not stray far from your partners tree, developing a shared passion and curiosity for the power of plant medicines and psychedelics. Books about the medical applications for psilocybin, ayahuasca, and LSD litter her room. You've learned a new use case during every dinner for the past month. When MAPS released their template for a high school curriculum in psychedelics, she didn't wait a beat. Her DAO governance proposal was out the door the next day.

You're particularly proud of her ability to recruit a team and develop the Mycellium Network AR demo. For only a few weeks of development, the demo was surprisingly polished and compelling. It guides players through a simple educational experience in real forest environments, allowing them to visualize the vastness and complexity of the mycelium network as it facilitates communication and nourishment between plants, trees, and wildlife.

With a simple job posting and a white paper, she quickly found two Unity developers to build the demo. Both are students within Creators Journey, one based in India and the other in Brazil. Both developers were  pseudonymous. But that didn't matter. Much of the best talent these days is taking this approach. By scanning their wallets, she could hire them with confidence immediately. No interview jitters, no one dimensional resume, and no bias standing in the way.  All that mattered were the on-chain certificates in their wallets to validate completion of Unity AR development 101, 202, and 303, along with verifiable sample code from similar projects. The blockchain doesn't lie. These kids were good.

They also had big ideas to augment her vision, suggesting she take a page from the 'play to earn' playbook of successful metaverse games such as Axie Infinity, but with a spin. 'Learn to earn'. The Mycellium Network AR game would reward players with tokens as they completed tasks and demonstrated mastery of the topic. The distributed tokens could come from a treasury funded by MAPS itself in the form of BTC or ETH, or sponsors who want to spread knowledge on the power of mushrooms and psilocybin. Or, perhaps the tokens are native to the AR game itself. As players/students accumulate more tokens, they graduate into certain 'knowledge tiers' that qualify them for future token or NFT airdrops of various sorts. Gosh... if only learning was this fun and rewarding when you were a kid!

Context: University of the Future 

Monetization and distribution are of course at the center of a thriving creator economy. But further upstream lies something equally if not more important; the means by which we help people tap into their own creative genius. Too many people lament about creativity, or their lack thereof. Despite common rhetoric, every person does indeed have a creative bone in their body. It's just a matter of identifying it and nurturing it early and often. Perhaps this is possible with better and more custom forms of education. Perhaps we can foster entire generations who will never know what it means to do things they hate or toil in ways that dampen the soul

As these examples allude, the combo of immersive tech and crypto could revolutionize how we engage and reward students for their work, potentially changing the very definition of what it means to be a student. Balaji Srinivasan is already running such an experiment today with his website 1729.com, where they offer crypto rewards for learning new skills, or completing small tasks. As for immersive and experiential education, these ideas are best explored in an essay called 'Hamilton and Disneys Education Flywheel', by one of my favorite writers, Packy McCormick. He discusses how the play Hamilton inflamed within him an entirely foreign level of curiosity in US history.

I had the exact same reaction he describes in his essay. The play created an insatiable desire to learn more about this man and our countries beginnings. Right after seeing the play I dove deep into Wikipedia, bought the Rob Chernow book, and had the Hamilton soundtrack on replay for a solid month. Do I know the words to every King George III song? Yep. A side effect I can live with given my newfound appreciation and understanding for my countries beginnings. My hidden Broadway aspirations aside, the takeaway is this: through the power of storytelling and creative IP, a previously non-existent yearning to learn and understand was sparked.

Packy goes on in his essay to imagine a world in which this type of content is the future of education. He lays out a business case for how and why Disney should package up IP like Hamilton, spin out all kinds of new experiences, formats, and flavors, and deliver them as part of a US history curriculum for youth.

No doubt, Disney would likely hit this out of the park, with the potential for a powerful flywheel effect. They already nail the first rung of said flywheel, content and compelling IP/narrative, acting as the basis for 'lessons' by world-class teachers. Imagine an interface within Disney+ that pops up after watching Hamilton, targeted at students, saying "Want to learn more? Click here to take the Hamilton US History course!"  In this example, Disney could treat teachers (or perhaps a TeacherDAO) as partners, working with them to evolve existing IP or media into educational TV shows, video games, or interactive assessments. Perhaps Packy's most compelling insight is how this could free teachers from the constraints of local (publicly and woefully funded) classrooms and open the door to income generation on par with top actors, musicians, and athletes. This could in turn inspire more of the worlds talent to teach.

My favorite aspect of Packy's flywheel is the idea of 'Communities and Experiences'. Imagine educational virtual worlds, such as Hamliton for US History lessons in Roblox or Fortnite. Or immersive theme parks e.g. the new Star Wars: Galaxy's Edge theme, in which you feel like a participant in the Star Wars universe. But in this case, it could be 'Hamilton Land', akin to the stale field trip that is Colonial Williamsburg, but much more fun, engrossing, and memorable. Within these virtual worlds, students from around the world could meet, create, and continue to explore the IP and supporting lessons (potentially creating the nucleus of their 'squad' for future endeavors as well?).

The final leg of this flywheel is where the game really starts to change for students, vaulting them into their realm of creation, entrepreneurship, and self-sufficiency. Consider the fact that the internet rewards those who create. Packy proposes replacing traditional tests with creative projects in which students showcase their knowledge. This could be videos that expand on Hamilton's story, podcasts that dive into a particular topics, games that promote various characters. Students could receive pass/fail for completion of the project, while gaining exposure and the opportunity to build their brand and presence within a desired field.

As a cherry on top, Packy suggests that the very best student produced content could be repurposed as 'top of the funnel' content for Disney’s formal lessons or curriculum, increasing their exposure and incentivizing them to do their best work. This formula could work across hundreds of IPs, with all type of new characters and worlds (real or imagined). My synopsis doesn't do Packy's essay justice. I adamantly suggest bookmarking and reading it for yourself.

