The people who know AI best are saying: use a little less

OpenCode is an AI coding tool used by nearly a million developers every day, growing tenfold in four or five months. Its co-founder Dax said in a podcast interview: "Honestly, I think we need to use a bit less AI." The host paused. Dax continued: "No competitor has beaten us by being better at using AI. The users we have came because we had better quality, and that quality came from slowing down." He wasn't alone. Spotify's CTO set a firm rule: AI was fine to use, but quality standards had to hold. The result was slower deployment, but nothing shipped broke. GitHub took the opposite approach, letting AI-merged code accumulate, and recently every user's pull requests disappeared for over ten hours. AI pushed code output up sixfold. Bugs followed. Around the same time, AI drove the cost of explaining things down to almost nothing. Give a child any concept, and AI can rephrase it ten ways, calibrate to their level, give instant feedback, more patient than a tutor and cheaper than cram school. You'd expect parents to feel relieved. Many don't. Because while AI made giving answers cheaper, knowing where the child is stuck didn't come down in price. Two different worlds, same pattern. AI speeds up output, but judgment, whether what came out is actually right, only becomes more valuable. More code doesn't help if no one can tell which pull requests to trust. More explanations don't help if no one can tell where a child's understanding broke down. AI gives speed. What it multiplies is the judgment you bring in. Dax, at the end of that interview, said: "We need to think more, build less, and build what actually matters." When he finished, the agent in the corner of his laptop was still waiting for his next command.