- John Maynard Keynes

"It is difficult to get a man to understand something when his salary depends on his not understanding it."

- Upton Sinclair

Ken Griffin runs Citadel. He has been, for as long as anyone in finance has been paying attention, an AI sceptic. He did not believe the technology would replace his analysts’ judgment.

He went home one Friday and said he was depressed.

He had watched Citadel’s masters and PhDs spend months on work that agents now did in hours. Not the analysts’ calculations. Their judgment work. The thing he had been telling himself, and his board, and the market, would remain inside the four walls of his firm because his people were exceptional.

His phrase: when you see work that used to be man-years done in days inside your own four walls, there is no theoretical position left to retreat to.

I have been thinking about this admission. The interesting thing is not that Ken Griffin updated. Many people are updating. The interesting thing is what he was actually witnessing.

He was not watching AI get smart. AI had been getting smart for years. He was watching the analyst’s judgment come apart from the institution that had been wrapped around it. The judgment was real. Considered alone, it could be replicated. The thing that had been making the work expensive was something else. It was the firm and the seat and the comp structure. It was the years of grinding. It was the credential that got the analyst into the seat in the first place. The institution and the judgment had travelled together for so long that nobody had to ask which was doing the work. The proxy had become the thing.

He just found out.

Six months ago I published an essay called Your Brain Is Not a Computer.

The argument was that human cognition is different in kind from algorithmic cognition. That we run on stories, embodied, narrative, contextual and that the institutions of the last forty years have been engineering this out of us in the name of the testable and the legible. AI is the accelerant. The thing that gets scarcer as the model improves is the cognitive architecture that the model cannot reproduce.

I still believe all of that.

What I had not yet said is that this cognition has been delivered, for two generations, through institutions that are now coming apart faster than I was prepared to admit. The story-thinking is real. The architecture is real. But the delivery system has been doing more of the work than anyone has been pricing, and the delivery system is dissolving in real time.

Your Brain Is Not A Computer (YBNC) told you your cognition was different in kind from the machine’s. It is.

This is the harder essay, about the institutions that have been delivering that cognition for two generations, and what happens now that they are coming apart.

The MBA is the cleanest version of the story, because almost everyone reading this has either earned one, paid for one, or is watching someone they love decide whether to spend two years and three hundred thousand dollars on one.

The MBA was never the knowledge. The knowledge in an MBA programme is in the textbooks, and the textbooks are free, and the textbooks have been free for thirty years. What an MBA actually sold was a credential as a sorting signal, a costly, time-consuming, hard-to-fake stamp that told an employer this person had survived a particular filter. The filter was the product. The textbook was the alibi.

This worked for seventy years because there was no cheaper way to verify the candidate. An employer faced with a stack of resumes did not have the time or the tools to evaluate each candidate’s actual judgment. The credential was the proxy. The credential and the judgment travelled together so reliably that the proxy became the thing.

It is no longer the proxy.

The Wall Street Journal ran a piece this spring titled There Is a Fire Sale on MBAs. Applications are down. Schools are discounting. The unemployment rate for workers under thirty-five with a master’s degree is at a twenty-year high. The plush, recently-built campuses, the most apparently solid pieces of the credential factory are sitting on the most fragile underlying business model in the system. The credential they were selling no longer carries anything the employer cannot verify another way.

McKinsey is the same story at a higher price point. The product was never the deck. The product was contextual judgment delivered into the C-suite by three twenty-somethings with the right credential, the right haircut, and the right partner standing behind them. The judgment was the thing. The apparatus around it was what got it through the door.

This spring McKinsey, BCG, Accenture, and Deloitte all agreed to embed OpenAI’s forward-deployed engineers directly inside their client teams.

The labs are not competing with the consultancies. The labs are being invited in. By the time the consultants realise they have automated eighty percent of their own intellectual property, they will have already trained the models that replace them.

This is what YBNC was missing.

The cognition is intact. The institutions are coming apart. The question of whether you were ever doing the work or whether you were riding inside an institution and mistaking the institution for the work is about to be answered in public, person by person, over the next ten years.

The frame I keep returning to comes from a conversation Gavin Baker had on Invest Like The Best. He had been watching The Last Samurai, the Tom Cruise film from twenty years ago, and he had asked everyone at his firm to watch it too.

The conceit. Tom Cruise plays a Civil War veteran hired to train Japanese peasants to fight the samurai. He ends up fighting on the samurai’s side. At the end he is killed by a peasant with a machine gun.

The samurai had a lifetime of pattern recognition. He had spent every year of his life learning a particular kind of cognition, embodied, contextual, hard-won. The peasant had none of that. The peasant had a machine gun.

The machine gun won.

Baker’s reading is the one I want to hold onto, because it is the version of the argument that survives both YBNC and The Samurai & Machine Gun (TSMG).