My closing thought on this topic... It would be cool to see Disney make this all happen. But why not a DAO of creators and educators? Sure, iconic IP is the long pole in the tent, but they could pool funds to acquire (heck, DAOs are doing this today to buy the constitution and buy NBA teams. Why not IP?). I predict that we will see this attempted within the next 5 years.

And… back to 2042

Your AI assistant nudges you out of your mycelium day dream. Ah yes, it's your anniversary tonight. Time to get a gift. You ask your the assistant to show a list of top gifts ideas based on the past 12 months of conversation with your partner. A new self-driving car, a luxury safari vacation in South Africa, and piece of art from his/her favorite up and coming artists. Expensive taste... whats new. But nothing you can't manage. Each price tag roughly equates to the weekly royalty streams in ETH from your sci-fi character IP. You could use a vacation… You switch to VR mode, and are suddenly transported into an immersive tour of the glamping venue nestled amidst the South African wilderness. Wow... one helluva way to unplug. Safari it is. Right within your wallet interface, you take out a loan against those ETH royalty streams and receive USD stable coins in return. Taxable event avoided, safari booked.

As if right on cue, your youngest pokes his head into the office. "Time for our play date!" he yelps with enthusiasm. You check your watch and see its only 1pm. A few hours of 'work' should do it for the day.

'Indeed it is. Hey, do you want to see what your sister built?'

'Yeah!"

As you walk out of your office into the living room, you're met with a gigantic mess. Overturned furniture, stray pillows and cushions, a flipped over vase with dirt and plants on the ground. Unquestionably, this is the familiar wake of AR laser tag, woefully played indoors.

"What did I tell you about playing laser tag inside!" With each increasing decibel of your voice, and each notch up in blood pressure, a small red dot starts to increasingly blink and grow in the top right corner of your field of view. A subtle yet effective reminder that your emotions are getting the best of you. You pause, take a deep breath, and address your sons transgressions with a calmer voice and level head. His lesson learned and understanding cemented (hopefully), you instruct him to partner with the cleaning robots and clean up the mess. If he does a good enough job, and can lead the robots to a remedy in under 30 mins, he'll get to go out and play. With the authority of a tiny general-in-training, he barks high pitched commands that send the robots into a tizzy of tidiness, all while grabbing his own vacuum to join the foray.

You congratulate him on a job well done, acknowledging both his leadership and knack for hygiene. Okay, play date earned. You share the mycelium game with his 'youth-AR' glasses and drop the demo into his 'approved content' folder. Hand in hand, you approach the forest that is your backyard, fire up the mycelium AR app, and surrender to the entirely new wonders and insights of this place you've roamed a thousand times before.

In Part I, we focused on the obvious problem with our current system: money printing + inflation (aka fiat f*ckery).

In Part II, we hit the common misconceptions with inflation and expose the less obvious problem it creates (aka government stealing our time and The Cantillon Effect: the movement of purchasing power from the have nots to the haves).

To fully grok this essay, highly suggest starting with Part I & II. I think you'll enjoy... feedback on each has been quite positive.

• Part I | Fix the Money, Fix the… World?

• Part II | The Hidden Cost of Inflation

But I get it, who has time to read?! In which case... here's a TLDR on Part I & II:

• Modern money (aka fiat currency) is empirically broken. The root cause is a ledger for money that is entirely flexible, opaque, and easily corrupted, giving central banks and governments an easy button to fix short term economic pain. With the stroke of a key, they can print money & increase money supply on a whim.

• In just the US, between 2008- 2022 the Fed has partnered with big banks to print $10T, increasing the US Money supply by 246%. More than 2x the amount of US dollars have been printed in the last decade than in the history of the US dollar. In other countries, this problem is far worse and much more blatant (see Japan, Brazil, Israel, Mexico, Vietnam, Poland, Venezuela, Bulgaria, Ukraine)

• The result is rampant inflation. We're now told that inflation is coming down. But CPI (how we measure inflation) is a complete scam.. It doesn't include any of the things the average person really desires, e.g. a house, a trip, the gym, a meal at a nice restaurant, etc. They also replace key products/services within CPI with cheaper versions as the better version inflates... (!?!?!)

• They also tell us we need inflation to spur investment & growth. Not true. See the booms in innovation & growth in the 1800s and during the Renaissance (both no a hard money standard, with no structural inflation).

• In reality, the root incentive within our system is to boost money supply & create inflation. This is for three key reasons:

  • 1/ Inflation is a mechanism for government to implicitly default on its debt and push the debt burden onto the general public (i.e. a shadow tax)

  • 2/ Inflation moves wealth and purchasing power from the have nots to the haves. This is a reverse robin hood effect that is widening the wealth gap. The rich, powerful, and connected get access to printed money first, allowing them to buy scarce assets before prices rise downstream. Meanwhile, everyone else is priced out of living a normal, high quality life. They struggle to keep up, despair kicks in, and the seeds of popularism + social unrest are sowed...

  • 3/ Inflation props up a system built upon mountains of debt. It needs inflation to boosts the collateral & value of loans, and to ensure centralized sources of power/control avoid default & complete collapse.

The stark reality of this situation: all the debt governments are trying to pay down with our purchasing power... its already insolvent. All of it. It's backed by nothing and there is no realistic way of paying it off. The only solution is to increase the money supply and keep trying to inflate it away.

The multi-hundred-trillion-dollar question... how long can this go on? Forever? Is infinite leverage a thing? 

