Categories
Science Stanford

Bypassing the Leaf

For my entire life, I’ve understood the world through a simple, quiet equation: green plants take sunlight and air, and turn them into the stuff of life. It is a slow, terrestrial magic we all learn in grade school.

But lately, after listening to Professor Drew Endy at Stanford, I’ve been sitting with a curious yet exciting realization: that ancient equation is being rewritten.

Professor Endy champions a concept called electrobiosynthesis, or eBio. At its core, it represents the engineering of a parallel carbon cycle that operates independently of traditional photosynthesis.

The global industrial complex is approaching a transition point where our traditional reliance on extractive fossil fuels is being superseded by a regenerative, biological manufacturing paradigm.

For millennia, humanity has relied on the biological “middleman” of the plant to capture solar energy. But natural photosynthesis, for all its quiet beauty, is limited by severe biochemical constraints. Most commercial crops convert less than 1% of incident solar energy into usable biomass.

Electrobiosynthesis changes the math. By bypassing the plant entirely, we can utilize high-efficiency photovoltaics—which capture over 20% of the sun’s energy—to drive carbon fixation directly into the metabolic hubs of engineered microbes. This fixed carbon is transformed into organic molecules, serving as the feedstocks for high-value products like proteins and specialty chemicals.

In my own career, I’ve watched industries undergo profound, structural phase shifts. This really feels like another one of them. It seems that we are looking at a future where any molecule that can be encoded in DNA can be grown locally and on-demand. This fundamentally decouples manufacturing from centralized industrial nodes and fragile global supply chains.

The field appears to currently be in its “transistor moment,” moving from laboratory feasibility to industrial pilot plants. It signifies the ability to construct and sustain life-like processes without being restricted to the terrestrial lineage of photosynthesis.

Of course, with such foundational power comes the weight of unintended consequences. The ability to engineer life at this level brings severe biosecurity risks, and even the “Sputnik-like” strategic challenge of international competition in biotechnology. There are profound ethical dilemmas on the horizon, such as the creation of “mirror life”—organisms made from mirror-image biomolecules that might be invisible to natural ecosystems.

But the trajectory seems set. The vision described by Professor Endy—a world where we grow what we need, wherever we are, using only air and electricity—is no longer a distant science fiction. It is a nascent industrial reality. This future is being written not in sprawling factories, but in the microscopic architecture of the cell.

I’ve just now reading a deep research report on this whole area that I asked Google Gemini to create. It’s fascinating and I’ve discovered a whole new area (beyond AI) to explore further.

Categories
Business Creativity Space SpaceX

Test like you fly!

There’s a phrase in the SpaceX documentary that keeps coming back to me: “Test like you fly.” It sounds like a slogan. The kind of thing that gets painted on a factory wall and eventually stops meaning anything. But the more I sit with it, the more I think it’s actually a philosophy that reaches well beyond rocket engineering.

The video — a 25-minute documentary SpaceX released last week — is ostensibly about Starship Version 3. New ship, new booster, new engines, new pad, new test site. Everything rebuilt. And they’re not shy about framing it as a reset, not an upgrade. One description I read called it “a quiet violence in progress.” That phrase stopped me cold, because it’s exactly right. Progress that looks violent from the outside — all that fire and metal — but is somehow quiet in its inevitability.

What moved me watching it wasn’t the engines. It was the engineers. SpaceX put the people on camera: the ones running cryogenic pressure tests at 80 Kelvin, stress-testing tank structures at 70% proof, explaining their failures and their data with the flat affect of people who have made peace with how long hard things take. There’s something almost monastic about it. You choose a problem that will not yield easily. You accept that the work will outlast any individual sprint of enthusiasm. You go back to it anyway.