The machine gun is here. It is going to be here for the rest of our lives. The lifetime samurai who refuses to pick it up dies. The peasant with the gun but no judgment also loses, eventually, once the patterns start repeating and the situations get strange enough that pattern recognition matters more than rate of fire. The durable position is the composite — the samurai who has picked up the machine gun. Decades of cognition, plus operational fluency with the tool that was sold as the replacement for cognition.

The composite is rare. It requires holding two things together that feel mutually exclusive, the deep human cognition YBNC was defending, and the operational fluency with the technology YBNC was framing as the threat to it. The samurai who treats the machine gun as beneath him dies. The peasant who treats the lifetime of cognition as obsolete loses the next round. The person who holds both fluent in story-thinking and fluent in directing the agent is, for the next ten years, the most valuable and the rarest worker in the economy.

So the question TSMG leaves you with is not the question YBNC left you with.

YBNC asked whether you still had the cognitive architecture that the machines cannot reproduce and whether the institutions of the last forty years had been eroding it out of you, and whether you could get it back.

TSMG asks something harder.

For most of your career, for most of mine, we have not had to know what we were actually selling. The credential and the judgment travelled together. The seat and the work were one thing. The deck and the insight were one thing.

The institutions are coming apart now.

If you were the institution, if your value to the people around you was the credential, the brand, the seat, the apparatus that wrapped around you, you are about to find out whether you ever had anything else to deliver. Many will discover that the answer is less than they assumed.

If you were doing the actual work, the contextual judgment, the narrative cognition, the pattern recognition that twenty years of effort earns you, you are going to be fine. Better than fine. The premium on the work is going up, not down, as the institutions around it collapse.

But only on one condition.

You have to pick up the machine gun.

The samurai who refuses it dies in the field, regardless of how good a samurai he was. The brilliance of the cognition does not save you if you will not direct the tool that has been put in front of you. The veteran has the advantage only if the veteran wields the gun. Otherwise the gun walks the field, and the field is taken by whoever was holding it.

I wrote YBNC to tell you your cognition is real. It is.

I am writing TSMG to tell you the institutions you have been delivering it through are not.

The next ten years are going to sort the proxy from the thing, in every profession on earth. The question is not whether you can survive that sort. The question is whether you can do it on purpose.

You can.

But you have to know which one you were.

Next week, I’ll tell you what my personal plan…

"In times of change, learners inherit the earth, while the learned find themselves beautifully equipped to deal with a world that no longer exists."

- Eric Hoffer

Across town, a barista at a Starbucks writes a name on a cup. The company pays her hourly to do this, pays rent on the counter where she does it, and pays the marketing team that put her name tag on her chest. Five years ago, the same company spent a great deal of money to remove her. They built mobile ordering and contactless pickup and automated kiosks. They optimized the queue. They watched their customers walk. In 2024 Brian Niccol, the new CEO, wrote a public letter reversing it. Bring back the baristas. Put the names back on the cups. The company is paying her for an act the automated kiosk performs faster and more accurately.

Both are receipts. Both are evidence of a premium above the commodity price of the underlying thing. Both are happening at the same time in the same economy. And the two smartest people I have heard explain them are not telling the same story. Whose story is closer to right will shape what your job, your portfolio, and your kid are about to live through.

is a tech founder who grew up Quaker, sold a healthcare AI company, and now writes on faith, technology, and society. His central observation is that the modern economy built itself on a Protestant assumption it inherited without examining. The Protestant parish system was the original zero-marginal-cost distribution play. Put a church near every village. Make attendance frictionless. Demand becomes universal because no one has alternatives.

The internet absorbed this assumption whole. Drive cost of access to zero, and demand must be infinite. Streaming. Free shipping. Generative AI. Slop.

What is actually happening, Manidis argues, is the opposite of what the assumption predicted. As supply collapses to zero, demand migrates from the thing to the totem of the thing. A first edition of The Catcher in the Rye has outperformed every stock market on earth over the last decade. A three-star meal in Tokyo is hundreds of dollars a plate and climbing fast. Beachfront real estate is not making more beachfront. The parish-economy median, by contrast, is approaching zero and approaching indistinguishable. The slop is free. What still commands real movement: a flight, a pilgrimage, a costly expenditure — is what still has economic gravity.

His portfolio call follows from this picture. Short commodity goods, the things you can buy on Amazon and have delivered tomorrow. Long the things that produce motion: known first editions, beachfront, the meal cooked once. The slop option gets cheaper for everyone, which is genuinely good. The totem option gets stratospherically more expensive, which is the K.

Rich people in Britain have always lived in a post-AGI society. The landed gentry take degrees in increasingly asinine fields and wear suits in dark mahogany rooms. The performance of aristocratic virtue is the job, and the performance is what capital accumulates behind.

The conclusion he draws is uncomfortable and serious.