As the foundation wobbles, perhaps a parallel system is a good idea, and at the very least, a smart hedge or insurance policy.

Let's explore why.

Subscribe now

Part III | Why Bitcoin (Really) Matters

Concerns about government debt are nothing new. We've all heard the hemming and hawing from parents, teachers, and politicians about government spending, the federal deficit, and austerity.

Real eye-glazing-change-the-channel-go-on-living-my-life type of stuff.

When I tried to explain our current debt crisis to a buddy, he said "Well yeah, what's new? America doesn't run on Dunkin', it runs on debt".

A cute Boston-native quip... Also a scary metaphor for general public sentiment, stemming from the fact that some people think they've seen this movie before.

The first debt hysteria happened in the late 80s/90s. That's when we created the famous 'debt clock' and Ross Perot had the most famous independent presidential run in history, campaigning on the federal debt issue and widening deficit.

Debt was indeed soaring and our interest expense was accelerating. People expected the sky to fall.

What they didn't expect was a 30 year period of unprecedented growth and deflation. China became our friend, the Soviet Union crumbled, and the eastern world opened up. This fateful marriage between Western capital and Eastern labor/resources birthed our savior: globalization.

In tandem, we dropped interest rates to historic lows and experienced a GDP bonanza. But the world and global banking system also became massively over leveraged along the way.

Decades of complacency later, our chickens are coming home to roost. It's the late 80s/90s all over again. But this time its far worse, at a much grander scale, and accelerating at a much faster pace: all by multiple orders of magnitude.

To explain why, let's start with the money in your wallet, or rather, the lack thereof (due to taxes). Peter St. Onge recently laid this whole fiasco out eloquenty in this video.

Highly suggest a watch/listen (about 3 mins long). Otherwise, I'll summarize:

• If you look at just the interest payments on our federal debt, it now consumes 40% of all personal income taxes. i.e. almost half of the money you pay Uncle Sam goes towards just the interest the US owes on its old debt.

• If we add in new debt (which came in around $2T in 23) that adds up another 80% of your personal income tax.

• That's right 120% of your income tax bill is going towards debt.

• But wait.... what about the remaining trillions we have to spend for the military, borders, wellfare, healthcare, social security, etc?

• Voila. The federal deficit in all its glory.

But again, federal deficits are nothing new. The US has almost always spent more than it makes. So what's different now?

A few things: scale, speed, and the extent to which our only solution is also our greatest detriment, i.e. we're being forced to saw off the very branch we stand on.

First, the scale & speed:

Annualized, the Treasury is now predicting a debt expense (i.e. our interest payment) of close to $1 Trillion.

In November 2023 alone, US debt interest was $89B. This is more than we spend for the Departments of... Agriculture, Education, Energy, Transportation, Homeland Security, Justice, State, Transportation, NASA, and Veterans Affairs... combined.

This is just on our old debt. To compound things, new debt is rising at the fastest pace ever. The US Government is currently on track to produce over $6T in debt, annualized. It took the the US 225 years to accumulate $6 trillion in debt. We're now going to produce $6T within 1 year. That's $12 million, every minute, of every day.

To make things worse, we've made that debt much more expensive by raising interest rates. For the last decade, interest rates were near zero (making the interest payments nominal). Now, they're close to 5%, and a record high $8.9T of govt debt is maturing over the next year. The interest on this debt will have to be repriced at these higher rates… i.e. these interest payments will more than DOUBLE.

As a result, we're forced to take out a new 'credit card' (more debt) just to afford this higher interest payment: the makings of a classic debt spiral (to go deeper on the topic, this tweet by James Lavish is a must read).

Another fun (upsetting) thought experiment: there's about 7k - 10k people retiring every day. We could take the money we’re adding to the national debt, and instead, distribute it to new retirees along with a pat on the back and a nice note saying 'thank you for your contribution, go enjoy your life'.

That check would be $2.5M.

Instead, that money is spent on.. well, who knows what. Retirees see no noticeable benefit from it and that lovely debt burden gets pushed off on to their kids.

*sigh....

Zooming out, the total US debt is now at $34T and on pace to $35T by June.

And we haven't even taken into account future debt from ongoing proxy wars and more inevitable money printing (which is one of the main ways money gets printed: the US issues debt and the Fed + Big Banks buy it, injecting more cash into the system).

Sounds bad, I know. So what are our options?

• Cut our committed spending? Nope, its political suicide. No one is going to do it. At least not to the extent that it makes a difference.

• Raise taxes? Doesn’t work either. This disincentivizes and disables companies and entrepreneurs ability to increase productivity, conduct R&D, build production lines, hire more people, etc. We'd end up with higher taxes on less productivity/revenue, of which we need as much as possible. Not an option.

• Print money & issue more debt? Keep doing what we've always done. Raise the debt ceiling and borrow some more.  Stark reality: this is the only option. Listen to 98% of experts, and they'll tell you this outcome is a foregone conclusion, further cemented by the fact that the banking system remains unsound and the US government can't afford a recession (which has been looming for some time now). By printing money they release the pressure valve on banks (with increased liquidity), shore up the markets, and ensure that both tax revenue and GDP don't fall off the cliff.

And here in lies the 'sawing off the branch' metaphor:  when they inevitably print more money, they will fan the flames of inflation. This forces the Fed to raise interest rates. But in doing so, three things happen:

• 1/ they create more instability in the banking system

• 2/ they increase the cost of our debt (the aforementioned interest expense), and...

• 3/ they lower tax receipts (as asset prices fall and corporations reduce spending/growth).

A classic tripple whammy that creates an even larger federal deficit than before.

This creates the need for more debt to pay it all off (at higher rates mind you) and further money printing to inflate away its cost.

