How to Monitor AI Agent Drift in Production

AI agent drift is the silent degradation of an AI agent's behavior in production without any code changes, caused by model updates, data schema changes, or compounding shifts across dependencies. Traditional monitoring (uptime, error rates) fails to catch drift because the agent still runs without errors but produces subtly incorrect outputs. The article introduces the 'golden output' pattern as a practical approach to monitor the contract between an agent and its dependencies rather than trying to verify output correctness directly.