I keep thinking about that in the context of what we’re doing with AI — the other enormous, fast-moving project that I spend so much of my mental energy on. The development arc is different: iterative releases, weeks not years between jumps, demos that blur into deployment. But the same principle is buried in there somewhere. The best AI teams I read about aren’t the ones shipping the most polished demos. They’re the ones building infrastructure for failure — evals, red-teaming, structured feedback loops. Test like you fly.

The Raptor 3 engines now produce 280 metric tons of thrust each. Thirty-three of them on a Super Heavy booster means over 17 million pounds of liftoff force. I have no intuitive frame for that number. What I do have a frame for is what those numbers represent: three years of iteration on top of five years before that, on top of a theoretical foundation laid by people who didn’t live to see any of this. There’s a compounding in that which I find genuinely moving. Nobody built the Raptor 3 in isolation. It came from everything that broke before it.

The hardest part of the documentary isn’t the engineering. It’s the implicit acknowledgment of how much remains undone. No Starship has yet achieved full orbital velocity with both stages intact. In-space refueling is still untested. The thermal protection systems need more work. And yet — SpaceX talks about unmanned cargo missions to Mars before the end of this year like it’s on the roadmap, not the wish list. That sentence used to sound like marketing. Watching the footage, it doesn’t anymore.

I’m not sure what to do with that feeling exactly. It’s something between awe and vertigo. We’re living in a moment when the audacious has started to have quarterly milestones. When the impossible keeps showing up on timelines and then — bewilderingly, uncomfortably — meeting them.

Test like you fly. Fail with rigor. Build the thing you actually need, not the thing you could more easily explain.

I keep turning that over. There’s a post in there somewhere about writing, too — about the drafts nobody sees, the structural tests that fail, the versions that taught you the one that worked. But that’s for another day.

For now I’m just sitting with the footage of those 33 engines lighting up, and the quiet weight of how much went wrong before they could do that.

Categories
Books Curiosity Living

Working the Seams

This book highlight popped up in my morning Readwise feed recently:

“Fishermen work seams—seams between slow water and fast, between deep water and shallow, between sunlight and shadow. The eddies around rocks, the bubble lines along banks. That’s where the fish are.”

Neil King wrote it in American Ramble, his account of walking from Washington to New York. He was watching fishermen, not fishing himself, which maybe explains why it reads less like instruction and more like revelation. When you’re the observer, you have room to notice what the practitioner is too busy doing to say.

The word seams is doing something I can’t stop thinking about. A seam is a joining. It’s the place where two different things meet and, in meeting, create a third thing: the edge itself. Not slow water, not fast water, but the turbulent conversation between them. The fish aren’t in the slow water. They aren’t in the fast water. They’re in the argument.

I think most of the interesting things in life happen at seams.

The best conversations aren’t the ones where everyone agrees. They’re the ones where two people with genuinely different orientations are standing at the same edge, looking at the same water. The friction between the views creates something neither would reach alone.

The best writing isn’t the settled opinion, the fully-arrived-at conclusion. It’s the essay in the old sense — the attempt — where you can feel the writer at the seam of what they know and what they’re reaching toward. The bubble line between understanding and confusion. That’s where the reader is, too, if they’re lucky.

I notice this on my own blog sometimes. The posts that feel most alive to me aren’t the ones where I knew what I wanted to say before I started. They’re the ones where I began at a seam — between something I’d always believed and something that recently unsettled it — and wrote my way along the edge, not knowing which bank I’d end up on.

There’s a version of this that applies to attention itself.

I dwell on how I pay attention — when I’m reading, when I’m walking, when I’m in conversation. And I’ve noticed that my attention goes flat in the middle of things. Flat terrain. Constant depth. Unchanging light. I have to work to stay present when nothing is in transition.

But put me at a seam — a moment where the mood in a room is shifting, where a piece of music is about to resolve or refuse to resolve, where someone is on the verge of saying something they’ve been circling for an hour — and I’m completely there. Attention is predatory, maybe. It goes where the tension is.