And... we're back to where we started: more inflation, more interest rate shenangians, more erosion of the banking system, more recessionary risk, more money printing to fix it all. And so the spiral continues...

People might say, "but we'll be fine because our GDP is going up, right?"

Wrong.

A major driver of rising GDP is inflation. Its increasing in dollar terms, not in net new revenue and production, so tax revenues aren't really going up and closing the gap. They actually went down because higher interest rates have crushed assets, and in turn, diminished one of our primary sources of income: capital gains tax.

So as mentioned, the gap only widens.

Another common reaction is to think that the US government knows what its doing. Its full of economic wizards and they must have a master plan.

If that's you, consider the following anecdote from Lyn's book 'Broken Money' (and I'm paraphrasing): during a congressional hearing in early 2021, a congresswoman asked the chairman of the Fed about the implications of the 25% year-over-year spikes in broad money supply due to recent money printing. At the time, inflation was only 1.7%. She asked if it would impact inflation or the value of the dollar.

The chairman dismissed the concerns, saying "that such a surge in the amount of broad money likely wouldn't have important economic implications, and that we may have to 'unlearn' the idea that monetary aggregates have an important impact on the economy."

Fast forward a few months. Inflation starts rising and the Fed chairman initially dismisses it as 'transitory'. And so, they went on expanding the base money supply with 'quantitative easing' (money printing).

Suddenly, inflation is off to the races, hitting its highest rate in four decades.

Our oh so wise leadership at the Federal Reserve panics and does a complete 180. They shift their monetary policy and label inflation as the #1 problem to address, going on to rapidly raise rates and reduce the money supply at a record pace. In doing so, they created more than a trillion dollars worth of unrealized losses for banks holding Treasury securities and other 'low-risk' assets.

Directly from Lyn's book 'Broken Money': 

"By sucking deposits out of the banking system at such an aggressive rate, (the Fed) contributed to some of the largest bank failures in American history. By 2023, banks across the country had severely impaired capital ratios due to sharply rising interest rate. For the first time in modern history, even the Federal Reserve itself was running an operating loss due to paying such high interest rates on its liabilities relative to what it was earning on its assets. These Federal Reserve decisions affect the monetary conditions for 330 million Americans and billions of people in foreign countries and yet are made manually and subjectively by a group of just twelve people."

Lyn Alden, one of the most sane, level headed, objective, and pragmatic intellectuals in finance today... goes on to say, "How did we get to this point? Why isn't our money better than this? The global financial system has been broken for developing countries throughout modern history, and in recent decades, it has built up serious imbalances even for developed countries. It's no longer solid at its foundation, in part because its core technology is out of date."

That technology is an entirely flexible, centralized, opaque ledger of money; nothing more than a single node, 1990's database managed on-premises at the Federal Reserve.

The energy/effort required to monetize this debt and expand the money supply? The stroke of a few keys: alt-Control P (Print).

Obviously, the US Government/Federal Reserve isn't going to update their technology any time soon (if ever...)

But we, the people, most certainly can...

Our best option is the antithesis: a ledger/database for money that is 1) inflexible, decentralized, and transparent, 2) has a real-world physical constraint to producing more, and 3) is easy to self-custody, hyper portable, and unseizable.

In the past, the absurdity of our money printing + debt-fueled system was brushed under the rug.

Those who warned about this outcome were labeled conspiracy theorists and boys crying wolf.

Now, even the damn Federal Reserve Chairman (Jerome Powell, our system's primary puppeteer) himself is crying wolf. See this highlight from his interview on 60 Minutes.

He say's (paraphrasing), "The US Government is on a unsustainable fiscal path... and that just means the debt is growing faster than the economy... (over the long run, this concerns me very much), effectively we're borrowing from future generations."

Most recently, Jamie Dimon called it the most predictable crisis in history.

This narrative is rapidly growing in strength, especially on Wall Street. The people in the know are paying close attention and hedging accordingly.

Many are using gold. Some of the smartest, most powerful, and most influential are using digital gold, aka the aforementioned, modernized ledger of money: bitcoin.

Why? Because in a world/market rife with uncertainty and opacity, bitcoin is one of the world's only assets rooted in certainty, transparency, and predictability.

It doesn't matter what interest rates are or what the money supply is. It doesn't matter if there is peace or war; if we have a republican or democrat; if our economy continues to fall folly to human guessing and incompetence (aka central planning).

Regardless of it all... this asset is going to produce a fixed amount (21 million), on a known schedule, and remain entirely auditable along the way.

This is why people like Larry Fink, the CEO of the worlds largest money manager (Blackrock), someone who used to call bitcoin an 'index of money laundering', is now calling bitcoin a 'flight to quality'.

We'll cover how & why bitcoin = quality in a future essay. But first, its important to consider the downstream impact this fucked up game is having on daily life and society at large; beyond just the rising costs, wealth gap, & the Cantillon Effect (discussed in Part I & II)

We'll hit those topics next time in Part IV.

For now, take a breath and relax. Everything is going to be fine. (I think...)

Meanwhile, probably wise to start making that hedge. Buy a little bit of bitcoin and let the power of asymmetry help you sleep better at night.

1% - 5% of your net worth is all the protection you need. An example to illustrate the point:

• Compare two portfolios. Portfolio A has 100% exposure to the S&P 500. Portfolio B has 2% BTC exposure, with the remaining sitting 98% in all cash…

• Now pick any four year period (since bitcoin’s inception) and look at the compound annual growth rate.

• For any one of those periods… Portfolio B would have at least matched the performance of the S&P 500... with only 1/4 the volatility.

