How to Monitor AI Agent Drift in Production

How to Monitor AI Agent Drift in Production You deploy an AI agent on a Tuesday. It works perfectly. By Thursday, something is off — the outputs are subtly different, a downstream API changed its response format, or the LLM provider silently updated their model weights. Your agent is still running. It's still returning 200s. But it's drifting. This is the problem nobody warns you about when you ship autonomous AI systems: they degrade silently. What Is AI Agent Drift? Drift is when an AI agent's behavior changes over time without any intentional modification to its code. Unlike traditional software bugs, drift doesn't throw errors. It doesn't crash. It just... shifts. There are three main flavors: Model drift happens when the LLM behind your agent changes. OpenAI, Anthropic, and Google all update model weights, fine-tuning, and safety filters on their hosted models. Your agent's prompts haven't changed, but the completions have. A prompt that used to produce structured JSON now returns