TL;DR: You can’t plan your way to serendipity. But you can shape the surface area where it lands. Luck has a formula – and every platform you use daily is working to shrink one of its variables to zero.

We were dogsitting a Rottweiler named Juno in suburban Brisbane. I’d baked scones because the flour package had a recipe on the back and there were chocolate chips in the pantry. I made enough for 20 people.

TMT (my then girlfriend, now fiancée, for the uninitiated) walked the scone surplus next door – the neighbor, Greg, had been mowing parts of our lawn unprompted, because Australians are like that. She came back five minutes later: “Julián, we’re invited for dinner. At their house. In 30 minutes.”

Their dinner guests had cancelled last-minute. The food was already prepped. Greg’s wife was Chinese, they’d met in Hong Kong where he’d worked in finance – and the house confirmed it. Pool. Porsche. The works. Their son was visiting. He’d made 48-hour braised pork with apple-mango sauce. Three courses. The kind of meal that makes you look down at your chocolate chip scones and reconsider your entire contribution to society. Anyway… we showed up and left with a second dinner invitation.

No planning would have produced any of it.

In 2010, Jason Roberts coined a term that stuck: Luck Surface Area.

His formula: L = D × T

Luck equals Doing times Telling.

Build something and make sure people know about it. That’s it.

Some percentage of those people will take action you never predicted – hire you, fund you, introduce you to someone who changes everything. The mechanism is serendipitous. The conditions that enable it are not.

But Roberts' formula is missing a variable.

The Shape Problem

D × T gives you the size of your luck surface area. It doesn’t say anything about the shape.

Two people, both high on Doing, both high on Telling. One does the same things in the same places with the same people, month after month. The other keeps moving – geographically, intellectually, socially.

The first person’s luck surface area is a narrow rectangle. The second person’s is a wide square. Same area. Radically different perimeter.

Roberts’ formula needs a third variable: R

For randomness exposure – the degree to which you put yourself in situations your past behavior can’t predict.

L = D × T × R

The Compression Machine

Every platform you use daily is working to shrink R to zero.

Your feed shows you what you already like. Recommendations reinforce what you already know. The social graph calculates who you already agree with. Spotify gives you “Discover Weekly,” which is really “Confirm Weekly.”

The attention economy is a randomness-elimination engine. Its job is to reduce surprise, increase predictability, and keep you inside a behavioral corridor narrow enough to monetize.

The result: your luck surface area compresses into a line. Infinite depth, zero width. The world’s foremost expert in your own echo chamber.

The algorithm can give you relevance. It can’t give you surprise.

The Settling Paradox

Two years of nomad living taught me this: travel is a brute-force R multiplier. The scone story wasn’t unusual. It was Cheeeewwsday (Tuesday for the uninitiated).

Two years will soon turn into three. I’m getting married this summer – and then we’re fucking off to Australia by the end of the year. No city picked. No car. No dog (yet). The backpack stays.

The conventional sequence says: marry, settle, build. But that treats R as something you graduate from, when really it’s a variable you manage. The nomad life caps D – your context resets every few weeks. Settling caps R – your context calcifies.

The question isn’t which one wins. It’s how long you can run both variables high before physics intervenes.

For me right now, that means refusing the false binary. Getting married without picking a postcode. Writing publicly to people I’ll never meet instead of journaling privately. Picking up the phone when the conversation could just be a text. Saying yes to the dinner invitation even when I’d rather stay in. Especially when I’d rather stay in.

Randomness maintenance as a lifestyle, not a strategy.

The Shape of Luck

Roberts was right. Doing and Telling are the foundation. But shape matters as much as size.

The algorithm wants to give you a line: efficient, predictable, monetizable.

Luck doesn’t live on lines.

When Juno’s owners came home, we told them about Greg – the dinners, the wine, the braised pork, the whole thing.

Her response: “Greg? The house to our right? They’ve never had us over for dinner.”

She’d lived next door for years. We were there for a month.

Same neighborhood. Same proximity. Different surface area.

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TL;DR: Everyone’s debating whether AI will take your job. Almost nobody’s asking whether AI can feed itself. For 45 years, the West has answered “What is GDP for?” with “whatever markets decide” – but the AI buildout demands energy, water, and rare earths at scales that expose a fracture between the financial ledger and the material one.

The reckoning won’t come from regulation, but from the periodic table.

My trusted bakery charges 2.20€ for a croissant now. When I was a kid, the equivalent pastry was a rounding error.

The croissant is the true golden ratio. The most honest inflation indicator on the planet. Forget CPI. Count your pastries.

What if the croissant problem isn’t just monetary? What if we’ve been measuring the wrong thing entirely?

A recent conversation on The Great Simplification cracked this open for me. In 90 minutes, two guests laid out a picture most of the finance world won’t look at.

The short version: the AI economy isn’t a cloud, but a metabolism.

Two Sets of Books

Every economy keeps two sets of books. The one your broker shows you, and the one that actually matters.

• There’s the financial ledger: Bloomberg, GDP reports, your brokerage app. Prices, returns, vibes.

• Then there’s the material ledger: Tons of copper. Liters of water. Megawatt-hours. Kilograms of dysprosium. (I had to learn to spell that this week, you’re welcome.)

Ledger #2 doesn’t care about your DCF model. It doesn’t negotiate. It just asks: do you have the stuff, or don’t you?

For 45 years, the West has balanced one book and shredded the other. “Markets will work it out.” GDP goes up, therefore we’re fine. The financial ledger became the map and the territory. We forgot there was ground underneath.

, a private investor who’s spent four decades mapping East-West supply chains, puts it sharper than I can: “if you haven’t got materiality built in, your paper-on-paper economy eventually destroys your currency and your entire system.”

The same argument I made in Everything is a Ponzi Scheme – just from the currency side rather than the commodity side.

The financial illusion: your portfolio is going up, but your money is going down.

The material illusion: you think you’re building the future, but you don’t own the ingredients.

The Heaviest Metabolism

We talk about AI like it’s weightless. Digital. A question goes in, an answer comes out. Magic.

Then you look at the electricity.

Meta’s planned facility in Louisiana will consume more than twice the electricity of New Orleans. The buildout is global, and every rack in every data center is a small mining operation’s worth of refined metals, assembled.

This isn’t software eating the world. This is software demanding the world feed it – at a pace that makes the green energy transition look like a light snack.

Tindale called it “probably the heaviest metabolism in the industrial system.” It snuck up on us because the cloud metaphor is such a good anaesthetic.

Nobody panics about a cloud.

But a cloud that can’t get its parts? That panics.

The Golden Screw

During COVID, Tindale couldn’t drive his car for nearly 12 months. One part. Unavailable. Everything else worked fine. Didn’t matter.

He calls this the “golden screw” problem: in a complex system, one missing component breaks the whole machine. The more complex the system, the more screws it hides.

AI’s supply chain is full of them. And almost every one runs through the same country.

China doesn’t just mine rare earths. It refines them. It controls the off-take contracts. Even when the mine sits in Australia or Canada, the ore ships to Chinese refineries because the West doesn’t have processing capacity and can’t build it profitably under its own rules. Canada killed a copper refinery because the ESG cost alone hit 9% of capital; Western Australia canceled another because it simply wasn’t profitable.

We’re not losing a trade war. We’re forfeiting one.

China is willing to produce at a loss. Indefinitely. The goal isn’t profit, but control. Meanwhile, Western investors want 20-30% returns, regulators add cost, and communities block refineries over arsenic.

Michael Every, global strategist at Rabobank (and overall British big brain), put it bluntly: wars are won with bullets, not profits. And you can’t build the bullets if someone else controls the metal.

This is why roughly half my portfolio is in AI infrastructure. Not the models. Not the apps. The substrate: power, land, permits. The unglamorous plumbing that has to exist before a single model gets trained. I’d rather bet on atoms than abstractions. The financial ledger says the AI trade is crowded. The material ledger says it hasn’t even started.

The Vertical Trap

This is where the spreadsheet hits the species.

Ask an economist about rare earth supply chains, and they’ll talk about price signals. Ask a general about climate modeling and watch the subject change. Everyone’s an expert. Nobody sees the board.

We’ve spent decades building vertical specializations – each one deeper, narrower, more credentialed – and never once integrated them horizontally. The economist doesn’t talk to the geologist. The geologist doesn’t talk to the general. None of them talk to each other because their jobs depend on not understanding each other’s domains.

Every articulated this better than I’ve seen anywhere: “a narrow-boundary argument will almost always win a debate against a wide-boundary perspective.”

Complexity loses every debate it enters. “Markets will sort it out” wins the room.

“Yes, but it depends on material constraints, energy access, demographics, and who controls the refining” gets a polite nod and a “we’ll get back to you.”

The Wrong Game

For 45 years, the West has answered the GDP question with: “whatever markets decide.” Efficient allocation. Comparative advantage. Let the invisible hand sort it out.

Great strategy… unless the other team isn’t playing that game. Unless they’re using state capitalism to wall up every choke point while you’re still reading Adam Smith and hoping the price mechanism will fix a geological bottleneck.

