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Testing AI Agents
Unit tests, golden tasks, record/replay, and evals that catch regressions before prod does.
- Testing AI Agents: Production Testing Strategyβ β βHow to design a testing strategy for AI agents using unit tests, evals, regression testing and runtime monitoring.
- Eval Harness for AI Agents: Repeatable Evaluationsβ β βAn eval harness lets you run repeatable tests for AI agents and compare results across versions.
- Golden Datasets: Reliable Test Data for AI Agentsβ β βGolden datasets contain curated test cases used to evaluate agent behavior consistently.
- Unit Testing AI Agents: Testing Agent Logicβ β βHow to write unit tests for agent logic, reasoning steps and tool execution.
- Tool Mocking and Fault Injection for AI Agentsβ β βMock tools and inject failures to test how AI agents behave when APIs return errors, latency or outages.
- Regression Testing for AI Agents: Prevent Behavior Driftβ β βRegression testing ensures new agent versions do not break existing behavior.
- Replay and Debugging for AI Agentsβ β βReplay past agent runs to debug failures and understand why an agent made a specific decision.