Detect Silent Drift in AI Agent Decisions Before Users Complain

AI agents can degrade in decision quality without errors, as model updates or traffic shifts cause silent drift. The author proposes instrumenting decisions with attributes like step, decision type, and tool name to measure quality distributions. This approach enables baselines and alerts to catch regressions before they impact users.