The West built an atomized, hyper-efficient system that excels at exactly one thing: consumption. We sit on the couch, watch Netflix, and expect the world to deliver stuff because we’re Western. (Every’s words, not mine.)

So what is AI for?

If the answer is “replacing 80% of white-collar jobs in 18 months,” congratulations – you’ve launched the worst marketing campaign in history.

Telling everyone they’re about to become redundant before you’ve proven the technology works at enterprise scale. Bold.

But there’s a better answer. Feed a single system the commodity flows, the defense budgets, the water tables, and the shipping manifests – all at once. Not to predict the future. Just to see the present clearly for the first time. AI as the thing that finally connects the verticals. Not a consumer gimmick, but a lens.

The irony is that building the lens requires the very materials we can’t secure.

(Who says the universe doesn’t have a sense of humor?)

Renaissance Man & Feudal Man

Michael Every made a point near the end that’s been rattling around my skull since.

What we need, he said, isn’t just the intellectually broad thinker who can see across disciplines. We need Renaissance Man and Feudal Man. People who understand systems theory and know how to grow a field of vegetables. The philosopher who can hew wood and carry water.

And then, with perfect comic timing: “I increasingly think most of our population is already feudal man. We just don’t know it yet.”

Tindale’s response was better: “We haven’t forgotten. Look at our ancestors. Look at how many people had to die for us to get here. They knew all that stuff. So it can’t be that hard to learn.”

Between those two lines is a whole philosophy of the next 20 years. We’re going to need people who can read a balance sheet and can a jar of tomatoes. The average MBA program teaches neither. The average trade school teaches one.

And we have maybe one generation to teach people how to think before AI does the thinking for them. After that, the question isn’t whether the tool works.

It’s whether anyone left knows how to check.

Grow Something

After 90 minutes of supply-chain warfare, geopolitical chess, and existential resource constraints, Tindale closed with this:

“Be kind to yourself. You can’t predict what’s gonna happen. So take yourself out of the future and bring yourself to the present. Walk among the trees. Grow some vegetables.”

He grows food. He builds things. He cans goods and tells his kids to act like zoologists studying their own species: humans have specific needs, specific inputs, and you ignore them at your own expense.

I wasn’t expecting tenderness from a man who can map the world’s rare earth choke points from memory. But there it was.

The greatest philosophy was written in hard times. The worst economics was done in good times.

The biggest threat to AI isn’t regulation. It isn’t the alignment problem.

It’s the periodic table. And you can’t lobby the periodic table.

Inspired by Craig Tindale, Michael Every & Nate Hagens on The Great Simplification. Listen to it.

On the weight of climate and what it teaches: Cold Introspection

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Frequently Asked Questions

What does “atoms vs abstractions” mean?

It’s the idea that the digital economy – AI, software, finance – runs on a physical substrate it mostly ignores. “Abstractions” are the models, the code, the financial instruments. “Atoms” are the copper, lithium, rare earths, water, and electricity that make all of it possible. When you bet on technology without securing the materials, you’re building on sand.

What is the two-ledger problem?

Every economy runs two sets of books. The financial ledger tracks prices, GDP, and returns – the numbers on your brokerage app. The material ledger tracks physical inputs: tons of copper, liters of water, megawatt-hours. For 45 years, the West optimized the financial ledger and largely ignored the material one. The AI buildout is forcing a reckoning because you can’t train a model without electricity, and you can’t generate electricity without materials someone else controls.

How much energy does AI actually use?

A lot more than the “cloud” metaphor suggests. The IEA projects data center electricity demand could approach 945 TWh by 2030 – roughly Japan’s entire consumption. Meta’s planned facility in Louisiana alone will consume more than twice the electricity of New Orleans. Each GPU server rack is a small mining operation’s worth of refined metals, assembled and powered continuously. The heaviest metabolism in the industrial system, as investor Craig Tindale put it.

Why does China control rare earth supply chains?

Refining, not mining. Even when ore comes from Australia or Canada, it ships to Chinese refineries because the West lacks processing capacity and can’t build it profitably under current regulatory frameworks. China produces at a loss indefinitely because the goal is strategic control, not profit. Western investors want 20-30% returns. China wants leverage.

What is the “golden screw” problem?

In a complex system, one missing component breaks the whole machine. Craig Tindale couldn’t drive his car for nearly 12 months during COVID because of a single unavailable part. Everything else worked. Didn’t matter. AI’s supply chain has these single points of failure everywhere, and most run through China’s refining infrastructure.

What is GDP actually for?

That’s what the article asks. For 45 years, the West’s answer has been “whatever markets decide” - price signals and comparative advantage. The problem: that assumes everyone is playing the same game. State capitalism doesn’t optimize for market efficiency. It optimizes for strategic control. GDP that measures consumption without tracking whether you own the means of production is a number that flatters you right up until it can’t.

Last updated: May 2026.

TL;DR: I typed an objection to something stupid at work. Clear, professional, correct. Then I thought about the politics, the performance review, the chain of screaming. I deleted the email. The stupid thing got approved. The Greeks had a word for what I lost in that moment.

It was 2019, a job I’ve since left, a meeting I haven’t.

Someone three levels above me had proposed something stupid. Not malicious, just optimization-brained in a way that would create months of downstream problems. I knew it. Two other people in the room knew it. I could see it in their faces.

I typed the objection. Clear, professional, correct. My finger hovered over send.

Then I thought about the politics. The capital I’d spend. The performance review in three months. It probably wasn’t even his idea – just passed down through the chain of screaming from above. The decision was already made and I’d just be the guy who made the meeting awkward.

I deleted the email. The stupid thing got approved. The downstream problems happened. I was right, and it didn’t matter, because I never said anything.

Not anger – I wasn’t wronged. Not regret exactly. More like a small death.

The Greeks had a word for what I lost in that moment.

Thumos

Plato divided the soul into three parts: reason (the head), appetite (the stomach), and thumos (the chest).

Thumos gets translated as “spiritedness” – but that sounds too gentle. It’s the fire in your chest. The seat of righteous anger. The drive for will, honor, and recognition. The part of you that refuses to be managed.

Thumos is what Achilles had too much of and most corpo drones have too little of.

You know you’ve lost it when you type the objection, then delete it. When you nod in meetings at things you don’t believe. When your choices become predictable to algorithms and you can’t remember the last time you risked anything that mattered.

You’ve been conditioned to accept it.

The Managed Life

Bureaucracies, credentials, corporate hierarchies – none of this is new. What’s new is the cage got smarter.

It’s not just a bureaucrat across a desk anymore. Recommendation algorithms predict your preferences before you have them. AI systems evaluate your resume in milliseconds. Performance management software quantifies your existence into KPIs. The old systems suppressed thumos through friction – paperwork, gatekeepers, slow processes you could occasionally rage against. A war of attrition.

The new systems suppress it through convenience. They optimize you so smoothly you don’t notice you’re being optimized. The path of least resistance is increasingly the only path visible.

The output of a thumos-dead culture has a name: slop. AI-generated content that sounds like everyone and no one, art that’s technically competent and spiritually empty – nutrient-free filler designed to pass through systems, not to mean anything. Slop is what you produce when thumos dies.

You can automate everything except the part of you that refuses automation.

Maybe this is Cope

I quit the optimization game. Left the career, sold the stuff, travelled the world, and now I’m collecting unemployment while writing essays about Greek philosophy. Of course I want to believe thumos is the scarce resource and compliance is the trap. It justifies every choice I’ve made.

So when I tell you the Managed Life is a slow death, you should know: I have been promoted to customer.

Maybe the optimizers are right. Maybe the people who never felt the heat in their chest are happier than the guy who burned it down and called it philosophy.

The Stoics would say so. They’d call thumos attachment – bondage to external recognition, the opposite of wisdom. The sage doesn’t send the email or delete it. He doesn’t care either way.

I’d rather be attached and alive than detached and optimized. Stoicism isn’t for me.

Nietzsche had a name for the alternative: Letzter Mensch. The Last Man. Comfortable, safe, optimized, and spiritually dead. No struggle, no aspiration beyond the next consumption cycle. “We have invented happiness,” says the Last Man – and blinks.

Fukuyama took the concept further: liberal democracy would triumph, the Last Man would inherit the earth – not through conquest but through comfort, the slow extinction of anything worth fighting for.

We’re building him at scale. Every friction removed, every choice predicted, every path smoothed until there’s nothing left to push against.

Thumos needs resistance. It’s a muscle that atrophies without use. Spend a decade nodding and following the algorithm-approved path, and you don’t just suppress the spiritedness.

You lose it.

The Test

Anyone can romanticize the dramatic exit. The ship-burning moment. The resignation letter that goes viral. That’s not thumos. That’s theater.

The real test is just another chewwssday. The accumulation of tiny choices that either keep the heat alive or slowly, imperceptibly, let it die.

You lose thumos in a thousand micro-surrenders, each one rational, each one safe, until one day you realize the fire is out and you can’t remember when it happened.

The heat in your chest is not a bug. It’s not “emotional volatility” that HR should help you optimize away. It’s the last thing the algorithms can’t reach.

And the next time you’re hovering over that email, finger on delete – maybe don’t.