Which is what the fish are doing, of course. The seam isn’t just a metaphor for where interesting things happen. It’s why interesting things happen there. The fast water sweeps food along; the slow water lets you hold your position; the seam between them is where you can eat without being eaten. The fish are solving a real problem. They’re just also, accidentally, living beautifully.

I wonder sometimes if this is what makes a good editor, or a good friend who reads your drafts. They find the seams — the places where you’ve unconsciously papered over a tension, smoothed the fast water into the slow, given the reader no place to be a fish. “Something’s off here,” they say, and what they mean is: you resolved this too quickly. Stay in the argument longer.

The eddies around rocks, the bubble lines along banks.

I want to be a better noticer of those. Not to resolve them. Just to work them.

Categories
Atomic Energy Nuclear Energy Science

The Traffic Light That Split the Atom

If you wandered past the Mathematical Society and kept going, you’d come to a pedestrian crossing on Southampton Row where it meets Russell Square in London’s Bloomsbury. On a humid morning in September 1933, something world-changing happened there.

It was Tuesday, September 12. A cool, drizzling, quintessentially English autumn day. Leo Szilard — a brilliant, restless Hungarian-Jewish physicist who had fled Nazi Germany earlier that year — stood waiting at the traffic light. He was irritated, as people often are when a red light holds them up on a gray morning. He had been thinking about Ernest Rutherford’s recent lecture, in which the great pioneer of nuclear physics had dismissed the idea of extracting usable energy from the atom as “moonshine.”

Szilard disagreed. And as the light turned green and he stepped off the curb, the thought arrived in a flash.

What if a single neutron struck a nucleus and caused it to split, releasing two neutrons? Those two could split two more nuclei, releasing four — then eight, sixteen, thirty-two. In a large enough mass of the right material, the process could sustain itself — a chain reaction — and liberate enormous amounts of energy.

He saw it all in that instant: the possibility of limitless power, and the shadow of a weapon unlike anything the world had ever known.

Szilard was not in a laboratory. He was not surrounded by colleagues or equipment. He was simply crossing a London street, a refugee with too much on his mind, when the future opened up in front of him.

He filed a patent within the year and had it kept secret by the British Admiralty. He spent the rest of his life in the aftermath of that crossing — working on the first controlled chain reaction in Chicago in 1942, then becoming one of the most tireless advocates against the use of the weapons he had foreseen. The man who imagined the chain reaction spent decades trying to break it.

The spot where it happened remains utterly ordinary. Buses and taxis still rumble through the intersection. Tourists hurry toward the British Museum. Students cross on their way to Russell Square. There is no plaque. Szilard himself, given how deeply pacifist he became, might not have wanted one.

That feels right. The moment wasn’t grand or ceremonial. It was the kind of quiet, internal shift that happens when a prepared mind meets an ordinary irritation at a traffic light.

The hinges of history are fragile things, and they don’t announce themselves. Enormous consequences — nuclear power, the atomic bomb, the Cold War, decades of arms-control efforts — all trace back to one man’s realization while crossing a rainy London street. And once a thought like that arrives, it doesn’t leave. Szilard carried his for the rest of his life. He understood, earlier than almost anyone, both the dazzling promise and the terrible cost of what he had imagined at that crossing.

I came to this story through Sebastian Mallaby’s The Infinity Machine. It stopped me cold on the page, the way the best historical details do — not because it was dramatic, but because it was so ordinary.

Next time you’re stuck at a pedestrian light on a humid morning, pause for a moment. The light will change. You’ll step forward. But you never really know what might change with you.

Categories
Chemicals Petroleum Semiconductors

The Invisible Layer Beneath the Chip

At the edge of a semiconductor fab, nothing looks dramatic.

No flames. No smoke. No sense of weight.

Just pipes, valves, and a silence so controlled it feels artificial.

It’s easy, standing there, to believe that oil—the old engine of the economy—has been replaced by something cleaner, lighter, more abstract. Software, maybe. Or data. The kinds of things that don’t spill.

