The Agent Reproducibility Paradox: Debugging Non-Determinism in Production

The Agent Reproducibility Paradox: Debugging Non-Determinism in Production Your production agent made a decision that broke something. A user reports a weird output. A compliance audit flags unexpected behavior. You investigate. You grab yesterday's logs. Same prompt, same tools, same input. You replay it locally. Different output. Welcome to the agent reproducibility paradox. The Root Problem: Agents Aren't Deterministic Traditional software bugs are deterministic. Same input + same code = same crash, every time. This is why debuggers work: you can reproduce the exact state, step through execution, find the bug. Agents don't work this way. Consider a single agent API call: Input prompt: "Process this transaction" Model: Claude 3.5 Sonnet Temperature: 0.2 Available tools: [payment_api, audit_log, fraud_check] Yesterday, this returned output_a . Today, same prompt, same config: The model version updated (Anthropic released a patch) The temperature seed drifted (framework version changed