In 2012, a quant named Patrick Hagan built JP Morgan's portfolio risk model in Excel. He'd never built one before. It cost the bank $6.2B.

Hagan wasn’t an amateur. He co-invented a formula the whole industry still uses. But he had never built a value-at-risk model (which is a bit like asking a Michelin chef to fix the dishwasher). The model went live with a formula that added when it should have averaged.

Today’s AI builders aren't selected for knowing the work best. They’re selected (or self selected) for being excited about the tech, and that puts us all at risk.

In 1853, Erie, Pennsylvania rioted for two months to keep its train tracks the wrong size.

Erie sat where incompatible track gauges met. Trains from New York couldn't run on Ohio rail, so every passenger changed trains and every load of freight came off one car and onto another. This was terrible for the country, but wonderful for Erie. A whole local economy grew up in the friction. Hotels, restaurants, transfer agents.

So when the railroads moved to standardize, Erie fought back.

I see that same fight inside companies right now.

Every math olympiad champion in the last thirty years learned one thing first. And it wasn't a formula.

Olympiad problems are built so no memorized formula will crack them. No syllabus, no study guide. Winners are the ones who can look at a problem they've never seen and work out what it's actually asking, before they reach for a single technique.

They call it “reading the problem.”
And it’s the secret to building better solutions.

Before 1878, the only way to know if two chemicals would explode was to mix them and stand back.

Then Josiah Willard Gibbs did the math. He didn't make reactions safer — he made them calculable. Measure a couple of properties, and the result was known before the beaker left the bench. Chemistry stopped guessing.

But we still run business like alchemists. Especially with AI. We can sorta feel which experiments might be dangerous, but we can't size them. So we do the two alchemist things: mix and pray, or wrap projects in so much bubble wrap nothing moves.

In the 1870s, bank robbers stopped cracking safes and started kidnapping bankers. 

When a combination lock was too hard to bypass, bank robbers went around it. Grab the manager at home, walk them to the vault, make them dial it open. The safe was secure. The person who knew the combination wasn’t.

A locksmith named James Sargent saw the real problem. The vault didn't need a tougher lock. It needed to be something even the right person couldn't open on command. In 1873, he wired a combo lock to two kitchen clocks. It wouldn't open for anyone until a set hour the next morning. Not a thief. Not the manager. The combo didn’t matter, the vault was dead until nine.

Now, you kidnap the banker and you've grabbed someone who can't help you. The secret in his head stopped being worth taking.

We're back at that problem with AI agents.

MALFUNCTION 54 flashed forty times a day, so the operators ignored it. Until people started dying.

Japan Railway solved that exact problem a century ago, and the fix looks ridiculous…

Rip out trigger words and em dashes and detectors can still spot AI writing 93% of the time.

AI’s tells are hidden in the structure. Here are six structural markers of AI writing, and how to avoid them.

Researchers at U of Maryland scored 61,608 stories to find what separates human writing from AI. When they fine-tuned a new model to fake human style, detection fell from 97% to 3%. But when they threw out “style” and judged the writing on how a story was built, the machine still got caught. 

Read more for six rules from the data…

Bite into a Kit Kat, and you’re eating failure. Between each perfect wafer is a layer of ground up rejects. That’s exactly how we should build agents.

A market beats a committee. And yet that isn’t how we run our businesses.

Jane Street is a quant trading firm that made $13M per employee last year. They're famously strange. They built a realtime auction to allocate GPU compute using a currency called “Hive Bucks." Anyone can bid, outbid, or kill a project they think is wasting cycles. No approval. No meeting. The market clears itself.

Most companies don't have a compute problem. Yet. But they do have constraints. And the most common solution is a State Planning Commission with better catering.

Galileo hid his greatest findings in a secret code, and it held back science for generations. Now, Gary in Accounting is doing the same thing.

When playgrounds install softer surfaces, kids break MORE arms. Kids see rubber and think they're safe. So they climb higher and jump from places they wouldn't have before.

But broken arms aren't broken necks. Good playground design isn't about eliminating injury, it's about padding the things that cause broken necks, and leaving enough real risk so that kids stay and learn to climb.

If we pad the floor, risk doesn't disappear.
It relocates.
Same thing happens with AI governance.

In 1956, the FBI foiled the biggest bank robbery in US history — just five days before the robbers would have gotten off scot free. They survived six years of the FBI, but they didn't survive each other. 

The gang's rules were simple:
Don't touch the money, don't get arrested, don't talk.
Ride out the six-year statute of limitations and walk free.

They almost made it. What broke them wasn't a detective. It was the split.

I see the same squabble today over who gets credit for AI gains. These fights don’t just poison one initiative, they kill the transformation that’s supposed to follow. 

In 1986, scientists worried runaway nanotech might convert the entire earth into Gray Goo. And that’s exactly what it looks like inside some of my clients.

Phrase of the week: "AI sprawl."
When everyone can vibe code an app, each solution becomes more goo, slowing down the company. How long before tech and org debt eats the business?

Brex may have just open-sourced an antidote.

UnitedHealth Group ran an AI with a 90% error rate. On purpose.

That's what the class action says. The nH Predict algorithm, built on 6M patient records, would automatically override physician recommendations. If patients appealed, they won 9 times out of 10. The courts are now forcing UnitedHealth to answer: Did they build governance around a model they knew was wrong? The answer, from what's emerged in discovery, appears to be No.

That's what ungoverned AI looks like.

Anthropic’s Economic Index just measured millions of Claude chats and published what people actually use AI for at work. Their finding: 49% of U.S. occupations now have at least a quarter of their tasks being handled by AI.We did the math on what those tasks cost…

The inventor of the printing press died penniless.

Not because the press didn't work. It was spectacular. Gutenberg produced in days what took scribes months. He solved the hardest part of the problem…and never saw it coming when his solution became the New Problem.

He flooded his local market with cheap books. Prices collapsed. His books had no way to compete with all the expensive books in faraway towns. He'd revolutionized production but ignored distribution. His breakthrough created the crisis.

Three teams that threw away their old systems to work AI-first.

Not AI-assisted. Not "we gave everyone Copilot." Threw away the process and started over.

There's a surgery called an osteotomy. When a bone has healed wrong, it's functional enough to walk on but misaligned the only fix is to re-break it, set it correctly, and let it heal from scratch. You can't correct the alignment from the outside.

Most workflows are that bone. They healed around fax machines, email chains, weekly standups, and quarterly planning cycles. Layering AI on top doesn't fix the alignment. It just makes the limp a little faster.

In 1923, Henry Ford owned 75% the American tractor market. By 1928—5 years later—he walked away a failure. 

Problem was, Ford’s tractor was just a mechanized plow. He simply replaced the horse with an engine.

John Deere saw something Ford missed:…

In 1921, Billy Mitchell sank an ‘unsinkable’ battleship with an airplane. The Navy's response? Courtmartial him, and promote the admirals who said he couldn’t do it.

"A committee where 10 people have to say yes is the opposite of innovation." That's Coinbase CEO Brian Armstrong. Last year, one innovation bet netted them $1.35B in revenue.

Here's the system that made it possible—and why most companies could never replicate it.