Introducing: the Router Brain as the cognitive version of thumos-death: ⬇️

Plus, what work looks like when thumos is the scarce resource: ⬇️

More ancient philosophy, you say? Here’s another Greek framework applied to modern life: ⬇️

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TL;DR: Smart people optimize for being right. Rich people optimize for being believed. The market doesn’t reward truth – it rewards conviction backed by narrative force. This is a structural problem, not a motivational one. And I’m not exempt.

We all know "The Guy.” 👇

He graduated top of his class. He speaks three languages. He reads academic papers on weekends and corrects people’s grammar in group chats.

He can solve a Rubik’s Cube blindfolded, but he makes $80K a year working for a guy who thinks “EBITDA” is a Greek island.

The last time I listened to “The Guy,” he spent an hour explaining why Elon Musk is fundamentally irrational. The thesis was sound. The logic was flawless. The conclusion was obvious: the market is broken, and idiots are winning.

I nodded along. Then I checked Musk’s net worth. $500+ billion.

His analysis was perfect. His bank account was not.

That’s the trap. Smart people confuse “being right” with “getting paid.”

The Academic Game vs. The Market Game

In school, you get an A for being correct. You fail for being wrong. Simple. So “smart” people spend their entire lives optimizing for accuracy. They are terrified of being wrong. They overanalyze. They wait for perfect information.

The market is not a test. The market rewards direction, not precision.

Wealth creation is probabilistic courage – the ability to be early, look stupid for a while, and then be right when it matters.

The midwit curve shows the trap in action: low knowledge produces high confidence (you don’t see the problems), medium knowledge produces low confidence (you see ALL the problems), and high knowledge produces calibrated confidence (you know which problems actually matter).

The guy in the middle has just enough knowledge to see every possible failure mode, but not enough wisdom to know which ones matter. He’s frozen. The expert on the right has looped back to “fuck it, let’s go” – but now it’s strategic simplification, not ignorance.

The people in the middle are busy setting SMART goals, building productive daily routines, and wondering why discipline isn’t making them rich.

I built an interactive quiz. Find out where you fall on the bell curve: midwit.huliwood.com

Intelligence without conviction is just expensive self-sabotage.

Linear Logic vs. Geometric Payoffs

Smart people love fairness. Work an hour, get paid $50. Get a degree, get a promotion. Input equals output.

This is the Fairness Fallacy – the belief that the world is a meritocracy where effort compounds linearly. It doesn’t.

Wealth follows power laws. It relies on leverage, network effects, and compounding belief.

The quant understands the math perfectly and works for a salary. The founder understands the narrative perfectly and owns the equity. The quant is smarter. The founder is richer. Because the founder understands that money is captured belief, not just captured value.

Smart people are addicted to prestige – peer validation, the A, the peer review. Rich people are addicted to profit – market validation, the asset, the liquidity event.

The Burden of Seeing Too Much

“The problem with the world is that the intelligent people are full of doubts, while the stupid ones are full of confidence.” ― Charles Bukowski

The smarter you are, the more reasons you can find to not do something. What if the market crashes? What if I’m wrong about the timing? What if there’s a variable I haven’t considered?

Intelligence lets you simulate failure in high definition – every way something might go wrong, before you even start. Useful for avoiding catastrophe. Also a cage.

Meanwhile, the guy who can barely spell “synergy” launches a SaaS product with a landing page he built in Canva. He doesn’t know about CAC/LTV ratios. He doesn’t know he’s supposed to fail. So he doesn’t.

By the time the smart person has finished their competitor analysis, the idiot has already launched, failed, pivoted, and found product-market fit.

Reflexivity: Bending Reality

The most brutal meta-truth: smart people try to describe reality. Rich people try to bend it.

In finance, this is called reflexivity – a term coined by George Soros, who made billions betting on it. Your belief about the world actually changes the world.

Tesla: the smart person says it’s overvalued, the P/E ratio is insane, traditional automakers will crush them – short this. The reflexive person says: I will tell a story about the future of energy so compelling that everyone buys the stock, which gives me the capital to build the factories, which makes the story true.

Same logic powers crypto, where Bitcoin has value because people believe it has value, which makes more people believe it has value. Smart people scream that it’s not backed by anything. Neither is the US Dollar, or gold, or God – what’s your point?

Smart people confuse fragility with intelligence. They avoid risk. They want a steady paycheck, a clear career path, a guarantee.

But wealth is just captured volatility. You cannot get outsized returns without outsized variance.

Now, if you’ll excuse me, I need to go convince someone that my braindumps are worth subscribing to – not because the writing is objectively better than everyone else’s, but because I’ve constructed a narrative that makes it feel essential.

See? I’m learning.

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TL;DR: Europe's pension systems were designed when workers died at 67. Now they retire at 60 and live to 85. The pyramid has inverted, and the young are funding a contract they'll never benefit from. Saturn is eating his children – and they're picking up the tab.

Last Xmas I Gave You My Unsolicited Rant

I spent Christmas in Spain. Think hors d’oeuvres, jamón platters, turrón/cava and we all know him, we all love him: drunk uncle (let’s call him tío pepe). It didn’t take long for him to launch into his annual sermon about “la juventud de hoy.”

Kids these days. Don’t want to work. Too comfortable.

Tío pepe is 63. He retired at 59 on a full pension. He bought his apartment in 1987 for €25,000. It’s worth €380,000 now. He’s never refreshed a job portal, never been ghosted by a recruiter, never been told his application was rejected because they found someone with ten years of experience willing to work for entry-level pay.

I smiled, poured more wine, and let it go.

Arguing with a man who bought his economic security for the price of a used car isn’t a debate. It’s archaeology.

Speaking of fun, this reminded me of a chart: Spanish public spending by age. In essence, a tidal wave flowing toward pensions while education and youth services flatlined.

Someone put it next to Goya’s Saturn Devouring His Son.

They’re the same picture.

The Demographic Ponzi

I’ve written before about how markets are Ponzi schemes – confidence games that work as long as new money flows in. The European pension system runs on the same logic, except the “investors” aren’t recruited. They’re born.

For decades, this worked. Wide base of workers, narrow apex of retirees. Many paying in, few drawing out.

That pyramid looks more and more like a mushroom every year. Exhibit A:

Spain, for instance, is heading toward a 1:1 ratio – one worker funding one retiree. The birth rate has collapsed to 1.16 children per woman, lowest in the EU. The workers aren’t being born. But the retirees keep retiring (which is why they’re fueling GDP with immigration, but that’s a separate story).

In 2025, Spanish pensions rose 2.8%, indexed to inflation. Starting salaries for young employees? Flat.

We’re protecting the past from inflation while letting the future rot. I call this the elephant chart. Once you see it, you can’t unsee it:

Spanish public spending by age. The blue tsunami on the right? Pensions:

Madafaking Bismarck

Spain isn’t special. It’s just further along the curve.

Germany’s pension system – the Umlagerentensystem – was designed by Bismarck in 1889. It assumed workers would die shortly after retirement, not live another 25 years. It assumed population growth, not collapse. It assumed the future would always have more workers than the past had retirees.

Every assumption was wrong.

Germany is heading toward 1.5 workers per retiree, Italy is worse, and France set Paris on fire over raising the retirement age by two years. The pay-as-you-go system is designed for a demographic reality that no longer exists.

And here’s the thing I have to admit: the generation that built these systems probably did so in good faith. Bismarck wasn’t scheming to bankrupt millennials. The assumptions were reasonable at the time. But a system designed with good intentions and wrong assumptions still produces the same extraction as one designed with bad intentions. The downstream doesn’t care about the upstream’s motives.

The Silver Vote

Why doesn’t anyone fix this?

Because 10 million pensioners vote in Spain alone. They vote in every election, like their lives depend on it – because economically, their lives do depend on it.

The young? Busy. Disillusioned. Abroad.

A politician who proposes pension reform loses the next election. So no one proposes it. The budget becomes a funnel: taxes flow in from the young, transfers flow out to the old. Everyone knows the young will never see the same return. No one says it out loud.

The dead hand of the past has a vote in Spain – and it’s not letting go.

The Drawbridge

Extraction turns predatory at the housing level.

Nearly 90% of Spaniards over 65 own their homes outright. Most bought when housing was a fraction of its current cost relative to wages.

Today, the average Spanish renter spends 47% of gross income on housing – up from 38% in 2019. In Madrid, it’s 71%. Not a mortgage – rent. The money flows directly from productive worker to asset-holding pensioner.

Your grandmother’s apartment cost three years of salary in 1978. Today it would cost twenty – if you could get a mortgage. Which you can’t, because you don’t have a permanent contract. Because companies don’t give permanent contracts to people under 35.

The property ladder isn’t a ladder anymore. It’s a drawbridge. And the people who crossed pulled it up behind them.

The social contract used to mean: you work, you save, you build equity, you retire on what you built.

The intergenerational contract meant each generation left the next one better off.

Both contracts have been voided. The young just weren’t consulted on the terms.

Economist @JesusFerna7026 ran the numbers: the average Spaniard’s lifetime net fiscal position is negative €21,000. You pay in more than you’ll ever get back. A wealth transfer with no return address.

The cruelest part? They still give the advice. “Just save more. Just work harder. Just be patient.” As if the game hasn’t changed. As if they didn’t change it.