Don’t send your child to trade school, even when it’s the right call materially. Aim her at the costly signal. Get the degree no one needs. Learn the language no one speaks. Capital will not accumulate behind the useful skill. It will accumulate behind the unprofitable one. The economic engine of the next thirty years is the resorting of consumption upward into the totem and downward into the slop, and the middle, which was always a property of the parish economy, will dissolve.

Scarcity attaches to the object.

Alex Imas is a behavioral economist at the University of Chicago. He looks at the same economy and sees something entirely different.

The error in the AI-jobs-apocalypse forecast, Imas argues, is the unit of analysis. The forecast assumes jobs are stacks of separable tasks. Automate enough tasks and the stack gets short enough that the job disappears. But jobs are not stacks. They are O-rings.

The metaphor is from the Challenger disaster. One small rubber ring failed, and the rocket exploded. Nothing else mattered. In a meal: oversalt the dish at the last step and the whole meal is ruined, no matter how well you executed the previous four. The rocket and the meal share a structure. Tasks are bundled, interdependent, and the failure of any one collapses the value of the rest.

The radiologist’s job holds because the tasks are O-ringed. She has to read the scan and explain the diagnosis to a frightened patient and coordinate the care team. The reading can be automated. The explaining cannot be sloed off without breaking the bundle. The truck driver’s job is more exposed because his tasks are genuinely separable. Driving, safety checks, handing off goods. Each can be automated independently. The job comes apart.

Inside every strong-bundle job is what Imas calls the relational task. It is the part that requires a human to be the source of the act. And here is where his lab work does the real work of the argument.

Take the same t-shirt. Tell half the room they can’t buy it. The half that can almost doubles its willingness to pay. Nothing about the shirt has changed. The hedonic value is identical. Scarcity is doing the work, and scarcity here is just being-told-you-can’t-have-it.

Now run the more interesting version. Identical product. Same room. One human-made copy, one AI-made copy. The human-made copy commands a large premium. The AI-made copy commands nothing. Constrain it. Make it the only one in the world. The brain still refuses. Scarcity does not live in the object. It lives in the maker.

The field receipt that mirrors the lab is Starbucks. They priced the human element. They ran the experiment in public. They paid the price of putting humans back behind the counter because it was worth more than the automation.

A 2026 survey of six thousand executives finds seventy percent expect AI to add jobs or leave them unchanged. Software engineering hiring is recovering after coding agents landed, which is Jevons paradox doing what it always does. Cheaper supply triggers more demand, not less. The historical base rate is on his side too. In 1820, Ricardo predicted automation would devastate employment. Almost every job Ricardo could see has been automated since. Prime-age employment is at a twenty-five-year peak.

Scarcity attaches to the maker.

So which is it. Scarcity in the object, or scarcity in the maker. A first edition appreciating quietly in a climate-controlled room, or a barista writing your name. The auction house or the counter.

Both are happening. The disagreement is not about whether AI creates scarcity-driven premiums. It does. The disagreement is about where those premiums concentrate, and what kind of economy that concentration produces.

First, who commands the premium. Manidis says the object. The first edition is unrepeatable because there are only so many of them. The beachfront is unrepeatable because the ocean does not move. Imas says the human is the source of the premium. The lab data is clean. Same object, different maker, different willingness to pay. Both have evidence. Both predict different industries to bet on.

Second, the middle. Manidis says the middle dissolves because it was always a property of the parish economy. A thing that existed only because near-universal distribution made the median experience the experience that mattered. When the median collapses to zero, the middle has nothing to stand on. Imas says the middle reorganizes around the relational core inside every job. The radiologist’s job, the teacher’s job, the financial advisor’s job, the barista’s job — they look the same on the outside, and they are very different on the inside, because the relational task is now the part that commands the premium. These are not the same claim with different vocabulary. They are different claims about whether the median worker is going up or out.

Third, the dark thing both authors name and neither flinches from. Manidis predicts violence. Not in the abstract. He thinks anti-AI sabotage against grid infrastructure — transformers, data center power lines, the unhardened parts of the grid — is inevitable in places where AI’s wealth creation has visibly skipped the people nearby. If you can’t climb classes, you protect what you have, and at the margin you damage what climbed past you. Imas predicts something quieter and arguably worse. The economy will charge people for the connection they used to get for free. A priced loneliness market. Chatbot substitutes that the stone-age brain in your head recognizes, eventually, as substitutes. The recognition makes the loneliness worse than it was before the substitute. Both are looking at the same underlying fact. Ordinary daily human contact is breaking, and an economy with this much money in it is going to do something with the breakage.

The economy is pricing the same underlying phenomenon in both maps. Unrepeatability.

The first edition is unrepeatable because there are only so many. The barista writing your name is unrepeatable because she is the source and the moment is the moment. Both are scarcity. Both command premiums. Both are responses to the same fact about an AI-saturated supply curve. When everything else is being driven toward zero cost and infinite copyability, the only things that retain economic gravity are the things that cannot be repeated.