But step a little closer, and the illusion breaks.

A modern fab is less like a factory and more like a chemistry experiment that never ends. Gases move through stainless steel arteries. Liquids are mixed, spun, deposited, stripped away. Surfaces are etched and re-etched until what remains is measured in atoms, not microns. The machines—Applied Materials, Lam Research—are precise, but they are not the story. The story is what flows through them.

Chemicals are doing the real work.

Not in bulk, the way oil once did. Not with force. But with specificity.

A barrel of oil is valuable because of its density—how much energy it contains. A liter of photoresist is valuable because of its selectivity—what it allows to exist and what it removes. One powers motion. The other defines structure.

Structure is where the modern economy hides its value.

A semiconductor is not impressive because of what it consumes. It’s impressive because of what it constrains. Billions of transistors, each one placed, shaped, and insulated with a chemical discipline that borders on obsession. The difference between a working chip and a useless one is often a contaminant you cannot see.

This is a different kind of industrialism.

The 20th century scaled by adding more—more fuel, more steel, more throughput. The 21st century scales by removing everything that shouldn’t be there. Purity is the limiting factor. Not how much you can move, but how precisely you can control.

From a distance, it can look like oil has become less important. The headlines have shifted. The glamour has moved on.

But the truth is more entangled.

Most of the chemicals inside a fab begin their lives as hydrocarbons. The solvents, the polymers, even some of the specialty gases—downstream of the same geological inheritance. Oil didn’t disappear. It changed roles. It moved from the foreground to the substrate.

The question, then, isn’t whether chemicals have replaced oil. It’s whether the economy has learned to express value differently.

Less in how much energy we can release. More in how carefully we can shape matter.

Semiconductors are the clearest example, but not the only one. Pharmaceuticals follow the same logic. Advanced materials, too. In each case, the breakthrough isn’t scale—it’s control. The ability to operate at the edge of what’s physically possible, and to do it repeatedly.

Which raises a quieter possibility.

That the defining resource of the next era isn’t oil, or even chemicals.

It’s precision.

And chemistry is simply the language we use to achieve it.

Categories
California Petroleum

The Last Tanker

There is a strange, quiet finality to the arrival of the New Corolla. It is a massive vessel, carrying two million barrels of crude—a literal, physical weight of energy—into the Port of Long Beach. It loaded up in Iraq on February 24th, just days before the world’s geopolitical plates shifted and the Strait of Hormuz effectively slammed shut.

By the time you read this, that oil will have been offloaded, refined, and moved into the capillaries of California’s infrastructure—into gas tanks, jet engines, and diesel generators.

And then, the silence begins.

California has long existed as an “energy island.” It is a geographic quirk that defines our modern life: we are disconnected from the domestic pipeline network that feeds the rest of the country. We don’t have the luxury of pulling from a pipeline in Texas or the Midwest. We are, by design, tethered to the horizon. We are dependent on the flow of tankers across the vast, deep blue of the Pacific.

For years, this worked. It was a invisible architecture of convenience. We consumed, and the tankers arrived with the metronomic precision of a clock. But the New Corolla is not just a delivery; it is a period at the end of a sentence. It represents the last of a supply chain that we assumed would be permanent.

When the analyst says, “all bets are off,” they aren’t just talking about prices at the pump or the logistical scrambling of refineries trying to source crude from Brazil or Guyana. They are describing the erosion of a certainty we didn’t realize we relied on. We have built a state—a massive, humming, technological engine—on the assumption that the world is a frictionless marketplace.

The crisis is not just about the supply of oil; it is the realization that we are fragile.

We look at our inventories, and we see them as a buffer. We are told they are “healthy,” but inventories are, by definition, a countdown. They are the water left in the glass after the tap has been turned off. We are now in the uncomfortable, interim phase where the supply lines are empty, and the new ones haven’t yet been built—or perhaps, cannot be built.

