The Cases That Don’t Exist

How GenAI is not yet ready for law

In 2023, a New York lawyer named Steven Schwartz filed a brief in a routine personal-injury case against an airline. The brief cited a half-dozen helpful precedents. The precedents did not exist. Schwartz had asked ChatGPT to find supporting cases, and ChatGPT — being a machine that produces plausible language rather than true statements — invented them, names and citations and quotations and all, then cheerfully assured him they were real when he asked. The legal world treated Mata v. Avianca as a freak show: a cautionary tale about one careless lawyer. An embarrassing one-off.

It was not a one-off. It was the first crack in a dam.

By the end of 2025, a researcher in Paris named Damien […]

Apple Gave Siri Hands

WWDC answered whether your assistant is private. It never answered whether it’s telling the truth — and Apple just gave it hands.

The smartest thing I’ve read about Apple’s WWDC didn’t come from Apple. It came from an analyst named Nate B. Jones, who watched the same keynote everyone else did and noticed that the real story wasn’t whether Siri had finally gotten smart. The real story, he argued, is a land grab over what he calls the trusted action surface — the place where AI actually meets your work, touches your apps, and is handed permission to do something. There are two great bottlenecks in AI, he points out: raw compute, which is Jensen Huang’s kingdom, and the trusted surface where intelligence becomes useful, […]

Two Brains

For two months this column has been describing an architecture. Here’s the part I kept in the footnotes: I’ve been building it.

I owe you a confession, and then I owe you a demonstration.

The confession first. For weeks I’ve written about why the machines can’t tell truth from plausibility — why detection isn’t a strategy, why fluency isn’t fidelity, why the only honest path is to separate the saying from the knowing and import truth from somewhere you can actually check. I’ve signed each of those columns with a one-line note that I co-founded a company “built on this conviction.” That little disclosure has been doing a lot of quiet work. These columns were not the musings of a neutral observer. They were the argument […]

Detection Is Not a Strategy

Every few weeks, someone announces a tool that detects AI hallucinations. A startup, a research lab, a hyperscaler bolting a “trust layer” onto its chatbot. The release uses the word “guardrails.” Everyone nods. Another brick in the road to safe, reliable AI.

I want to argue that we are cheering for the wrong thing — that hallucination detection, however clever, cannot be the strategy. It can be a backstop. It can be a monitor. It cannot be the plan. And the reason is older than computing.

Start with the trap at the center of the whole idea.

To catch a hallucination, your detector has to know the right answer. Sit with what that means. The original model produced a confident falsehood because it did not have the […]

Knowing What You Don’t Know

Why the next real breakthrough in AI isn’t a bigger brain — it’s a machine that can admit ignorance.

A reader caught me out.

Last column I argued that the great AI buildout — the hundreds of billions pouring into data centers and the GPUs that fill them — is aimed at the wrong layer. We are spending as if the bottleneck were the size of the model’s brain, when the real bottleneck is getting the right information in front of it. Cheap retrieval, I said, not expensive cognition.

A reader replied, pointing out the name Jevons.

In 1865, a young English economist named William Stanley Jevons noticed something strange about coal. As steam engines got more efficient — as they wrung more work out of every lump […]