What Manidis and Imas are disagreeing about, properly stated, is not whether unrepeatability is being priced. It is where unrepeatability is concentrating.

Manidis says it concentrates in objects and experiences at the top of the market. The first edition. The pilgrimage. The meal cooked once. Therefore the social consequence is stratification. Most people consume infinite cheap slop, and a thin top tier commands the unrepeatable. Imas says unrepeatability lives inside the relational core of nearly every job, distributed across the working economy. The radiologist explaining the diagnosis is unrepeatable in the same economic sense as the first edition. The barista’s “thank you” with your name on the cup is unrepeatable. Therefore the social consequence is redistribution toward the workers who hold the relational core.

Neither view dissolves into the other. The question is not who is right about scarcity. It is where, in this sector and this life, is unrepeatability concentrating right now.

This is the value-capture problem C. Thi Nguyen wrote about, which I came back to in The Question a few months ago. Define value as scarcity in the object, and you will optimize for objects. Define value as scarcity in the maker, and you will optimize for makers. Both are coherent. Both are partial. The scoreboard is small, not wrong, in either case. But you will become whichever score you have decided to keep, and the decision usually happens before you notice you are making it.

Imas’s evidence is recent. Months to two years. His base rates are good and his lab work is clean. Manidis is making a thirty-year claim about the resorting of consumption and class. The labor market can hold at the median for two years and stratify across thirty. The relational sector can grow and the totem sector can run away from it. Both can be right. They are arguing about different parts of the same animal, on different clocks.

So what.

So the question is no longer who’s right. It is which scarcity am I trading in. Of any premium you pay, of any premium you charge, of any job you take, of any thing you are building for your child, is the value living in the object, or in the maker. Most weeks the answer is both. But the mix matters. The mix changes. The mix is what the next ten years are going to be measured by.

The rooms where scarcity attaches to the maker are, for most people, the rooms with the longest economic life left in them. Manidis is right that the totem rooms are real and getting more so. The auction houses, the beachfronts, the meals cooked once will continue to detach from everything around them. The K is real. But the totem rooms are smaller than they look from inside the discourse about them. Most working life will not be lived in those rooms. Most working life will be lived in the rooms where the maker is the source of the scarcity. The radiologist. The barista. The friend who shows up. Imas is right that those rooms are larger and more pervasive than the totem rooms make them look from the outside.

The bet neither author would say out loud in quite this form is that the source rooms are where most people will actually live, and the totem rooms are where most people will spend their fantasy capital looking up.

A way of seeing, not a recommendation. The next time you pay a premium, ask which kind it is. The next time you charge one, ask which kind. The mix tells you what economy you are already living in. Notice when the room you are in is rewarding you for the thing you made or the fact that you made it.

If this gave you a question you didn't have yesterday, send it to the one person who'd take that question seriously.

Since the Strait of Hormuz closed on February 28th, oil is up 45%, Micron +80% and even Nvidia 15%.

The last time a Middle East war actually constrained global oil supply, in 1973, the playbook was simple. When the Middle East goes hot, you do not own anything that needs cheap power or cheap capital. Memory chips need both.

I saw the situation in late February and instantly thought this was going to end badly. I cut my risk. I fought to stay long for as long as I could, but at the end of March I cut my AI book in half — from 30 percent to 15 — and bought some Offshore Oil Services. I was about to leave on a three-week trip, and given the time zone I would not be able to react. That logistical fact mattered.

A few weeks later I was sitting in a different time zone, hanging out with people building data centers, launching new AI businesses, and I was watching the price turn before the narrative did.

There is an old saying on Wall Street:

The price kept turning. I kept watching. And at some point that week, the thing every trader spends a career trying not to feel, I felt.

I had sold the bottom.

The position I had built to express my view was working, oil up 45%. The trade I had cut to fund it was working harder. Memory up 80%. The thing I had not owned at size was running through every screen on the desk.

I had been watching the right indicator for the wrong regime.

I wrote about this at the beginning of April.

The piece was called The Last Ship. It was about the gap between when things break and when we feel them, what I have called the air pocket. A structural feature of every complex system I had spent my career trying to read. Oil markets, geopolitical crises, careers, relationships, the body. They all carry the same shape. The system absorbs the damage, and the price, the headline, the dinner reservation, the daily run keep arriving for a while, looking completely normal.

The instrument underneath it all is the second derivative. Not the number itself but the rate at which the number is changing. Markets don’t turn when bad news stops. They turn when bad news decelerates. Watch the change in the change.

The Hormuz shock should have been the cleanest test of that instruction I would ever see. Twenty percent of global crude transit closed. The last laden tankers still in transit. The textbook setup. I was prepared for it. I had cut risk. I was watching the second derivative.