It is easy to look at this and see a political or economic failure. It is harder to see it as a human one. We have become experts at consuming the distant, while remaining strangers to the mechanics of that consumption. We have lived in the architecture of the “global everything,” and now, as the walls of that architecture contract, we are forced to look at the geometry of our own isolation.

The New Corolla will depart for distant waters. It will leave behind a void, and in that void, we will find out if our resilience is as robust as our rhetoric.

The future is only guaranteed for those who can afford to survive the present.

And for now, the present is a question of how much gasoline is left in the tank, how much jet fuel is available and how quickly we can learn to walk on our own.

Categories
Writing

The Unfinished Note

I’ve been sitting with a Susan Orlean line for a few days now, the way you sit with a splinter you can’t quite locate.

“Stories don’t need a ‘conclusion,’ a flourish of finality. It’s better to leave readers falling forward, tumbling through the piece and beyond it, finishing the tune in their heads.”

What strikes me isn’t the advice — plenty of writing teachers have said something like it — but the verb she chose. Tumbling. Not drifting. Not lingering. Tumbling. There’s a loss of control in that word, a small helpless momentum, the way you take one more step than you expected on a dark staircase and your body has to catch up to itself.

I’ve always been suspicious of endings that arrive wearing their own bow. You can feel them coming, those last paragraphs — the rhythm slows, the sentences get more declarative, the writer seems to straighten up and clear their throat. And then comes the lesson, the restatement, the turn toward uplift or hard-won wisdom. The piece explains what it was about. You close the browser tab and that’s the end of it.

But some pieces don’t end so much as they stop, at the right moment and the right angle, and something in you keeps moving. You find yourself thinking about them in the shower two days later. You’re not remembering the conclusion because there wasn’t one. You’re still inside the piece, finishing the tune, as Orlean says. The writer handed you the melody and walked off mid-phrase.

I think about this with music. Jazz, especially. The best solos don’t resolve — they suggest a resolution and then leave the air charged with it. Miles Davis understood that the note you don’t play is still a note. The silence after the phrase is part of the phrase.

I’m not sure I’ve ever actually written an ending this way. Most of my pieces come in for a landing; I can feel myself starting to circle and descend. Maybe that’s the real lesson in Orlean’s line — not a craft note about structure, but a challenge to trust the reader enough to leave the door ajar. To believe the piece was good enough that they’ll want to keep walking around inside it.

I’m still not sure I do.

Categories
AI Business

The Topography of a Face

I found myself staring at the physical geometry of a conversation the other day—not the words, but the topography of the faces delivering them.

Elad Gil recently shared a fascinating experiment during a conversation with Tim Ferriss. He’s been uploading photos of startup founders into AI models and asking the machines to predict if they’d be successful, purely based on their “micro-features.”

“Because if you think about it, we do this all the time when we meet people, right? We quickly try to create an assessment of that person, their personality, and what they’re like. There are all these micro-features—like, do you have crow’s feet by your eyes, which suggests that your smiles are genuine? […] So, I have this whole set of prompts that I’ve been messing around with, just for fun, around: ‘Can you extrapolate a person’s personality based off of a few images?'”

He notes the model breaks down the crow’s feet and the furrowed brows, extrapolating a personality from a static frame. It’s a parlor trick, perhaps. But it works because it holds a mirror to our oldest, most unexamined instinct.

We are all amateur phrenologists of the human face. We sit across a table, measure the crinkle of an eye or the tightness of a jaw, and we build a rapid, invisible architecture of trust or suspicion. Over decades of investing and making career choices, I’ve often leaned heavily on this silent language. I’ve backed founders because their intensity felt genuine, and I’ve passed on others because something in their posture felt misaligned.

But if I am brutally honest, that intuition has sometimes been a mask for my own blind spots. I’ve held on to failing investments for far too long because I trusted a reassuring smile. We like to think our gut instinct is a sophisticated instrument. Often, it is just a pattern-matching engine running on deeply flawed historical data.