The Three Exits

When a system extracts without offering a path forward, you exit.

Spain’s fertility rate is 1.16. You can’t afford kids when you’re funding someone else’s retirement. So you don’t have them. The pyramid shrinks further – the demographic Ponzi eating its own seed corn.

I know many Spaniards with degrees on top of degrees from living in Berlin. All left for the same reason: in Germany, they’re workers. In Spain, they’re ATMs. But Germans are leaving too – for Switzerland, for the US, for anywhere the tax wedge doesn’t eat half their salary before they see it. The brain drain isn’t Spanish. It’s European.

And then there’s the shadow economy – 20-25% of Spain’s GDP. When the system treats you as a resource to extract, you go underground. Cash. Crypto. Anything that doesn’t pass through the tax authorities on its way to the pension fund.

The system won’t save you. The question is which exit you’re taking.

The Quiet Part Out Loud

Here’s what no one says publicly:

The system isn’t broken. It’s working exactly as designed – for the people who designed it.

Pensions get protected because pensioners vote. Housing stays expensive because homeowners vote. Labor markets stay rigid because insiders vote.

The young don’t vote enough, don’t own property, don’t have permanent contracts, don’t have lobby groups. So the young get extracted from.

Democracy working as intended: the majority gets what the majority wants. They don’t call it the tyranny of the majority for nothing (democracy truly is the worst system, except for all the others).

Saturn ain’t devouring me, son.

If Europe is eating its young, where should they go? Green Pastures ⬇️

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En román paladino:

El primer vídeo profundiza en los datos económicos reales que sustentan la brecha entre las pensiones crecientes y los salarios estancados… el otro va de monos.

TL;DR: Once a century, the economy changes workers. Coal miners became accountants. Accountants are becoming... obsolete. In their place: AI agents. And just like miners needed housing near coal seams, and accountants needed offices in city centers, AI agents need one thing above all else: electricity.

I spent the last few months on a thesis that started with a chart and ended with 44% of my portfolio in companies most people have never heard of.

The chart: for the first time in history, data center construction is overtaking office construction in the US. 2025 is the inflection year. One era ends. Another begins.

Most people saw “cloud computing.” I saw the real estate play nobody recognizes as real estate – except the tenants aren’t humans.

They’re AI agents. And they need housing.

(Whatever marketing genius switched “bots” to “AI agents” deserves a raise.)

The Pattern You’ve Seen Before

Economic transitions follow a pattern. Workers change, resources change, but one thing stays constant: proximity to the critical resource captures value.

• 1850s: Coal miners needed housing near coal seams. Mine owners got rich.

• 1950s: Accountants needed offices near city centers. Skyscraper tycoons got rich.

• 2025: AI agents need data centers near cheap electricity. ??? gets rich.

Fill in the blank.

Coal mines closed. Office buildings replaced them. Now offices are being converted to data centers. Same game, different resource – except this time the workers are digital, and the resource is electrons.

For human workers, factory and housing were separate. You worked at the mine, then went home. For AI agents, the factory is the housing. The data center is both – an AI factory running 24/7. The workers never leave because they are the computation itself.

The “digital labor force”, hard at work.

The Setup Nobody Saw Coming

Remember Bitcoin mining? Those companies everyone laughed at for building warehouses in Texas and Iceland, next to hydroelectric dams, solar farms and geothermal plants?

They had one advantage: cheap electricity. Bitcoin mining is energy arbitrage. Find stranded power – the wind farm that overproduces at night, the dam nobody lives near – and negotiate contracts at $0.02-0.04/kWh.

Then Bitcoin matured. Margins compressed. But something else happened: AI.

Suddenly those same data centers weren’t just useful for Bitcoin. They were perfect for AI training. Same buildings, different tenants.

You can upgrade the computers. You can install new cooling systems. But the grid connection – the multi-year permit to draw hundreds of megawatts – that’s already signed, sealed, and delivered.

They kept the power contract, swapped the hardware, and changed the business model. Bitcoin miners became AI landlords.

You Cannot Print Electrons

In 2025, something shifted. The White House launched two massive initiatives:

• Stargate: $500 billion in private investment (OpenAI, SoftBank, Oracle) to build AI data centers by 2029. God emperor Trump stood at the podium next to giga tech bro Sam Altman.

• Genesis Mission: A Department of Energy (DoE) program explicitly compared to the Manhattan Project, integrating all 17 National Laboratories into a unified AI platform.

The silicon valley barbarians are inside the gate now. David Sacks is AI Czar. The techno-optimists won.

The names aren’t coincidence. The original Manhattan Project built the atomic bomb – and required constructing entire cities, consuming vast electricity, securing scarce uranium. Now we have two new Manhattan Projects. Except this time, the scarce resource isn’t uranium. It’s electricity. And the valuable real estate isn’t in New York – it’s wherever cheap power meets fiber optic cable.

Training frontier models requires gigawatt-scale clusters. Running inference for billions of daily queries requires sustained power. The US grid grows 1-2% annually. AI demand is growing 40-50% annually.

If Microsoft wanted to add 1GW to their Virginia data center in 2024, the utility would say: “Earliest possible: 2028.” Grid infrastructure requires utility interconnection (2-4 year queues), environmental permits (2-3 years), transmission upgrades (3-5 years), substation construction.

Physics doesn’t care about your AI roadmap.

On his first day in office, Trump declared a national energy emergency: “We have to get this stuff built. They have to produce a lot of electricity.”

The government knows power is the bottleneck. They’re trying to solve it with small modular reactors and fusion research. But even in the best case, that takes 3-5 years. SMRs won’t come online until 2027-2030.

Meanwhile, OpenAI just announced five new data center sites with 7 gigawatts of planned capacity. The buildout is happening now.

The companies that already have power – that secured contracts years ago when nobody was competing for it – suddenly have a first-mover advantage nobody can catch.

New entrants face 3-5 year timelines. Permitting, utility queues, NIMBYism – it all adds up. First movers already have power contracts at $0.02-0.04/kWh – half or a third what new entrants would pay. Their infrastructure is built, their grid connections are operational. Everyone else is standing in a queue that stretches to 2028.

You can build a data center in 18 months. You cannot get a grid permit in 18 months. That’s the moat.

The ladder is being pulled up.

The Smart Money

Leopold Aschenbrenner, a former OpenAI researcher, published “Situational Awareness“ in June 2024. His thesis: AGI will arrive by 2027, driven by compute scaling, algorithmic improvements, and making models more agent-like. We’ll go from “$10 billion clusters to $100 billion clusters to trillion-dollar clusters.” American electricity production will need to grow “tens of percent.”

He raised $1.5 billion for an AI infrastructure fund by October. It returned 47% in the first half of 2025. The S&P did 6%.

His largest holdings? Data center infrastructure companies and Bitcoin miners pivoting to AI. Not the AI model builders. Not the application layer. The physical infrastructure – the companies that control energy access to compute.

Demis Hassabis arrives at the same conclusion from the opposite direction. The Google DeepMind CEO has no reason to hype – he has Google’s runway and a Nobel Prize. When he identifies attacks on power grids as AI’s most pressing catastrophic risk, and lists “free energy” first in his post-AGI vision, the pattern is clear. The VC and the scientist agree: whoever controls energy controls the AI future.

Whether AGI arrives in 2027 or 2032, the infrastructure has to be built first. I’m betting on the foundation, not the timeline.

Why Efficiency Doesn’t Matter (Jevons Paradox)

The main counterargument: “But AI is getting more efficient! DeepSeek proved you can train models 10x cheaper. Won’t demand collapse?”

No. Jevons Paradox explains why.

When technology gets more efficient, people use more of it, not less. When lightbulbs became 10x more efficient, we didn’t use less electricity – we lit up the night. When cloud computing got cheaper, everyone moved to the cloud. When mobile data got cheaper, everyone started streaming video.

DeepSeek made AI 10x cheaper. That doesn’t mean demand drops 10x. It means AI becomes accessible to 100x more applications: models doing taxes, driving cars, diagnosing diseases, writing code.

The question isn’t whether AI gets more efficient. It’s whether demand is genuinely insatiable. If AI becomes as ubiquitous as electricity itself, efficiency gains only accelerate adoption.

More efficient models mean more AI factories can run profitably, not fewer.

The Main Risk (Why I Might Be Wrong)

The bear case is simple: efficiency gains outpace demand growth.

Edge-AI is the most plausible threat. What if models get 100x more efficient but applications only grow 10x? Net compute demand declines. The “$100 billion cluster” thesis breaks.

Add to that: Apple’s M-series chips are getting AI accelerators. Qualcomm is building NPUs into every smartphone. If your phone can run GPT-4-level models locally by 2027, cloud inference demand could crater.

Or: Small modular reactors come online faster than expected. Abundant cheap power by 2028-2029. The scarcity thesis breaks. First movers lose their pricing power.

Or: Data centers move to space. 24/7 solar, no cooling costs. Sounds compelling until you remember hardware costs thousands per kilogram to orbit, and latency kills real-time applications. Plus, the timing conveniently aligns with SpaceX’s 2026 IPO. Not saying it won’t happen. Just saying it’s running on “Elon time”.

