Agent Drift

Agent drift is the gradual decline in an AI agent’s performance over time as data, models, or the surrounding environment change.

An agent that scored well at launch can degrade as inputs shift, dependencies update, or the underlying model changes, so a single evaluation expires.

Periodic re-evaluation against a sealed benchmark detects drift and keeps a published score honest.