Now, we are handing that very human habit over to a machine. We prompt the AI to become a “cold reader,” and it obliges, predicting who will be the quiet observer and who will deliver the dry wit.

The unsettling part isn’t that the machine might get it wrong. The unsettling part is that it might get it exactly right—by mimicking the very same rapid, superficial judgments we make every day, just at a terrifying scale.

We are teaching silicon to read the human code. The future will belong to those who realize the code was always written in our own biases.

Categories
Storytelling Writing

The Nerve of the Opening Line

For years I wrote first paragraphs that explained what I was about to say, which is a little like a joke that begins by describing how funny it is.

Susan Orlean has a better idea. In her book Joyride, she writes that a lede doesn’t need to preview the story or summarize what the rest of the piece will be about. What’s important is that it captivates readers and holds them fast to the page so they keep reading.

The conventional wisdom about ledes is that they exist to tell readers what they’re about to read. The billboard theory of the opening. Here is what this story is. Here is why it matters. Here is what you’ll find if you continue. The lede as table of contents, compressed.

Orlean is saying something stranger and more honest: the lede’s job is not to inform. It’s to hold the reader.

There’s a distinction there worth sitting with.

Informing a reader is a transaction — you transfer content, they receive it. Holding a reader is something else entirely. It’s closer to what a magician does in the first thirty seconds of a performance, or what a stranger does when they say something at a party that makes you turn and face them fully. You haven’t learned anything yet. You’ve just been made to stay.

The ledes that have held me longest tend to have almost nothing to do with the stories they open.

Joan Didion begins “The White Album” with a single sentence — “We tell ourselves stories in order to live” — that takes the entire essay to even partially fulfill.

Gay Talese opens his Frank Sinatra profile not with Sinatra’s voice or his legend but with a man going silent: “Frank Sinatra, holding a glass of bourbon in one hand and a cigarette in the other, stood in a dark corner of the bar between two attractive but fading blondes who sat waiting for him to say something. But he said nothing.”

Tracy Kidder opens The Soul of a New Machine not with computers but with a boat in a storm, Tom West awake for four straight nights while everyone else is seasick, the rest of the crew left wondering what on earth this man does for a living.

None of these ledes summarize. All of them hold.

What they share, I think, is a quality of disturbance. They’ve moved the ground slightly underfoot. Something is tilted.

Didion’s first sentence argues that we tell ourselves stories in order to live, and you feel the vertigo in it immediately — wait, is that true? Is that a good thing or a desperate thing?

Talese gives you a man diminished by illness and silence, and everything that follows is measured against that diminishment.

Kidder’s boat goes somewhere that prose about minicomputers wouldn’t, and by the time you’ve crossed that dark water with West, you’re already a different kind of reader than you were on page one.

I think about this when I try to write.

I grew up reading ledes the billboard way — I thought the first paragraph was a promise about what the reader would receive. And sometimes I still write them that way, which is to say I write them first and delete them later, because they’re stage fright disguised as generosity. Here is what I’m about to tell you really means please don’t leave before I find my footing.

The Orlean formulation — captivate, hold, keep reading — shifts the pressure off the writer’s anxiety and onto the reader’s experience. The question is no longer what do I need to tell them? The question is what will make them unable to leave?

That’s a harder question. It requires knowing something about what people can’t resist. Strangeness. Motion. A body in trouble. A door left open. The suggestion that someone knows something you don’t.

The best ledes I’ve ever written didn’t come first. They came after I’d already written the whole piece and finally understood what it was actually about — which turned out not to be the thing I thought it was about at the start. You can’t write the sentence that makes someone stay until you know what you’re asking them to stay for.

The lede isn’t a promise. It’s a wager. You’re betting that the reader will follow disturbance into the dark — and the only way to make that bet is to trust the disturbance yourself first. Most of us don’t. Most of us write the billboard because we’re afraid that if we don’t explain what’s coming, the reader will leave.