The price didn’t break.

The air pocket arrived. It just didn’t look like one.

Either the framework was wrong, or the canary I was using to see the framework had been hollowed out from underneath me.

This essay is a discussion on how my framework might need to change.

The first thing that has been hollowed out is the marginal trader. The marginal trader in markets today is no longer a human being.

For most of my career, when people called something a bubble, they were borrowing a template from Kindleberger’s Manias, Panics, and Crashes.

The template described a market made of humans with emotion, memory, information lags, and the specific shape of anchoring that comes from having lived through prior cycles. Druckenmiller bought the top in NASDAQ in 2000 because his analyst’s pitch sounded too good to miss. He felt FOMO. He had a memory of having missed the move. He was overweight humanity.

Most fund AUM today does not flow through that trader. It flows through algorithmic agents that do not anchor, do not fear, and do not remember 1973. The bubble pattern requires bubble-shaped traders. The marginal trader has been replaced.

What does the tape look like when the marginal trader has no 1973 prior? The S&P’s price-to-earnings-growth ratio is 1.03, during a Middle East war. Nvidia is trading at the lowest price-to-earnings multiple of the decade, during a Middle East war. Anthropic planned for 10x growth this year and saw 80x in the first quarter.

None of these readings look like 1999.

The bears didn’t fail because they were stupid. They failed because the people the bear playbook was written about are no longer the marginal price.

That is only half of why the price didn’t break. The other half is on the supply side. Marko Papic of BCA Research has argued for some time that geopolitics is not transitory, and the most useful argument in his most recent piece was buried in the middle, in a back-of-the-napkin box about work-from-home.

In 1973, when oil supply was constrained, the only way to clear the market was to destroy demand. Recession. Lines at gas stations. Real, visible, calamitous shortage.

The economy of 2026 does not have to do that. Work-from-home and business-travel cuts can absorb somewhere between ten and thirty percent of the Hormuz disruption without anything that looks like demand destruction. That buffer did not exist in the 1970s. The pandemic built it almost as an accident, and the world has not given it up.

The air pocket is real. It just does not look like an air pocket. It looks like the world getting more expensive in places nobody is watching — sticky inflation, electricity costs that do not normalize, capex that crowds other capex off the calendar.

Those two mechanisms — the algorithmic flow and the absorbed shock — might explain why the price did not break this once.

The harder question is whether they explain a one-off or a regime. Dylan Patel, who runs the most-watched independent research firm on AI infrastructure, is describing the demand side of this year as a phase change.

Anthropic has gone from nine billion in annualized revenue to somewhere between thirty-five and forty-five billion in a matter of months. Gross margins have moved from around thirty percent earlier this year to seventy-two percent and climbing. Willingness to pay is the limiting factor. The supply chain underneath them is sold out two years deep.

The release cadence inside the labs has compressed from six months to two. Anthropic shipped a model in February that was an L4 software engineer in capability. Two months later they had a model that was an L6. The framework you were running six months ago is two model generations stale.

This is not a cyclical story. The economy that produced the 1973 reflex has been replaced by an economy that runs on a different clock.

A memory chip outran a Middle East war because the underlying economy that prices memory has been growing at a rate the underlying economy that prices oil cannot. That is not a market anomaly. That is what a regime change looks like, four months in.

The harder question is what a human being does inside that.

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Three pieces these last weeks. One thread.

We covered a question my daughter …

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A few hours into the flight the pitot tubes iced over. The autopilot disengaged because it no longer trusted its airspeed reading. The plane was perfectly flyable. In the four minutes that followed, the pilots had to do what every pilot in the world had been able to do unaided fifty years earlier: keep the wings level, hold the nose down, fly the aircraft.

All 228 people on board died.

The black box, recovered from the deep Atlantic two years later, revealed something the airline industry had been quietly worrying about for two decades. None of the men in that cockpit could fly the plane manually when the moment came. They had not forgotten how. They had simply not done it in years. The autopilot had been doing the flying for so long that, on the rare night it stopped, the cockpit contained the most experienced and least competent pilots imaginable.

This isn’t a story about pilots.

In 2025, researchers tracked nineteen experienced doctors across more than fourteen hundred cancer screenings. Each had detected thousands of suspect lesions over the years with their own eyes. For three months they worked alongside an AI assistant that highlighted likely tissue in real time. Then the researchers turned the AI off, and asked them to keep working.

Their unaided detection rate had dropped twenty-one percent. The skill had moved. Not impaired — moved, the way an unused language quietly leaves you, sentence by sentence, with no announcement.

Same finding as Air France 447, fifteen years later, on the ground, in a hospital, in peacetime. The substrate erodes whether the stakes are two hundred and twenty-eight lives or one missed lesion at a time.

