The Failures You Never See

There's a kind of AI failure you never see, because it doesn't look like failure. The answer is fluent, confident, complete. And quietly wrong.

The obvious mistakes are easy. You catch those. The dangerous ones wear the exact same voice as the correct ones: a fabricated detail slipped in among the true ones, a requirement silently dropped, a small contradiction with something it told you three messages ago.

None of it announces itself. That's the whole problem. The tone is identical whether the model is right or wrong, so the tone tells you nothing.

I spend my days hunting these, and the lesson keeps repeating. The skill isn't spotting a model that sounds wrong. Anyone can do that. It's learning to distrust one that sounds right.