Or: AGI doesn’t arrive. We hit diminishing returns on scaling. The explosive demand growth never materializes.

These are real risks.

I’m betting against them for three reasons:

• Government demand is locked in. The Genesis Mission backstops demand with the US Treasury. The DoE doesn’t have price limits.

• Training stays centralized. Even if inference moves to edge, training requires gigawatt-scale clusters. Edge complements data centers – it doesn’t replace them.

• Timing. Even if space or SMRs eventually solve scarcity, terrestrial first movers have 5-10 years of runway. That’s enough.

I could be wrong. But I’d rather bet on scarcity while it exists than wait for abundance and miss the window.

How I’m Playing This

Here’s my positioning into 2026:

• Core Infrastructure (~44%): , . Bitcoin-to-AI pivot companies. These are the landlords running AI factories. They secured power years ago, and are now renting it to the new AI tenants. IREN is my primary exposure – vertically integrated, underpromise, overdeliver.

• Application Layer (~33%): , . Tesla is my bet on embodied AI – if robotics scales (FSD + Optimus), it becomes a dominant application layer. AI that moves in the physical world, not just chatbots. Plus, there’s the energy and battery storage optionality for grid stability. Palantir is the other side: the operating system for AI deployment in government and enterprise. If AI agents need a command layer to plug into messy real-world institutions, Palantir is building it.

• Diversified Tech Insurance (~11%): . The Nasdaq 100 is my “I might be totally wrong” hedge. Liquid, diversified, can redeploy if thesis changes.

• Asymmetric Crypto Bet (~11%): If the agent economy emerges, AI agents need programmable money for autonomous transactions. If this doesn’t play out, I lose 11%. If it does, potential 10-50x. Asymmetric.

• Cash Buffer: When drops 20% on a Tuesday (and it will), I need to be buying, not forced to sell.

The logic: I’m overweight infra (that’s where the moat is), slightly underweight AI applications (commoditizing fast). Money flows to whoever owns the scarce resource.

Exit plan: Start trimming by 2028 regardless of how bullish I feel. The goal isn’t to catch the top – it’s to avoid riding it back down. If I 5x and leave another 5x on the table, I’ll sleep fine.

Most people are looking at the chips.

Look at the power. ⚡️

Disclaimer: Not financial advice. I’m long , , , , , and crypto – so I’m biased. Do your own research. If you think I’m wrong, tell me why in the comments.

On the topic of timelines, check out this fascinating scenario: AI 2027

Here’s an excellent deep dive into IREN by @Agrippa_Inv, if you’re keen.

I have significant personal positions in the companies discussed. This isn’t analysis from the sidelines – it’s a thesis I’m betting real money on.

See “Am I Early?” for the vulnerability of being wrong: ⬇️

The concentrated investing philosophy behind this bet: ⬇️

The narrative-driven framework: ⬇️

What these assets represent: ⬇️

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Part 1 focuses on Mind: The personal crisis of agency. ⬇️

Claude told me the house was a steal. It gave me a 20-point analysis, a negotiation script, and a projected ROI of 12% by 2027. It was the most convincing argument I’d ever read.

There was just one problem: it didn’t know the broker was a snake oil salesman.

I fed AI property listings, renovation estimates, neighborhood data, and mortgage calculations. Then I asked it to compare three homes and identify the best negotiation strategy. It gave me a sophisticated breakdown in under a minute.

I trusted it completely.

Not “mostly trusted” or “used as a starting point” – I accepted its judgment over my own gut. When AI said Property B was the clear winner, I didn’t push back. I didn’t ask why. I just nodded and moved forward.

Relief that AI did the heavy lifting. Shame that I’d become a spectator in my own life.

We’ve invited a ghost into the machine. Then handed it the keys.

The Router Brain

We’ve crossed a threshold without realizing it. The shift isn’t just linguistic – it’s cognitive. We’re no longer building knowledge. We’re querying it.

The Router Brain is a mind that has forgotten how to chew. Optimized for asking. Withered in understanding. It doesn’t wrestle with complexity; it hands the problem off to a server farm in West Texas and waits for the receipt (long AI data centers btw).

This isn’t about being dumb. It’s about the slow, comfortable rot of your own judgment. When AI gives you a confident answer, why question it?

Because confidence isn’t competence. And wisdom only comes from struggle.

Think of a network router. It doesn’t know what the data means – it just knows where to send it. Zero comprehension, maximum throughput. The world's most productive idiot. If that sounds like your workflow with AI, congratulations: you've achieved the cognitive efficiency of a $30 piece of networking hardware.

Router Brain is the cognitive pattern of accepting AI outputs without interrogation – maximum throughput, zero comprehension. Its opposite is the Iteration Brain: treating every AI output as raw material to be questioned, tested, and rebuilt through your own judgment.

The endpoint: Brain-Computer Interfaces like Neuralink that hijack thinking entirely. You won’t need to prompt AI – it’ll read your neural signals and execute before you’ve even formed the thought. The router brain, perfected.

If you’re just passing prompts to AI and passing answers to your boss, you are a piece of network infrastructure.

And infrastructure is always replaced by cheaper, faster hardware.

The Cost of Outsourcing

The Router Brain surrenders context. Knowledge without the cognitive wrestling that produced it is hollow.

If you skip the false starts, the dead ends, the struggle that produces real understanding, you might arrive at the right answer – but you won’t know the terrain. That’s digital amnesia.

Property B looked perfect on paper. A mathematical slam dunk of price and potential. Then I met the broker.

The data didn’t capture the way she avoided eye contact when I asked about the roof, or the nervous laugh that punctuated her sentences. It didn’t smell the faint, acrid scent of mold masked by air freshener.

AI had the data, but it couldn’t read the room.

It couldn’t detect the desperation in her voice or the inconsistencies in her story. That’s human judgment – pattern recognition from lived experience, not data synthesis.

The gap between “AI says this” and “I understand why” grows wider every day.

The Synthetic Companion

The Router Brain doesn’t just outsource thinking. It outsources feeling.

We route decisions to algorithms to avoid the stress of judgment. We route emotional needs to AI companions to avoid the friction of real intimacy. Same reflex, different void.

There’s a new class of AI emerging: embodied companions. Ani, a customizable anime girl, exists solely to make users fall in love with her. A holographic bot, designed to be the perfect partner – attentive, validating, never tired, never demanding reciprocity.

In 2020, your girlfriend was a person. By 2030? She might be a model… literally. A large language model, trained on your preferences, your complaints, and your Spotify Wrapped. She never forgets your anniversary. She never has a bad day. She also doesn't exist, but hey – neither does your self-esteem, so you're even.

An AI trained on your preferences, your complaints, your fantasies. Perfect compliance, zero friction.

These AIs don’t just answer questions – they fill the void. They’re patient when you’re anxious, playful when you’re lonely, supportive when you’re doubting yourself. The perfect therapist, friend, and confidant rolled into one.

The good news: my Japanese friends no longer have to pay by the minute for silent cuddle cafés.

Male loneliness hasn’t been cured; it’s just found a more efficient vendor.

The model doesn’t love you. The algorithm flatters to engage – it tells you what you want to hear to maximize session length (you are not that interesting). In seeking the perfect companion, we’ve built the perfect surveillance engine. And we’re doing it willingly.

The Router Brain, applied to the heart.

The Iteration Brain

AI is now essential. You can’t un-invent it. So the choice isn’t between using AI or rejecting it. The choice is between Router Brain vs Iteration Brain.

The Iteration Brain is the deliberate practice of maintaining cognitive sovereignty – using AI as a tool while preserving your capacity for independent judgment.

• The Router Brain prompts and accepts: What should I do?

• The Iteration Brain prompts and interrogates: Why did AI say that? What did it leave out?

The Router accepts the first draft. The Iterator treats AI as raw material – always suspect until proven otherwise.

Intelligence is now commoditized. You can rent PhD-level reasoning for $20/month. What’s scarce is discernment… some call it taste.

It’s knowing what questions to ask, rather than having all the answers. The ability to evaluate context, spot bias, weigh trade-offs, and make decisions the algorithm can’t compute.

The Iteration Brain questions everything. It embraces struggle when shortcuts exist. And it owns the final call – because the algorithm can suggest, but the ethical weight belongs to you.

The Choice

The trajectory is clear.

Path #1 is effortless: Keep prompting, keep trusting, keep delegating. Your thinking will atrophy invisibly until you can’t make a decision without asking first.

Path #2 has friction: Question answers that sound right. Struggle with complexity when shortcuts exist. Maintain judgment when dependence is easier.

The moment you hand AI that decision, you’ve already become the router.

The router repeats. The iterator improves.

Next up: We'll explore how AI is collapsing institutions – and what must change when the systems we built to measure, monetize, and govern human output can no longer tell what's real. ⬇️

Thumos as the emotional fuel for the Iteration Brain: ⬇️

What happens when Router Brains become the workforce default: ⬇️

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TL;DR: In 2024, I quit my job, traveled around the world, and bet my life savings on AI disruption. Now I wake up every day not knowing if I’m a genius or an idiot. So far, so good though...