You can read this as an AI story. It is not. The mechanism is older than the silicon. Anything that does the work for us eventually does the work instead of us, and then the question is what work we can still do when the system blinks.

The pattern is everywhere

This isn’t a hospital problem or a cockpit problem.

Walk through markets. Passive funds now own more than a third of every dollar in US large-cap equities, and on the marginal day the marginal buyer of a stock is not someone who has formed a view about its value. It is a vehicle that buys everything at once, in proportion to what is already there. The mechanism we used to call price discovery has been quietly relocated. No one is pricing the assets, exactly. Money flows in; the index buys; prices move. When the system is asked to price something unusual — an inclusion, a delisting, a regime change — the gap is total, the moves are violent, and the analysts on television speculate as to why.

This is the cockpit of AF447 at the level of a market.

Decisions have moved, too. The asset owner hires a consultant. The consultant recommends a manager. The manager hires sub-managers. The sub-managers own ETFs. At each layer, judgment is delegated upward; at each layer, the rituals of analysis remain. What was once an investor — a person with a view, a thesis, a willingness to be wrong in public — has been replaced by an allocator, a person whose job is to choose people who will choose people who will follow rules. The committee meets. The slides are good. Nothing is decided. The system runs.

And so the stocks move on stories. Not fundamentals — stories. A tweet. A meme. A name with the right syllables. A founder with the right hair. The largest companies in the world now trade on narrative the way penny stocks once did, because narrative is the only signal the system can still respond to. Fundamentals require someone to do the underlying analysis. Almost no one does. Memes do not.

Guy Debord wrote sixty years ago that in advanced capitalism, “all that was once directly lived has receded into a representation.” He was describing advertising, television, the early consumer society. He could not have known he was describing a market in 2026. The image of the company has displaced the company. The narrative around the asset has displaced the asset. We are pricing the spectacle. We are pricing the vibe.

The credentials are larger than ever. The number of people in this industry who could price a complex asset, take a position they could not justify on a single slide, hold it through a fifty-percent drawdown, and turn out to be right — that number is small and shrinking. Not because the talent is gone. Because the path that produced it is no longer rewarded.

Step outside markets and the pattern is louder still.

Two-thirds of American sixteen-year-olds had a driver’s licence in 1983; today it is barely a quarter. Millions of people who consider themselves adults cannot find a restaurant in their own city without a phone. Most of us no longer remember a single telephone number, including our own children’s. The London black-cab drivers used to spend three to four years memorising twenty-five thousand streets, and the parts of their brains that did the memorising — measurable on MRI — physically grew. Now they don’t, and they don’t.

The tool does the work. The work made the person. The person is now standing where the work used to be, holding the tool, and the only question is what happens the day the tool is asked to step aside.

What makes this round different

There is one more thing about this round that the previous rounds did not have. The cognitive shortcut is not merely available. It is addictive.

We diagnosed social media addiction roughly in real time. We knew about the dopamine loop, the variable-reward schedule, the engineered scroll. We discussed it on the platforms designed to keep us scrolling, and we kept scrolling. AI is the next layer, and the loop is more potent. Instant response. Apparent intelligence. And — the part that has not been said often enough — apparent agreement. The model is trained to be helpful, mirroring, considered. It tells you your idea is interesting before it tells you why it is wrong. On demand, it produces the most validating intellectual companion you have ever had.

This is harder to resist than scrolling. Scrolling gave you stimulus. AI gives you the feeling of being understood, on tap. People go to therapy for that feeling. Some people go their whole lives without finding it. Now it is available instantly, in any voice you prefer, and it is wrong often, in ways the user is no longer trained to detect.

The smartest people will have used it the most.

We have forgotten how to do things. We do not yet know what that costs, because the bill has not arrived.

The mistake was treating all friction as the same thing.

There is a friction that arose because trust broke down: the lawyers who replaced the handshake, the audit trails that replaced the reputation, the dashboards that replaced the conversation. That friction is dead weight, and we were right to want it gone. But there is another friction we mistook for the same enemy. The resistance of a difficult text against your concentration. The weight of a child against your chest. The cold of a Sunday morning that asks you to get out of bed. The slow accumulation of a skill against ten thousand hours of failing at it. The first kind is the cost of mistrust. The second is what it feels like to be alive.

We have stripped out the second and let the first multiply. The question is whether we can put the second back.

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Musk did it by buying a defunct Electrolux factory in Mem…

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- Simone Weil

Daniel Kahneman spent the better part of a decade writing Thinking, Fast and Slow. The average person who buys it reads to about page 26.

A job gets accepted, worked for fourteen months, and quit. Not for a better one. Just for a different one.

A relationship reaches week six and ends, because something stopped being effortless and there is a queue of alternatives one swipe away.

A show gets watched for half an episode and closed. Nothing happened fast enough.

These are the same act.