• Pretty wild…

• Key takeaway: allocated appropriately, and along a long term time horizon… bitcoin can create LESS volatility, not more, with massive upside to boot (i.e. the ultimate asymmetric bet: a critical concept to understand if you plan to hold bitcoin).

The challenge is building conviction and lasting through that 4+ year holding period. Fortunately, the beauty of that smidge of exposure? It doubles as a force function to learn… enlivening your curiosity and compelling you to study bitcoin and all its nuance.

Doing this homework is critical. It’s the only way to ignore the perceived volatility and take a long term view. When you do, I promise… the conviction becomes an irresistible, gravitational force.

Hence the famous bitcoin quip, “once you see it, you can’t unsee it”.

If you’re eager to start learning now, this website is the most comprehensive out there: An Encyclopedia of Due Diligence.

With one glance, you’ll see why they say it takes 100+ hours to fully grok bitcoin.

But fret not. In Part V & VI, we’ll compress that journey down to 30 minutes.

Until then… watch this video…

Thanks for reading. If you haven’t read Part I and Part II, check em’ out below. They represent the critical first step towards building said conviction + gravity. Enjoy!

• Part I | Fix the Money, Fix the… World?

• Part II | The Hidden Costs of Inflation

I just walked into an Apple Store and bought it off the shelf. Easy peasy.

It was a surreal moment.

I’ve spent the past decade trying to make spatial computing real. Trying to make it matter. For most of that time, the average person just didn’t care, didn’t get it, or didn’t think it’d ever be a thing.

And then suddenly…. here was the defining retail space of our generation, flipped into a spatial computing shrine; a table full of Apple Vision Pro’s (AVP) stretched across the middle of the store, videos about the promise of spatial computing played on every wall, and a line of people wrapped around the walls, waiting for their glimpse of the future.

In the middle of the store was a ‘demo lounge’. People of all types were getting immersed: kids, parents, grandparents, business types, artistic types, tech nerds, jocks, you name it.

That was the moment that it really hit me; seeing all of their reactions. It was a cacophony of oooo’s, aaahhh’s, wow’s, holy shit’s, omg’s, unreal’s, amazing’s, etc.

All these years I’ve wondered if I was crazy. I’ve wondered if I was wasting the prime years of my career. I’ve wondered if all the countless demos, prototypes, events, presentations, business trips, and late night rants would ever amount to anything.

But in that moment, I was awash with excitement and relief.

I was re-energized.

I realized… it was going to be okay. I’m not crazy and this hasn’t been a waste. Spatial computing is going to be a thing and its going to change the world.

While we still have a ways to go… the dress rehearsal is over. It’s time to educate, integrate, and build.

My First Impressions

Despite all my essays and podcast appearances talking about the Vision Pro, most of my takes were based on second hand sources. I had yet to try the Vision Pro myself. I was taking a bit of a leap of faith…

I’ve now spent 5-6 hours in the device (including throughout my Sunday morning routine of coffee, journaling, house cleaning, and friends/family catchup calls).

And while my opinions are still forming, I thought I’d give a quick breakdown of my initial impressions (removing as much industry bias as possible).

In a sentence: The Vision Pro is incredible, and despite some mainstream media takes, it’s quite useful right out of the box, especially for certain types of people & professionals.

That said, it’s certainly an MVP (minimum viable product). Albeit, a powerful and massively impactful one at that. I can’t overstate the technical breakthrough here… the end result is a UI/UX that makes you want to come back for more (unlike devices to date).

While far from mainstream-ready, it's the 'mainstream awareness' and the starting gun we’ve been waiting for since the 60's.

All of my original takes (from this essay) hold true, especially on the use cases front.

There is immediate utility & value for…

• Screen Replacement: a mobile 'virtual workspace', hyper conducive to focus and flow. As a writer & podcast/video editor... this is my primary use case. - Limitless Home Theater: The Vegas Sphere or IMAX in your living room, in your hotel, on the plane, etc. (watching Masters of Air with the Sahara Desert all around me was...

• Sports & Entertainment: the spatial video experiences are mesmerizing. I mean... Being inside the recording studio with Alicia Keys? Behind the goal of an MLS game as the ball rips into the top corner? Pure goosebumps... this is the use case that will sell hundreds of millions of devices come V2.

• Spatial & Hands Free FaceTime: Turning your friends & family into the Wizard of Oz in your living room for a catch up chat is awesome, especially in being hands free, allowing you to do go about your day (e.g. while making coffee, cleaning the house, making a meal, etc)

• 3D Presentations: Using apps like JigSpace to tell stories about complex products or plans. This will almost certainly be the best way to convey value about anything that is inherently 3D. Enterprise knowledge transfer... fully unlocked.

• Spatial Memories: Re-experiencing special moments through the spatial photo/video capture... I've seen a surprising number of people cry from this experience. (Some wild philosophical implications from being able to relive memories at this level of fidelity...)

Okay, as a V1 product, it’s not all rainbows & sunshine.

Here are some of the cons:

• Avatars: You become an awkward avatar to others during the spatial FacetTime, and... the Apple Avatars have a long way to go (granted, it is in 'Beta')

• Weight: The weight is noticeable after 45/60 mins. But you can offset this with proper headband adjustment and/or using the alternate headband. (An observation: Despite that initial discomfort... the experience was so compelling that I didn't care at first. So much so that it sparked a desperation to find that sweet spot of weight distribution... Thankfully, it exists)

• iPhone Visibility: you can't see your iPhone screen via the pass-through quite as clearly as I'd hoped. And there's not yet a way to mirror your phone in the device, although I've heard this is coming.

• Lack of multiplayer mode: the primary downside is the extent to which its all single player, today... The real magic is going to be collaborative experiences. This is obviously on the near term horizon, so the negative quips about isolation don't hold much weight for me, at all...