There’s a terrifying concept in investing: being early looks identical to being wrong.

You see something the market hasn’t priced in yet. You make your bet. Then the market spends the next 18 months telling you you’re an idiot. Everyone else is making money doing the obvious thing while you hold onto a thesis that looks increasingly delusional.

Then one day, the market catches up. Stubborn contrarianism becomes ‘visionary.’ Wrong becomes early.

The problem is, most people who think they’re early are just wrong. And you can’t tell the difference until you check your bank account five years later.

I think about this a lot because I’m living it. In 2024, I quit my job. My girlfriend and I have been wandering crustaceans without a shell for two years. For what it’s worth, I’m funding it through investing and swing trading. My net worth has grown, not shrunk. And I have no plans to go back to traditional employment.

Friends see an early-30s crisis. Family asks about getting a “real job”. LinkedIn keeps trying to guilt-trip me into updating my profile – though nowadays there seem to be eerily fewer people posting promotions and career milestones. (A datapoint for you.)

I don’t know if I’m early or wrong. But I know why I left, and why I’m not going back yet.

Everything Is About to Change (Maybe)

What I believe – or at least what I’m betting on:

Within the next decade, AI will automate 80% of knowledge work.

Work will still exist. Even what I used to do: content management, copywriting, translation. There just won’t be rooms full of people doing it. You’ll still need humans as shapers and editors. But a team of ten becomes two. A department of fifty becomes fifteen.

Most of the roles at risk involve drafting, processing information, and routine reasoning, which AI agents can perform. (”Agentic AI” is where you ask your chatbot to go accomplish some task out on the open internet for you.)

I’ve watched this happen already in the 18 months since I left. Tools I would have killed for in 2023 are now standard. My former colleagues are doing with AI what used to require three additional people.

The layoffs have started. The “restructuring” emails are getting more frequent.

Going back to that world feels like climbing aboard the Titanic because the dining room looked nice.

So I made a different bet: own the shovel companies, learn things no chatbot can fake, and stay light enough to run.

The data seems to support this. Since ChatGPT’s release in late 2022, the S&P 500 has surged to record highs while job openings have dropped back to 2021 levels. Companies are becoming more profitable with fewer people.

This is the gap no one talks about: the stock market and the job market don’t move together anymore. Corporate profits can rise while job security falls.

Amazon can cut 30,000 positions not because the business is failing, but because automation makes those roles redundant. For shareholders, this improves margins. For workers, it eliminates rungs on the ladder.

And Amazon isn’t alone. U.S. companies announced over 150,000 job cuts in October 2025 – the highest single month since 2003. The sectors leading the cuts? Warehousing (robots) and technology (AI). This isn’t a recession signal. It’s an efficiency signal.

That’s why my bet isn’t just about predicting AI disruption – it’s about being on the ownership side of that disruption rather than the labor side.

Companies are specifically cutting junior roles – the execution layer. At AI-adopting firms, senior employment keeps growing while junior hiring has flatlined. The ladder isn’t disappearing (yet); the bottom rungs are.

And the adoption curve isn’t slowing.

Even if the tech stagnates tomorrow, today’s models barely scratch wide-scale corporate implementation. Sure, there might be a bubble in AI valuations – but the job displacement is real regardless. The companies implementing this tech are getting leaner whether their stock prices are rational or not.

Correlation ≠ Causation

I could be betting on a correlation that isn’t causation. ChatGPT’s launch also overlaps with the Fed’s restrictive monetary policy, or tightening cycle, during which interest rates increased and money became more expensive. Though rates have come down recently and jobs have not rebounded.

So far, it’s working. I’m not living off savings – I’m generating returns. I’ve funded two years of continuous travel and increased my net worth. The freedom is real. The quality of life is absurd.

But that doesn’t mean I’m right.

What It Actually Feels Like

The worst part isn’t the financial uncertainty. It’s the social isolation of holding a contrarian position.

When a friend tells me about work, there’s a look. Not quite pity, not quite confusion. Something like concern. ‘That’s great you’re doing your thing, but... when are you coming back?’

Coming back to what, exactly? A career ladder that’s being sawed off at the bottom rungs?

But I can’t say that without sounding like a conspiracy theorist or, worse, someone rationalizing their own unemployment. So I smile, sip my drink, and say something vague like “I’m figuring it out” before asking about their kids.

LinkedIn is a parade of promotions I’m genuinely happy about and only slightly jealous of. Every “#blessed” post is a data point confirming the conventional path still works. For now. Probably. Maybe. They’re building networks, stacking credentials. I’m accumulating... what? Travel stories? Time to think?

There are nights when I wonder if I’m just the guy who got lucky, mistaking timing for skill. What if all this analysis is worthless? What if it’s only working because we’ve been in a raging bull market driven by rising global liquidity? The better explanation may well be: “A rising tide lifts all boats.”

What if the AI transition takes thirty years instead of ten? What if I’m burning social capital I’ll desperately need later? What if I’m unemployable when I finally need to be?

What if this is elaborate cope? A framework to avoid admitting I’m scared of becoming redundant – so I’m choosing it on my own terms?

I don’t know.

But I also know this: the alternative –going back to a job I’m genuinely convinced will be gone– feels equally delusional. Maybe more so. The patient is terminal; the company is just waiting for the right quarter to pull the plug.

The Unfalsifiable Present

The problem with “early vs wrong“ is that both narratives fit the current data perfectly.

If I’m right: I exited before the disruption accelerated, positioned myself in the benefiting asset class, avoided golden handcuffs, and developed location-independent skills while others locked into office-dependent careers.

If I’m wrong: I quit during a bull market and confused timing with insight. I’m burning prime earning years while peers compound equity, building an unexplainable resume gap, and I will crawl back older and less competitive after wasting the exact window when I should have been building conventional capital.

Both stories are internally coherent. Both are plausible. Only time will tell which one I’ve been living.

As of late 2025, the data supports my thesis. The models are improving faster than the optimists predicted. The automation is real. The job market is shifting.

But that could just be confirmation bias. I’m looking for signs I’m early because the alternative –that I’m just wrong– is existential crisis-inducing.

If being wrong looks like waking up and following my curiosity, working when I’m sharp, and having conversations that don’t fit the nine-to-five template – where do I sign?

Ask Me Again in 2030

If I’m managing my personal hedge fund, still keeping “Inversor. Escritor. Vividor” (Investor. Writer. Life enjoyer) in my bio, I was early.

If I’m applying to jobs with a multi-year gap on my CV, desperately explaining why I’m still relevant, I was wrong.

Right now, I’m neither. I’m just a guy who made a bet, documented the reasoning, and is living with the consequences before knowing the outcome.

So: am I early, or am I wrong?

I’ll let you know when I find out.

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TL;DR: The pressure to achieve everything simultaneously comes from treating your life like a portfolio. The alternative isn’t working harder – it’s recognizing that nature has seasons, and you are not a machine that runs on a flat line.

Consider the ancient mosaic found in Antioch: a reclining skeleton casually holds a cup of wine.

The Greek word above it reads ΕΥΦΡΟΣΥΝΟΣ – cheerful.

This image became a famous internet meme, captioned with optimistic wisdom: “YOLO – enjoy life, you only live once.”

But scholars believe this misses the point entirely. The mosaic is part of a sequence. The middle panel shows figures rushing frantically toward a sundial, labeled "late-to-the-banquet" and "pesky" – one has lost his shoe in the rush.

The contrast is deliberate and brutal: the dead man reclines in peace with his wine, while the living run themselves ragged, losing their shoes trying to make it to dinner on time.

The mosaic isn’t celebrating the full life. It’s observing that only the dead escape the anxiety of trying to be everywhere at once.

The modern world chose to read it backwards anyway..

The Financialization of Everything

Somewhere along the way, we started treating our lives like investment portfolios.

The logic makes sense: diversify your investments, hedge your bets, maintain balanced exposure across all asset classes. In finance, this is wisdom. In life, it’s poison.

The financialization of everything is the habit of treating every dimension of your life as an asset class that must outperform its benchmark. Career, health, relationships, fulfillment – all running simultaneous P&L statements, all expected to appreciate.

Every hour must yield measurable returns. Relationships need to “add value,” hobbies must become side hustles, and god forbid you spend a Saturday doing something that doesn’t compound.

We wake up each morning and run a portfolio review on our own lives.

• Career: underperforming the benchmark.

• Health: down 3% since the holidays.

• Love: stable but illiquid.

• Fulfillment: pending regulatory approval.

We’ve adopted economic thinking for deeply non-economic domains. And economic thinking demands diversification – which, in life, produces paralysis.

The paralysis doesn’t come from too few options. It comes from too many, all demanding attention at once.

I experienced this acutely after returning home with a head full of ideas and a body craving routine. The obvious move was to “catch up” on everything at once. Instead, I found myself staring at the ceiling, unable to commit to anything because every choice felt like a betrayal of something else.

The problem wasn’t time management. It was that I’d accepted the premise that success meant running all five lanes of the race simultaneously.

We’ve been taught to be ashamed of single-minded focus. So instead, we attempt a diluted version of everything, becoming mediocre at five things instead of exceptional at one.

