8 posts across Directing AI, Work & Judgement
Simon Willison endorsed a rule blunt enough to actually follow: write it yourself, then use AI only to flag problems, never to supply the fix. Two studies published the same week explain why the line matters more than it sounds.
4 min readA viral Hacker News essay, a tripled university failure rate, Anthropic's own usage dashboard, and OpenAI's internal delegation data didn't coordinate with each other — but read together they describe the same mechanism, and the same early check for catching it.
5 min readAnthropic launched a usage dashboard that asks 'What's one thing you want to keep doing yourself, even if Claude could do it faster?' It's the first time a major AI provider has built overuse prevention directly into its product.
5 min readA quarter of OpenAI employees now run four or more agents simultaneously each week. The people doing it most effectively are domain experts, not engineers — and as delegation grows, the risk of losing the ability to judge the output grows with it.
5 min readSkills decay when they go unused, and AI makes it easy to stop using several at once. That may be a fine trade — but it should be a decision, not a drift. Here's how to choose deliberately.
5 min readProfessional judgement was built by years of doing work that AI now does in seconds. Nobody misses that work — but the training it provided was real, and something has to replace it.
6 min read35.3% of Berkeley CS 10 students received failing grades in Spring 2026, up from under 10% historically. The pattern that caused it — using AI to skip the thinking rather than do the thinking — shows up in professional work too. Here's how to avoid it.
5 min readA developer's post about losing his coding skills after two years of AI-assisted work hit 541 points on Hacker News. The pattern he described isn't a developer problem. It's a professional skills problem — and there's a three-question test for catching it before it catches you.
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