Last thing I'll say... there's something about the wonder & awe induced by these experiences. Especially in watching other peoples reactions.

I brought the AVP to a little soiree and 'spatial-pilled' a bunch of first timers (and some hard core skeptics).

Their reactions were priceless: gaping mouths, gasps of disbelief, rants about all the possibilities. And the skeptics finally got it; classic case of 'gotta see it to believe it'.

My buddy ‘Eric the Skeptic’ said it himself… (this video is pretty hilarious and worth watching. He’s in the recording studio with Alicia Keys, and as a pianist himself, she’s one of his idols).

Here’s my friend Mike, an avid technologist who is equally as difficult to impress…

My main takeaway from these reactions: this tech taps into a level of human programming that is otherwise unreachable. But we can now access it on demand, while also measuring & understanding it in all kinds of ways.

It's hard to imagine all the magic we can harness as a result, for both our internal & external development.

This of course can be wielded for good & bad... It’s up to us to set the right guardrails, understand its power & effects, and harness the upside accordingly. Because no doubt... the upside is limitless... (especially when combined with AI).

We’ll cover more on this topic in a near-term future essay….

Until then, here’s this week’s Info Diet!

Subscribe now

The Info Diet #6

Welcome to edition #5 of ‘The Info Diet’ by Medium Energy: a simple list of content that has grabbed me most (articles, podcasts, videos, or books).

For the new comers… this ‘information diet’ is broken into three buckets:

(1) Technology- news & trends around all things cutting edge tech, with a focus on AI, spatial computing, and blockchain

(2) Being Human- all things that promote well-being and self-improvement, e.g. psychology, leadership, mental health, neuroscience, fitness

(3) Tech + Being Human- examples of all the goodness that arises when we properly merge buckets #1 and #2, aka: the upside from finding the right balance, or healthy tension, between tech and being human

Enjoy!

Technology

• Framing the Future of the Internet: Finally, a crypto/Web3 use case with real consumer potential: Farcaster- a protocol for building decentralized social networks. If you’re a skeptic about this space, this article is a must read. Promising stuff. .

• Sam Altman raising $5 - $7 TRILLION to build AI chips. This story is wild… but makes sense. Chips have become the most important & strategic resource of our time, and production capacity has consolidated into the hands of only a handful of players. Not to mention, the most important (TSMC), is at perpetual risk of hostile actionsn from China… I’m all for spreading out the power/bottle necks….

Being Human

• Extreme brainstorming questions to tigger new, better ideas- because the time to start thinking big and getting ambitious is now….

• Gut bacteria + mental health: Scientists identify specific gut bacteria linked to severity of depression and anxiety symptoms. Get on those probiotics people.

• The art of allowing change: Because we’re about to face a ton of it…

Tech + Being Human

• AI starting to threaten white collar jobs… and few industries are immune. You don’t say!

• MIT Study: AI not taking jobs- But wait… MIT CSAIL study reveals economic limits to job automation. Ah the joys of crossing the chasm!

• AI that can induce and stabilize lucid dreams- Okay… this is just insane. Worth reading the thread, but basically, this is like a LLM, but rather than being prompted by text, its prompted by brain states. From there, instead of generating words, it generates “ultrasonic holograms for neurostimulation to bring one to a lucid state.” Aka: it can produce virtual reality without virtual reality…

  • From the company Propheitc… “our mission is to give humanity the tools to explore and expand consciousness. Morpheus-1 is a leap forward in that mission, moving us closer to ultrasonically inducing conscious experiences on-demand and changing the world forever.”

• TLDR: Buckle up….

In Part I, we focused on the obvious problem: money printing & inflation (aka fiat f*ckery).

For complete context & appreciation, suggest reading Part I first (link here).

But I get it, time is money... so here's the Part I TLDR:

• Modern day money (aka fiat currency) is horribly broken. Why? Because time is money, indeed. And we are being robbed of it, slowly but surely, one (trillion) printed dollar(s) at a time.

• Money is a storage mechanism for all the effort, energy, and sacrifices we've made in the past, i.e. our savings. As we turn towards the future, these savings allow us to design, plan, and create the life we want. Sadly, most people around the world struggle to live the life they want (having kids, owning a house, good education, high quality food, a vacation or two, etc). Inflation is a major reason why and it’s poised to only get worse...

• In turn, inflation has become one of the most critical problems of our time. Money is upstream of everything... and when you follow the trail, you'll see that its manipulation is a major factor in many of humanity's greatest challenges: the wealth gap, popularism & political polarity, AI & automation, mental health, climate change, war, the list goes on.

• The heart of this problem is a ledger of money that is soft, manipulated, and easily corrupted. With a few strokes of a key, the supply of money has sky rocketed, causing a loss of purchasing power and an erosion of our savings/time.

• In just the US, between 2008- 2022 the Fed has partnered with big banks to print $10T, increasing the US Money supply by 246%. More than 2x the amount of US dollars have been printed in the last decade than in the history of the US dollar. In other countries, this problem is far worse and much more blatant (see Japan, Brazil, Israel, Mexico, Vietnam, Poland, Venezuela, Bulgaria, Ukraine)

• Globally, nearly half of the world’s countries experience double digit inflation, largely driven by similar increases in money supply. (Hidden Cost of Money) If inflation hovers at just 10% over the next decade, and wages don't keep pace, people will need almost 3x the amount of money to buy the same goods and services in ten years. The stark reality is that wages are not keeping pace e.g. see US, see Cali, and see Japan (suggest watching). And as this essay explores, the US & developed world are not immune from a similar fate...