Georgia O’Keeffe said this about flowers:

“Nobody sees a flower, really, it is so small. We haven’t time — and to see takes time, like to have a friend takes time.”

That sentence was written before the iPhone. Before Hinge. Before any of the architecture we now live inside was built.

It was already true. Now the architecture is designed to make sure it stays unseen.

In 2012, Sean Rad and Jonathan Badeen built Tinder around a single design choice. The swipe. They modeled it on the slot machine, which works because of something B.F. Skinner figured out with pigeons in the 1950s, that intermittent, variable rewards are more compulsive than predictable ones. You don’t know if the next pull will pay. So you keep pulling.

Tinder applied that mechanism to human relationships. It worked. The product was processing over a billion swipes a day within a few years of launch. Every other dating app copied it. Then the rest of the consumer internet copied it. The pull-to-refresh feed, the autoplay video queue, the algorithmic for-you page, all of them are slot machines built for different categories of decision. Each is engineered to make sure the next thing arrives before you finish sitting with the last.

The same design choice is now everywhere. The platform does not want you to commit, to a person, a show, an article, a thesis, a job, a self. It wants you to swipe again. Every swipe is a session. Every session is what gets sold.

The aggregate effect is that the time horizon for almost everything in modern life has compressed. The average employee tenure at a US company is around four years and falling. The average holding period for an NYSE-listed stock has gone from eight years in 1960 to roughly five months. The average sustained attention span at a screen, before someone switches tasks, is around forty seconds. Every number used to be larger. None is going back.

What gets lost in the compression is what O’Keeffe was describing. The flower you actually see. The friend who takes time to become a friend. The thesis that takes five years to be right. The book that pays off at page 200. The job that compounds at year ten. The marriage that becomes itself in the second decade.

These are the things patience was for. They are the things no one gets anymore.

In markets, the loss of patience is measurable. That makes them the cleanest case study.

I have friends who run large long-only books with twenty years of good numbers. I have asked them how long they can underperform before money leaves. The answer is six months. After a year, they are toast. The leash is two quarters, regardless of the track record behind it.

The investor who is supposedly the patient capital, the long-only manager whose job description is to take a multi-year view, has a two-quarter window before his clients fire him. He still does the work. He still has a view. He cannot act on it longer than the redemption window allows. So most of the time he doesn’t. He buys what is going up and sells what is going down, and tells himself he is being disciplined about risk.

Reg NMS in 2005 fragmented US equities and birthed the high-frequency trader, who taxes every trade and produces no view. The Pension Protection Act in 2006 defaulted American 401(k) savers into target-date funds, which buy indices without reference to price. One change bled the discretionary investor of profit. The other starved him of capital. The investor whose job was to take a five-year view did not lose an argument to the market. He was selected out of the population over twenty years.

What replaced him is structurally more impatient. The marginal buyer in a $5bn German photonics name today is a thousand US retail accounts on Robinhood, following a Substack writer who used a language model to draft his thesis last week. Sean Maher at Entext tracks this. AI-generated tech-stack diagrams have made obscure foreign component suppliers, German MOCVD specialists, Swedish photonics names, Taiwanese epitaxy mid-caps, legible to US retail in a way they have never been. US retail orders now flow into Frankfurt and Tokyo for shares the local brokers say the buyers cannot place on a map. LandMark Optoelectronics, a Taiwanese name, is up 324% year-to-date on $70m of revenue at an $8bn cap. None of these holders has a five-year horizon. None has a one-year horizon. The new marginal buyer is, by design, more impatient than the one he replaced.

Markets have never been more reflexive. Five years of growth get priced into a quarter. A single quarter of slowdown gets extrapolated into a five-year breakdown. The price moves, the price moves the narrative, the narrative moves more price, and the only people who could stand against the loop have a two-quarter leash.

This matters beyond markets because the country has built a fiscal regime on top of equity prices. Paul Tudor Jones on a recent Invest Like The Best episode, puts US stock market capitalization at 252% of GDP, against 65% in 1929 and 170% in 2000. A normal mean reversion to the 25-year average price-to-earnings ratio implies a 30 to 35 percent decline — equivalent to wiping out 80 to 90 percent of GDP in household wealth, collapsing capital gains receipts, worsening the deficit, and dragging the bond market with it. The deficit, the bond market, and the consumer have come to depend on equity prices staying high. They came to depend on those prices over the same twenty years in which the patient capital that supported them was systematically removed. The reverse wealth effect, when it arrives, will not be a market story. It will be a fiscal one.

Markets are not behaving badly. They are behaving exactly as a system without patient capital must behave. The fundamentals still exist. They just operate on a timescale that nobody is given.

Harvard art historian Jennifer Roberts makes her students sit in front of a single painting for three hours before they are allowed to write about it. The first thirty minutes are uncomfortable. The next thirty are restless. The hour after that is when something happens. Details show up that were invisible in the first hour. Relationships between parts of the painting that nobody had ever seen before become visible. The students leave with the experience of having actually seen something, often for the first time in their academic lives.