But the reader doesn’t leave because they’re confused. They leave because nothing reached out and held them.

The explanation never does that. The strangeness might.

Categories
AI Thinking Tools

Outsourcing Thinking but not Understanding

There’s a line mentioned in a recent discussion by Andrej Karpathy that I keep turning over: You can outsource your thinking but you can’t outsource your understanding.

It sounds like a warning. Maybe it is. But the more I sit with it, the more it feels like something older — a distinction philosophers have been trying to draw for centuries, suddenly made urgent by the fact that we now have a tool that makes outsourcing thinking almost frictionless.

Here’s what I notice when I use AI well: I get the answer, and I feel satisfied. There’s a small dopamine tick. Task closed. But if someone asks me an hour later to explain the reasoning, I often can’t. The thinking happened — somewhere — but not in me. I was a conduit. A confident one, too, which is the dangerous part.

This is different from looking something up. When I Google a fact and paste it into a document, I know I’m borrowing. The seam is visible. But when I ask an AI to reason through a problem with me, the output arrives in first person, in fluent prose that matches my own register, and something in my brain says I worked this out. The seam disappears. That’s new. That’s the thing we don’t yet have good instincts for.

Karpathy’s deeper point is about construction. He’s a builder by temperament — his mantra, which he traces to Feynman, is that if you can’t build it, you don’t understand it. What you can’t yet construct, you merely think you understand. There are always micro-gaps in your knowledge, invisible until you try to arrange the pieces yourself and find they don’t quite fit. The AI doesn’t change that equation. It just makes it easier to mistake the map for the territory — and to feel strangely proud of a map you didn’t draw.

Hesse understood this, in a different century and a different idiom. In Siddhartha, the young seeker travels to meet the Buddha himself — the most perfectly articulated wisdom in the world, delivered by the man who actually found it. Siddhartha listens, acknowledges that the teaching is flawless, internally consistent, the most complete account of liberation ever assembled. And then walks away. Not from arrogance, but from recognition: even the Illustrious One cannot hand you his liberation. The path was his. He walked it. That walking is not transferable, no matter how perfect the description of the destination. Received knowledge, however exquisite, is not the same as earned knowledge. The gap between them is exactly the size of your own unlived experience.

That’s the same argument, made across two and a half millennia. Feynman says you have to build it. Hesse says you have to live it. Karpathy says the AI can do neither for you.

He’s also made a related observation about educational video — that a lot of content on YouTube gives the appearance of learning but is really just entertainment, convenient for everyone involved. Nobody has to do the hard part. AI-assisted thinking has the same shape, just more intimate. You’re not passively watching — you’re actively typing, prompting, engaging. It feels like cognition. But engagement isn’t understanding. Typing a question is not the same as wrestling with it.

I don’t think the answer is to use AI less. That’s not Karpathy’s argument either — he’s spent the last year building a school premised on AI tutors expanding what people can learn. The lesson is about custody. When I hand a problem to an AI, I need to stay in the loop as a learner, not just as a reviewer. There’s a real difference between asking give me an answer and asking help me build the reasoning. The first outsources thinking. The second — if you insist on it, if you refuse to be a passenger — can still leave the understanding in you, where it belongs.

But insisting is the work. And the work is now easier to skip than it has ever been.

Understanding isn’t a product you receive. It’s a residue — what settles in you after genuine struggle, after the confusion and the dead ends and the small hard-won moments of clarity. Siddhartha couldn’t get it from the Buddha. You can’t get it from the AI. Karpathy’s line is a custody argument: the thinking can travel, but the understanding has to stay home.

What unsettles me is that we’re building tools that make the borrowing invisible — that dress outsourced reasoning in the first person, that let us feel like we’ve understood something we’ve only processed. Siddhartha at least knew he was walking away from the teaching. He felt the gap. We might not even notice ours.