There is never a right time to regulate a powerful technology. I know this because the people building it have patiently explained it to me at every single stage, and the explanation always fits the moment perfectly. Early on, rules are premature. Later, rules are pointless. You have to admire a schedule with no office hours.

Phase one sounds like this: it’s too early. The technology is young, nobody knows what it will become, you’d be writing laws about science fiction. Regulate now and you’ll freeze the wrong picture, punish the wrong things, embarrass yourselves in front of the future. And honestly, this is not a stupid argument. Writing detailed rules for a thing that barely exists is genuinely hard, and history is full of laws that aged like milk.

Phase two sounds like this: it’s too late. The technology is everywhere now, wired into the economy, load-bearing. Rules at this point would break things people depend on, and anyway the genie doesn’t do refunds. Also not a stupid argument. You genuinely can’t un-ship what a billion people use every day.

Here’s the trick, and once you see it you can’t unsee it: there is no phase between them. No morning where the industry announces, right, it’s no longer too early and not yet too late, please regulate us this quarter. The window where rules would be just right turns out to have a width of exactly zero. Which is a remarkable coincidence, given who’s holding the tape measure. The last technology wave ran this exact play, start to finish: too early to burden the scrappy startups, then one merger montage later, too late to restrain the giants. The play works. That’s why it’s being run again.

The timing trap has a cousin: the moving goalpost. Every proposed trigger for action migrates the moment it’s approached. We’ll worry when the systems can do X. Then they do X, on a Tuesday, to mild applause. And suddenly X was never really the dangerous part, the serious threshold is Y, obviously, always was. Then Y arrives. You can watch this happen in real time if you keep notes, which almost nobody does, because the goalposts move at the speed of forgetting. That’s not risk assessment. That’s retreat with a whiteboard.

Now the honest kernel, because the trap only works by containing one. It’s true that you can’t write the perfect capability rule early. But watch the sleight of hand: we can’t write the perfect rule yet quietly becomes we should write no rules yet. Those are different sentences. You don’t need to know the final speed limit to require brakes, licenses, and insurance. Every mature field handles deep uncertainty with process rules instead of content rules: test before release, report incidents, keep records, carry liability for harm. None of those need to predict the future. They just need the future to be accountable when it shows up. The too-early argument defeats detailed content rules, fair enough. The playbook then quietly aims it at all rules, and hopes you don’t notice the upgrade.

The cruelest part is that both phases are self-fulfilling. Every year spent agreeing it’s too early is a year the technology integrates deeper, which strengthens next year’s case that it’s too late. The trap doesn’t just describe the window closing. It closes it.

Tonight’s exercise is an archaeology dig. Find the oldest confident prediction you can remember about what AI would never be able to do. Write stories, pass exams, hold a conversation, whatever your memory serves up. Notice that it happened years ago, quietly, and that no alarm sounded and nothing paused. Then ask yourself which of today’s it-can’t-possibly claims you’re currently treating as load-bearing walls. Because somewhere on a whiteboard, they’re already being redrawn.