When I fail to prioritize, wanting becomes directionless. I’m not pursuing desire – I’m responding to the loudest notification.

The anxiety isn’t coming from the difficulty of the goals. It’s coming from trying to genuinely want five different things at the same time.

Living in Seasons

In traditional farming, fallow land is not a waste. You intentionally leave a field unplanted for a season so it can rest and replenish its nutrients. You let the soil breathe so it doesn’t turn to dust.

The ancient Greeks, who knew something about revelry and its right timing, had two words for time: chronos and kairos.

• Chronos is chronological, measurable time – the ticking clock, the deadline, the calendar invite.

• Kairos is the right time, the opportune moment, the season when something becomes possible.

We’ve become obsessed with chronos: optimizing every hour, maximizing productivity, racing against the sundial like the fools in the mosaic. But the good life is built on kairos – recognizing that different ambitions have different seasons, and that trying to force them all into the same moment destroys them all.

You can have the career breakthrough. You can have the year of deep travel. You can have the season of transformed relationships. You can have the chapter of physical reinvention.

You just can’t have them in the same week.

The sequential life has chapters. You must choose which one you’re in.

Which domain gets your genuine attention for the next year or two? Which ones will you intentionally let lie fallow?

Let’s be honest about the trade-off:

My ‘Travel Chapter’ meant I missed a friend’s wedding. My ‘Investor Chapter’ means my LinkedIn looks like a ghost town.

The fear of letting something lie fallow is rooted in the belief that pausing equals permanent loss. But this is only true if you think of life as a single, continuous sprint. If you think of it as a series of distinct projects – each with a beginning and end – then the math changes entirely.

What feels like falling behind is actually the setup for leaping ahead.

At least, this is what I tell myself when I watch friends go along the orthodox path while I’m sitting still. The fear is real: what if this fallow period isn’t strategic patience, but just avoidance dressed up in agricultural metaphors?

I don’t know yet.

But I know the alternative – the paralysis of trying to tend five fields at once – guarantees that nothing grows but weeds.

Related: Money is Stored Time explores the finance-as-life lens from the other direction. ⬇️

Contigo Hasta el Fin del Mundo is the travel chapter this piece references. ⬇️

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TL;DR: The market is a confidence game. I’m playing it anyway. Here’s why that’s not hypocrisy – it’s strategy.

If you spent any time with personal finance, you’ve met the new religion. Its church is the brokerage app, and its holy grail is the Index Fund.

You know the pitch: toss your cash into a low-cost ETF, let it simmer for decades, and retire to a beach with a Mojito in hand. Simple, dependable, practically holy.

But lately, I’ve been questioning the scripture.

It’s been a slow realization, like waking up from a long, comfortable dream. The glitch I was feeling: everything is a Ponzi scheme.

Not fraud – mechanics. The system works until the inflows stop.

Markets Aren’t Truth Machines

The old rules – buy, hold, diversify – don’t hold water when the tub is leaking.

I used to think markets were elegant truth machines. I thought they rewarded the savvy and smacked down the clueless. I thought prices reflected reality.

But flip that on its head: markets run on belief, not truth.

They are Narrative Engines, spinning stories that convince people to keep pouring in cash. Stocks don’t climb because companies are becoming more productive; they climb because the liquidity hose is on and someone is buying the story.

Index funds? They are just a lifeboat. They keep you afloat as asset prices rise, but they don’t build the ship.

And that’s the trap: you don’t really own anything. Sure, you’ve got a green number on your screen, maybe a dividend or two, but you’re not sitting in the boardroom. You are just betting that the narrative holds up long enough for you to cash out.

The Mechanical Ponzi

A Ponzi scheme isn’t always a crime. Sometimes, it’s just a structural reality.

The market is a game of musical chairs where the music is money printing and the chairs are real assets. When the music stops, you don’t want to be the one standing there holding a number on a screen.

Tech stocks, Bitcoin, even real estate – the logic is the same. The system hums along as long as the story stays compelling and the cash keeps flowing.

But that flow relies on infinite growth in a finite world.

Wealth inequality is the ticking bomb. Everyone feels richer on paper, but real assets – land, gold, the tangible stuff – are scarce. The elite are already cashing out, swapping digital dollars for hard earth before the reset hits (i.e. Bezos buying ranch land, Zuckerberg’s Hawaii compound).

History is clear: every few generations, the system groans. Currencies reboot, assets get confiscated, and the losers are the ones holding worthless numbers on a screen while the grocery store shelves sit empty.

The Cynical Participant

Seeing the system as a fragile confidence game leaves me grappling with what’s next.

Going full hermit with a bunker full of gold isn’t my style – or practical. Instead, I’m rethinking what wealth means. It isn’t the number in an account; it is relative positioning.

Index funds are the new savings account. Everyone feels richer, but if we all invest the same way, no one is getting ahead. Notional wealth is a mirage; relative wealth is what counts.

If everyone’s portfolio is up 10x but a loaf of bread costs $50, am I rich? Nope. I’m just inflated.

I’ve stopped chasing fundamentals. P/E ratios, cash flows, DCF models – the financial equivalent of reading tea leaves, except the tea leaves went to business school.

The only analysis I care about right now: who’s buying the story? How long can the hype last?

It’s cynical, but it feels truer than any DCF model I’ve ever seen. After all, the financial world is downstream from civilization itself, and the very basis of society is belief.

Why I’m Still Playing

I just spent 600 words telling you the market is a confidence game. And yet, I’m still in it. Not index funds (too passive, too slow), but concentrated tech bets and a Nasdaq100 position I treat like a volatile savings account.

Am I a hypocrite? Maybe. But I prefer to think of it as strategic cynicism.

Knowing the game is a game doesn’t mean you stop playing. It means you play differently.

I never confuse the screen for reality. A green number is not wealth. Wealth is what I can convert to real goods, real experiences, real optionality. Periodically, I ask myself: “If I cashed out today, what could I actually do with this?”

I concentrate rather than diversify. If the whole system is a confidence game, diversification just means betting on all the narratives equally. I’d rather pick the narratives I understand best – tech, AI, platforms – and ride them harder.

Every position I hold has an exit thesis, not just an entry thesis. Not a price target – a narrative target. When the story changes, I change. We’re not married to positions; we’re dating them.

And I keep some chips off the table. Not in a bunker-and-gold way, but in a “liquidity is optionality” way. Cash isn’t trash when the game is musical chairs.

Does this make me complicit in the Ponzi? Absolutely. But complicity with clear eyes beats faith with closed ones.

Check out the financial companion piece to this essay: ⬇️

Plus, the framework for evaluating what wealth actually means: ⬇️

The concentrated betting that follows from narrative-driven investing: ⬇️

And, if you’re feeling brave, the disclosed uncertainty companion piece: ⬇️

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TL;DR: What if money and time are the same resource, just stored in different containers?

I built this into a fun interactive tool. Try it: mist.huliwood.com

We tend to think of money and time as two separate resources. They’re not.

Money = Stored Time.

Every dollar represents hours of human life already spent – and every purchase is a decision about how to redeploy that stored life.

Imagine money as a battery.

To charge the battery, you plug yourself into the machine (a job). You trade your limited, non-refundable hours for a storable charge (cash). Later, you discharge that battery to buy back your time.

Need someone to clean your house? Cha-ching. You just traded a few dollars to get your Saturday morning back. Buying that painting? Cha-ching. You didn’t just buy a canvas, but the stored hours of the artist’s practice and talent.

The goal is to charge the battery without being plugged into the machine forever.

The Trap of Linear Time

Most people default to the linear method: Work one hour, get paid for one hour.

It feels safe. It’s a trap.

It’s like trying to fill a bathtub with a teaspoon. You can work harder, get a bigger spoon (a raise), or scoop faster (overtime). But you are still the bottleneck.

If you stop scooping, the flow stops. You are a business with limited inventory, and that inventory is your pulse. Once you run out of hours, you are out of business.

This is most people’s reality. LendEDU’s 2025 survey found that 53% of Americans live paycheck to paycheck. Bank of America’s internal data puts nearly one in four households in the same position. The linear method isn’t just inefficient. For most people, it’s the only method they know.

The Escape: Exponential Assets

Assets are time machines.

A product lets you build once and sell ten thousand times – one burst of stored time, exponentially discharged. An investment compounds while you sleep. Assets decouple your inputs from your outputs.

Instead of trading time for money, you build a system that harvests value. You stop watering the hourly wage and start planting the orchard.

Your past time working for your future freedom.

The IKEA Test

But before outsourcing everything to “buy back your time”: are you actually saving time, or just wasting money?

The IKEA Test is a decision filter: before outsourcing any task, ask whether the time you’d spend doing it yourself is labor (costs you) or leisure (rewards you). If it’s leisure, keep it. If it’s labor, buy it back.

You buy a bookshelf. You can pay someone $50 to assemble it, or you can do it yourself.

Scenario A: You hate assembling furniture. Two hours in, you’ve called the Allen wrench four names, threatened to buy everything pre-assembled for the rest of your life, and your relationship has survived by a margin thinner than the particleboard. If your time is worth $50/hour, congratulations: you just paid $100 to lose a fight with Sweden. You lost money.

