I made myself a promise last week that the next newsletter wouldn't be about OpenAI or Anthropic. I lasted until Tuesday.

That's when Anthropic released Fable 5, their first public model from the new Mythos tier, the scary-powerful one they said was too smart to release back in April and built a whole safety initiative around. For three days my feed was just people building things they couldn't believe they'd built. Then Friday, the US government sent a letter, and by Saturday it was gone for everyone (my weekend plans included).

I didn't even get to write about it before it stopped existing.

A company spends months saying its model is too dangerous to release, ships a careful version anyway, and then watches the government take it completely at its word.

Anthropic said the order was an export rule blocking any foreign national from using Fable or Mythos including its own foreign staff. To comply, they switched it off for everyone. The reason given was national security. The specifics, by their own account, were never spelled out.

Their guess is that someone found a jailbreak (a way to get a model to do something it's built to refuse). Which means you can ask it to read some code and point out the flaws. Which every security team does on a normal day, and other tools already do with no trick at all.

So why pull the whole thing?

A few theories are going around. The Neuron shared a Wall Street Journal report that Amazon researchers flagged it to officials. Some people point to an old Anthropic–government feud. And some just point at the meme: tell everyone your AI is dangerous for long enough, and don't be surprised when they believe you. Could be a bit of each.

What's clear, though, is the precedent. As far as anyone can tell, it's the first time the US has pulled a frontier model after it went public. And what's worth your attention is not the news itself, but what it says about the future of your own work.

Window into the Future

The best thing I read all weekend wasn't really about the ban. It was Daria Cupareanu on what she built in the 72 hours before it.

She's not a developer. For months she'd been trying to get her own numbers out of Substack, which doesn't make that easy, and had given up. This time she just described what she wanted, walked away, and Fable built the whole dashboard for her. It's live on her site now, refreshing every morning.

She's in Romania. So she's also one of the people who lost it on Saturday.

According to Greg Isenberg, the smart move from here is to get good at local models. The ones you download and run on your own machine so nothing can ever switch them off. He's right that it's a real option now. You can run capable models at home, and his thread walks you through how to start. Alex Finn went even further encouraging you to own your own compute, before that gets taken away too.

Bans aren't the only risk. Mike Taylor flagged that the cheap era is ending. Right now AI companies subsidise your subscription but that won't last. Microsoft just moved Copilot to pay-per-use, and some bills jumped from $39 to over $3,000 a month. Funny timing, then, that the UK government landed on the answer the same week. What Works for AI Upskilling in the UK studied ten organizations: Airbus, Roche, the NHS and found the same thing every time: the tools were never the problem. Everyone had tools. What mattered was building skill that sticks with you, not one product that's gone in six months. We were one of the ten (still can't believe it) and their numbers, not ours: one team went from 49% to 86% confident using AI.

Easy to say, though. So here are three ways to actually build that confidence with AI regardless of whichever model is up, down, or suddenly charging you:

1. Get good at the skill, not the tool. That 49-to-86 jump was people getting better at directing AI (like what to ask it and how to tell when it's wrong). That works in Claude, ChatGPT, anything. Last week I called it keeping the first and last mile. Try this: run the same task through two models this week, so switching feels normal.

2. Save your prompts, not just the answers. Most people lose their best prompts. You write something that works, get a great result, then never find it again. So when a prompt nails something, paste it into one running note. Five seconds now, and it saves you redoing the thinking later. The wording might need a tweak when you move to a new model, but you're starting from something that already works instead of a blank box.

3. Keep your own data. You know the sinking feeling when an app you relied on shuts down, changes its plan, or locks your stuff behind a paywall? Same risk here. Keep your files, your numbers, and your important docs somewhere you control. That's Isenberg's real point: own enough of your setup that losing one tool doesn't wipe you out.

That's it. None of this is about trusting AI less. It's what lets you lean on it harder, because losing any one tool stops being a big deal.