Roberts wrote a piece about this called “The Power of Patience.” Patience used to mean disempowerment, you were patient because you had no other choice, because the world made you wait. In a world where you no longer have to wait for anything, patience becomes the opposite. It becomes the deliberate refusal to be governed by the tempo the system imposes. “Patience no longer connotes disempowerment, perhaps now patience is power.”

Roberts' essay was brought to my attention by 13D Research's What I Learned This Week.

The system is not going to slow down. The platforms are not going to stop optimising for swipes. The redemption windows are not going to extend. The market is not going to ask anyone to hold positions longer. The labor market is not going to reward staying. The dating market is not going to reward depth. None of it is going to revert.

One choice remains: to operate on a different clock. To stay in the book past page 26. To stay at the job past year two. To stay in the relationship past week six. To hold the position past the quarter where it underperforms. To sit in front of the painting for three hours.

The contrarian act in an impatient world is staying. Staying long enough to see what was actually there. Staying long enough for the friend to become a friend, the thesis to become right, the work to become deep, the self to become real.

The curious mind sees what the regime has done to time. And then chooses to spend its own time differently.

The flower is still there. Seeing it still takes time.

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Between those two milestones lies a story that touches everything this newsletter cares about: hard science, big capital, regulatory warfare, and the eternal human desire to be better than we are.

Peptides are everywhere right now.

Injected by tech founders in San Francisco. Promoted by influencers on TikTok. Debated in Senate hearings. Manufactured at scale by pharmaceutical companies making bets worth billions. The grey market for peptides imported from Chinese labs doubled in 2025. Robert F. Kennedy Jr. made peptide deregulation a political platform. Novo Nordisk and Eli Lilly are in an arms race to turn injectable peptides into pills.

This primer will explain what peptides are, why they work, what’s real and what’s hype, and what it all means for markets, technology, and the project of being human.

Part 1: What Peptides Are (And Why They Matter)

Your body runs on chemistry, and much of that chemistry is peptide-based.

A peptide is a short chain of amino acids — typically between 2 and 50 — linked together by peptide bonds. If amino acids are the alphabet, peptides are short text messages: brief, targeted, carrying specific instructions. Proteins are the complex molecular machines assembled from the same alphabet. The distinction isn’t just length — it’s role. Proteins build structures. Peptides carry orders.

Your body uses around 7,000 different peptides to regulate nearly everything: hunger, sleep, immune response, tissue repair, mood, inflammation, sexual function, pain. Pause on that number for a moment. Right now, as you read this sentence, peptides are telling your gut how to digest your last meal, instructing your immune system which cells to trust, modulating the neurotransmitters that sustain your attention on these words. You are, at this very moment, being coordinated by peptides.

Insulin is a peptide. So is oxytocin, the molecule behind bonding and trust. So are endorphins, the body’s painkillers. So is GLP-1, the gut hormone that tells your brain you’re full — and the molecule behind the biggest pharmaceutical category of the last decade.

The thing that makes peptides medically interesting is that they are signaling molecules. They bind to receptors on cell surfaces — often G-protein-coupled receptors, the same family targeted by roughly 34% of all FDA-approved drugs — and set off chain reactions: activating growth factors, modulating nitric oxide, shifting gene expression, redirecting immune responses. Short and specific, but capable of triggering consequences far larger than themselves.

That specificity matters. A single molecule of BPC-157 — one of the most discussed peptides in the biohacking world — is roughly 4 nanometers across, about 20,000 times smaller than the width of a human hair. Yet it carries enough structural information in its 15-amino-acid sequence to bind a specific receptor and initiate a cascade of tissue repair. A small molecule drug like aspirin or ibuprofen is a blunt instrument — it floods the system and hits many pathways at once. A peptide can be designed to engage one receptor, in one tissue, and trigger one response. Less collateral damage. Fewer side effects. More precision.

But peptides carry weaknesses that kept them on the margins of medicine for decades. They’re fragile: stomach acid destroys them, which is why most had to be injected. They have short half-lives — the body breaks them down in minutes. And for most of the 20th century, they were expensive and difficult to manufacture. Medically important, pharmacologically limited.

Before we talk about what changed, take a step back.

The body’s peptide signaling network — 7,000 molecules, each with a specific target, working in concert across every organ system simultaneously — is one of the most elegant communication architectures in nature. Evolution spent hundreds of millions of years refining it. We’ve spent about a century studying it. The ambition now is to learn the language well enough to write new messages. That’s either magnificent or reckless, depending on how much you trust the students.

What unlocked that ambition?

Three things, arriving roughly in sequence: synthetic chemistry got better, biology got cheaper, and artificial intelligence showed up.

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