With that backdrop, let's dive into Part II, where we'll hit two topics: (1) Inflation's common misconceptions, and (2) the less obvious problem it creates.

“If anyone can refute me—show me I’m making a mistake or looking at things from the wrong perspective—I’ll gladly change. It’s the truth I’m after, and the truth never harmed anyone. What harms us is to persist in self-deceit and ignorance.” -Marcus Aurelius

Don't we need inflation?

Despite its impact, inflation is surprisingly under-examined and under-discussed.

Sure, it's in the headlines and people acknowledge a number. We also take actions to control it while Wall Street encourages us to outrun it; spurring us on with their favorite investing + paper shuffling games.

But there’s very little public discourse about its true purpose and its 2^nd/3^rd order effects.

In contrast, we're led to believe inflation is normal; something that the government can control for the benefit of the economy. Some even believe it’s a natural phenomenon.

It's not. It's just a policy, rooted in Keynesian Economics and riddled with flaws and nonsense.

For starters, let's look at CPI (Consumer Price Index): the 'basket of goods' we use to measure & act on inflation. It's a complete scam. CPI doesn't include any of the things the average person actually desires, e.g. a house, a trip, the gym, a meal at a nice restaurant, etc.

It's also a moving target. They constantly change what's measured to hide the truth. At one moment, it will include the price of premium, Grade A beef. But once this beef becomes too expensive for the average consumer (i.e. a change in 'consumer preference'), it's replaced with low-grade beef. I mean... pure lunacy.

As for the idea behind inflation: they say we need it to spur consumption. Rather than save our money, we must spend it and get it moving through the economy to drive growth.

But when you get to the root of human behavior and incentives, you'll see the exact opposite is true.

In economic reality, we have to produce before we can consume. To produce, savings are required for meaningful & sound investment (e.g. not gambling on Game Stop, Dogecoin, or buying your 8th streaming service). Sound investment is what underpins entrepreneurship and money flowing to useful goods & services. It's this entrepreneurship that creates the true tail winds for growth.

If you come across someone stuck on inflation being necessary to spur investment & growth, you can challenge the idea in two ways.

First, just point to what historically became money on the free market: gold, the most inflation resistant commodity at the time. You can then point to the 1800s (when gold & silver were money). During this period, there was virtually no structural inflation.

This was a time of rapid innovation and massive productivity/growth, across the entire world. It was the time of rail roads, automobiles, electrification, and the harnessing of new types of energy. This was all upon a bedrock of harder money, one that people cherished and hoarded, sure, but deployed intentionally and strategically.

Second, consider the natural arrow of technology and progress. As just one example of many, the cost for a gigabyte of storage has dropped a thousand-fold. That value doesn’t just deflate away.

Rather, we’re able to use a thousand times more gigabytes. And with cheapness comes abundance, allowing us to consume more of the things we deem valuable.

So, when someone argues that an overly sound/hard money would hinder investment, they're double counting the idea, i.e. the argument negates itself.

That 'hoarded' unit of account only appreciates if technology is getting better over time. In other words, if technology & society are not advancing, and we remained stuck in the existing world, things aren’t getting cheaper and that unit of account is not buying us more stuff

But that's not how the world works. We are advancing and the invisible hand of technology propels us ever forward, constantly driving down price by lowering the marginal cost of production. But this progress only occurs due to investment.

So in theory, the only reason that unit of account would increases in value, and in turn, become worth saving/hoarding, is because investment would indeed be happening in the first place.

But this is not just theory. It's visible throughout history. Not just in the era of 1800's innovation & growth, but also during perhaps our most prolific era of human flourishing: The Renaissance (which was also on a sound money standard).

Now, this idea... this is what really prompted my study of money.

It's the idea of ‘reality distortion’, via a system that fights against the natural order of things and restricts our ability to reap the fruits of technological progress.

Meaning, in a natural world, technology is always boosting productivity and lowering prices. Or, per Jeff Booth's now famous quip: "prices always fall to the marginal cost of production."

These productivity gains should be flowing to society in the form of lower prices, making a good life more accessible to more people.

Yet, despite prices trying their damndest to fall (due to technology), we live in a debt-based system that simply won't allow it. It forces inflation and prices to rise to keep the mountains of debt from imploding.

Life could/should be getting better & cheaper, and people should be able to work less. Instead, life for most remains stagnant, and for many, it gets worse, forcing them to work more just to keep up.

The worst part? Rather than productivity gains flowing into society, they get concentrated into the hands of the fortunate few: those closest to the source of money creation. Which brings us to the less obvious problem with inflation & money printing...

The Less Obvious Problem

On the surface, money is printed with good intentions. It's our systems favorite safety blanket and the quickest & easiest way to avoid short term pain (so are drugs and ice cream...)

But behind the scenes, money printing is effectively two things: 1/ a mechanism for government to implicitly default on its debt, relying on inflation to push the debt burden onto the general public. And 2/ a reverse robin hood effect, moving wealth and purchasing power from the have nots to the haves.

These 'haves' include a host of beneficiaries who've parked themselves as close to the source of new money as possible, reaping massive benefits as a result. We're talking central bankers, politicians, big banks, wall street, monopolies, and anyone else the US government thinks deserves a bail out.

Why? Because they get access to freshly minted dollars first. They're able to use this money to acquire assets/capital before it enters into wider circulation and causes prices to rise.

As a result, the cost of the government defaulting on its debt is externalized onto society, and predominantly on to the middle & lower class. They don't own as many assets, so they don't get to ride the rising tail winds as things inflate. Asset prices rip upward, but their wages can't keep up. Hence, the widening wealth gap.

