Atoms vs Abstractions
The Periodic Table Problem
TL;DR: Everyone’s debating whether AI will take your job. Almost nobody’s asking whether AI can feed itself. The buildout demands energy, water, and rare earths at scales that expose a fracture 45 years in the making 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.
As we’ve established many times on this Substack, 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?
A recent conversation on Nate Hagens’ 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 Ledgers
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.
Craig Tindale, 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.
AI is about to reconcile both at once.
The Heaviest Metabolism
We talk about AI like it's weightless. Digital. A question goes in, an answer comes out. Magical stuff.
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 recently killed a copper refinery because the ESG cost alone was nearly 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.
You’re in a room full of people chasing IRR. The other side is playing a different game entirely.
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.”
Then nothing changes.
Until it does – all at once.
What Is GDP For? What Is AI For?
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 “generating videos of Brad Pitt and Tom Cruise fistfighting on a roof,” that’s a terrific technical achievement and a staggeringly wasteful use of the scarcest resources on the planet.
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 and 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 the podcast 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.
Maybe the real reconciliation isn’t between the financial ledger and the material one. It’s between the version of ourselves that stares at screens parsing geopolitical risk, and the version that knows – somewhere underneath all the macro – that the croissant matters more than the chart. 🥐
Inspired by Craig Tindale, Michael Every & Nate Hagens on The Great Simplification (RR 22). Listen to it.