Why temperature=0 Does Not Make AI Agents Deterministic and How to Test Them

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A technical article on DEV Community explains why AI agents can produce different outputs even when temperature is set to zero, a setting commonly assumed to eliminate randomness. The variation stems from floating-point arithmetic on GPUs, request batching by model providers, and infrastructure changes such as hardware swaps or model re-quantization. Tests that rely on exact string matching therefore fail intermittently even when the agent is functioning correctly, eroding developer trust in test results. The article recommends shifting assertions away from literal text matching toward verifying output structure, required fields, data types, and valid values. Using JSON Schema validators like Ajv is proposed as a practical approach to writing resilient, semantics-focused tests for non-deterministic AI systems.

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