People seem to either avoid or ignore the topic. If you bring it up, people tend to suddenly see you adorned with a tin foil hat.

But consider the following quote from Part I of this series. This is from the very guy who created the economy theory behind economic intervention + inflation (Keynesian Economics):

"By a continuing process of inflation, Governments can confiscate, secretly and unobserved, an important part of the wealth of their citizens. By this method they not only confiscate, but they confiscate arbitrarily; and, while the process impoverishes many, it actually enriches some....." - John Maynard Keynes

This is otherwise known as the Cantillon Effect, in which those closest to the source of money creation benefit at the expense of the rest.

Some call this a form of shadow taxation. Other calls it theft.

Theft sounds harsh, and perhaps bombastic. But what else do you call it?

No one voted for this. No one complied. No one was forewarned or educated about the whole charade.

It's like joining a startup and being granted shares. But little do you know, there's this (mysterious) group with the ability to issue themselves new shares on a whim, diluting your ownership stake in the process. Would you join that startup?

That's effectively our system. It dilutes our time/energy, our private property, and uses the proceeds to pay off government debt, all while helping the rich get richer.

Meanwhile, for the average Joe/Jane, buying a house gets further out of reach, saving for a kids education is becoming futile, and basic groceries & gas blows up the budget.

Some macro evidence: between 1975 and 2018 in the US, $50T has moved from the bottom 90% to the Top 1%.

We're told that economic intervention and money printing is meant to help the lower/middle class. In reality, it does the opposite, creating all kinds of downstream problems. The most damaging is the effect on people’s sense of hope & purpose as they remain stuck on a treadmill, or worse, shot backwards into the wall.

Is this being done explicitly? By evil people twirling their mustaches with glee? Not necessarily. It's a result of the incentive structures in an inherently flawed system.

These incentives can longer be ignored. They cause theft to become the organizing principle of the economy. The result is a destruction of what should be an otherwise pure and noble game of human interaction; a game that should be positive sum, within a free market, in which we all deal with each other consensually, and every exchange has a bilateral benefit.

Rather, we're forced into a game in which the incentive is to print money and get as close to the stolen proceeds as possible, e.g. to own shares in the central bank (yes, this is a private, for profit institution), to become a bureaucrat,  join a large bank, or work on Wall Street (where wages to push around paper are astronomically higher than anywhere else, ironically, all to help people race against the very inflation that they help create with central banks… coincidence?).

These people then go on to waste or gamble with 'customer money' (aka the citizens). 

Government wastes it in too many ways to count, but to name a few: unnecessary warfare, mainstream media puppeteering, wokeism propaganda, geopolitical trade wars, and over (incompetent) regulation.

Hiding in the shadows of it all? Bureaucrats parked right next to, or worse, influencing the money spigot itself.  Exhibit A: Nancy Pelosi, with a $400k salary, obtaining a net worth over $170M. Exhibit B: Elizabeth Warren, with a similar salary, and who came into government with very little net worth to speak of. She’s now worth over $60M.

This is akin to letting professional athletes gamble on the outcome of their own games.

As for the banks, Wall Street, and the monopolies they support? They enjoy privatized gains for a few years and distribute fat winnings to private shareholders. And then when they mess up and incur losses, government bails them out and pushes those losses onto the public.

It's worth noting the inherent incentive for inflation within the banking system that the Fed props up.

Many big banks operate with between 10x - 25x leverage. So for every $100 they use for loans, they only hold $4 - $10 of equity capital. The other $90 - $96 they use comes from your deposits. These banks need inflation, as it increases the value of the collateral backing those loans. That's the banking game in a nutshell; a debt-based house of cards that requires fiat currency expansion to increase the nominal value of the collateral on their debt.

Every other business model in the world is accountable to their solvency. But governments, banks, and Wall St? Not the case. They can drive up the prices of their own assets, and then socialize losses onto the rest of society.

Hence, the growing angst (everything feels expensive), social unrest ('Occupy Wall Street'), and populism (a lower/middle class in despair + Trump).

And hence, the common quip: "fiat is the real Ponzi"... A loop that feeds on itself; enriching those at the top, at the expense of those near the bottom.

Now, it’s not lost on me that I'm glossing over many details, and that this is a complex and nuanced problem. There's all kinds of tomfoolery sitting atop this system and no single institution, group, or individual is to blame.

But if there's one thing that can be blamed & targeted, it's a flawed incentive structure. At the heart of this incentive structure is a flexible, centralized, opaque ledger of money; nothing more than a single node, 1990's database managed on-premises at the Federal Reserve.

The energy/effort required for monetary expansion? The stroke of a few keys: alt-Control P.

Perhaps we should consider a ledger/database for money that is: 1) inflexible, decentralized, and transparent, 2) has a real-world physical constraint to producing more, and 3) is easy to self-custody and hyper portable.

With these properties, our savings could be protected, our money could work for us rather than against us, and the incentive structure would be flipped on its head.

Not only would this diminish the money printer as a form of shadow tax, and a mechanism for implicit default on its debt, but the state would also be held more accountable to its citizens; if the state erodes people's money and private property, the features of self-custody + portability would empower them to vote with their feet.

The worst part of this conundrum? All the debt they're trying to pay down with our purchasing power... its already insolvent. All of it. There is no realistic way of paying it off. The only solution is to increase the money supply and keep trying to inflate it away.

The multi-hundred-trillion-dollar question... how long can this go on? Forever? Is infinite leverage a thing? 

Me thinks not… As the foundation wobbles, perhaps a parallel system is a good idea, and at the very least, a smart hedge or insurance policy.

We explore why in Part III...(see link here).

Hope you enjoyed, and if you found this enlightening, please subscribe and share with a friend or two :-)