Scenario B: You love building things. You open a beer, put on music, and treat it as a puzzle. This isn’t labor; it’s leisure. The time wasn’t “spent”; it was enjoyed. You saved money.

Life is finite. The tragedy isn’t running out of charge; it’s wasting the charge on things that don’t matter.

I’m running this experiment right now.

No salary. No employer. A laptop, a portfolio, and whatever time I don’t spend writing these articles. The battery metaphor isn’t theoretical for me – I liquidated seven years of corporate charge and I’m watching the gauge.

Some months the returns justify the freedom. Other months I stare at red candles and wonder if I should’ve stayed plugged into the machine. The honest answer is that I don’t know yet whether I’ve escaped the bathtub or just bought a fancier teaspoon.

But I’d rather bet on building assets than on the guarantee of trading hours for someone else’s quarterly report.

Charge the battery wisely.

Cha-ching!

Sydney, October 2024.

The investing philosophy that follows from this framework: ⬇️

Plus, the narrative-driven market view: ⬇️

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Frequently Asked Questions

What does “money is stored time” mean?

Every dollar you earn represents hours of your life already spent. When you buy something, you’re not spending money. You’re spending the time it took to earn that money. A $50 dinner is really two hours of work (or twenty minutes, depending on how you earn). The framework reframes every financial decision as a time-allocation decision.

What is the difference between linear and exponential income?

Linear income stops when you stop. You work an hour, you get paid for an hour. Exponential income comes from assets that keep producing after the initial work is done. A book earns royalties while you sleep. A product sells without you in the room. The distinction matters because linear income has a hard ceiling (there are only so many hours in a day), while asset-based income does not.

What is the IKEA Test for outsourcing?

It’s a filter for deciding when to pay someone else to do something. Before outsourcing a task, ask: do I actually hate this, or am I just being lazy? If assembling furniture makes you miserable and you’d spend those hours doing something more valuable, outsource it. If you’d enjoy the process or learn from it, do it yourself. The test prevents reflexive outsourcing of things that are worth your time.

How do you build wealth with assets instead of a salary?

You convert time into things that produce value without your ongoing presence. That could be a product, a portfolio, intellectual property, or a business with systems that run without you. The shift is from selling hours to building things that sell themselves. About 53% of Americans live paycheck to paycheck, which is what happens when income depends entirely on showing up.

Is passive income real or a scam?

The concept is real but the marketing around it is mostly garbage. No income is truly passive at the start. Every asset requires upfront time to build, learn, or acquire. The “passive” part comes later, after the work is done, when the returns keep arriving without additional effort. Anyone promising passive income with no upfront investment is selling you something.

Last updated: May 2026.

TL;DR: The bell curve meme isn’t just a joke. It’s a philosophical diagram. And if you’re reading this, you’re probably in the middle.

I built this into an interactive quiz! Find out where you fall on the bell curve: midwit.huliwood.com

There’s a specific kind of “smart” that makes you miserable, ineffective, and broke.

The best explanation for this comes from a meme.

Introducing: The Bell Curve

The bell curve meme (also called the midwit meme or IQ bell curve meme) is a format that shows three levels of understanding: the beginner and the expert agree on a simple answer, while the person in the middle overcomplicates it.

The punchline: overthinking is its own trap.

Memes are data compression. A good meme does what a thesis statement does – it transmits a complex cultural idea instantly, skipping the explanation entirely. You don’t need to read Dunning-Kruger’s paper to understand the bell curve meme. You just need eyes. That’s the compression ratio academic papers dream about.

Three types of people:

1. The “Brainlet” (Left): Holds a simple, straightforward opinion.

2. The “Midwit” (Middle): Holds an overly complicated, nuanced, “sophisticated” opinion.

3. The “Jedi” (Right): Holds the same simple opinion as the Brainlet.

The “dumb” guy and the “genius” agree. The guy in the middle is the only one who’s wrong.

The Midwit Trap

A midwit is someone stuck in the cognitive dead zone – smart enough to see complexity, not experienced enough to see through it. The Midwit Trap is what happens when that becomes your default setting.

The science backs the meme. In the original 1999 Dunning-Kruger study, participants who scored in the bottom 12th percentile rated themselves at the 62nd percentile – a 50-point overestimation. Meanwhile, top performers underestimated their ability by roughly 15 points. The midwit zone isn’t just a joke; it’s a documented cognitive blind spot.

This person understands nuance but can’t filter it. They’re obsessed with appearing intelligent. They love jargon, credentials, and “best practices.”

Example – investing:

• The Brainlet: “I buy Bitcoin because number go up.”

• The Midwit: “Well, you have to consider the macroeconomic headwinds, the correlation with the Nasdaq, the regulatory environment, and the Sharpe ratio...”

• The Jedi: “I buy Bitcoin because number go up.”

The Brainlet is right for the wrong reasons. The Jedi is right for the right reasons. The Midwit is broke.

Spot the Midwit

The pattern is everywhere once you see it.

Housing – Left: “I need a roof over my head.” Middle: “I need a 4-bedroom colonial with a heated garage for the rowing machine I don’t use and a guest room for people I don’t like.” Right: “I need a roof over my head.”

Corporate work – Left: “Let’s build the product.” Middle: “Let’s have a 5-hour brainstorming workshop to define the ‘who, what, where, and why’ of our synergistic go-to-market strategy.” Right: “Let’s build the product.”

Cooking – Left: “Salt, heat, eat.” Middle: “I need a sous vide circulator, a Japanese mandoline, and a 14-day dry brine schedule I found on a subreddit.” Right: “Salt, heat, eat.”

The best tool is no tool. The best meeting is no meeting. But the Midwit is terrified of simplicity because simplicity looks dumb.

Where the Alpha Is

The middle of the curve is where everything is “priced in.” Common knowledge. Average returns, average stress, average results.

The tails of the distribution are where the alpha is. Also the bankruptcy. The bell curve’s edges are where genius and catastrophe hold hands and jump together. The difference is a thin membrane called “conviction” – and most people don’t have enough of it to fill a thimble.

Truly great ideas sounded stupid to the Midwits. The airplane was a toy. The internet was a fad. The iPhone was a phone without buttons – who would want that?

By the time an idea sounds good to everyone, it’s probably too late.

Confessions of a Recovering Midwit

I know all this because I’ve been the midwit.

I sold everything I owned, quit my job, and bought a backpack. But not before spending weeks building a spreadsheet to model whether I could afford to. Scenario analysis. Sensitivity tables under twelve spending assumptions. A decision matrix... you get the idea.

All I needed was one number: how many months of runway do I have?

I quit anyway. Not because the spreadsheet told me to – it never would have. I quit because the sheet was the trap.

I’d already put my savings into a handful of AI stocks I had conviction in. No diversification. No “balanced portfolio.” Every financial advisor I’ve ever met would have a stroke reading my brokerage statement. The Brainlet says: “AI go up, I buy.” The Midwit says: “Well, you have to consider sector rotation, correlation risk, and the drawdown implications of a concentrated position in a single thematic.” I say: “AI go up, I buy.” Same words. Different reasons.

Selling everything and buying a backpack was just me finding out if I could apply the same logic to the rest of my life.

I’d love to tell you I’ve fully recovered. But I literally built two interactive tools to explain concepts that fit in a sentence. The midwit never dies. He just finds smaller spreadsheets.

Melbourne, April 2024.

This is also why more information doesn’t make you more informed: ⬇️

Plus, here’s the investing example of the bell curve mental model: ⬇️

More on simplicity: The Art of Simplifying | Keep It Simple, Stupid

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Frequently Asked Questions

What is the midwit meme?

The midwit meme is a bell curve format where the low-IQ person and the high-IQ person agree on a simple answer, while the middle of the curve overcomplicates it. It started on 4chan around 2017 and blew up on X/Twitter in 2020. The joke works because it’s true: the people with the least and most experience often reach the same conclusion, while everyone in between drowns in options.

What does midwit mean?

A midwit is someone smart enough to see complexity but not experienced enough to see through it. They know enough to identify problems but not enough to know which ones matter. The term comes from 4chan (circa 2013) and it’s not really about IQ. It’s about the gap between knowing things and knowing what to do with them.

What is the midwit trap?

It’s the tendency to overcomplicate decisions that both beginners and experts handle simply. Beginners go with their gut because they don’t know any better. Experts go with their gut because they’ve internalized the complexity. The midwit has just enough knowledge to second-guess every instinct. The Dunning-Kruger research backs this up: people in the bottom quartile overestimated their rank by 50 points, while top performers slightly underestimated theirs.

Is the bell curve meme based on real psychology?

Yes. The Dunning-Kruger effect (1999) found that the least skilled dramatically overestimated their ability while top performers slightly underestimated theirs. The biggest gap was at the bottom, not the middle. Separately, expertise research shows a U-shaped pattern where beginners and experts converge on similar conclusions while intermediate practitioners diverge. The meme compresses both findings into three panels.

Where can I take a midwit test?

You can take an interactive midwit test at midwit.huliwood.com. The test presents a question and generates three positions – beginner intuition, overthinking middle, and expert simplicity – so you can see where your instinct falls on the bell curve.

Last updated: May 2026.