# What is regression testing for an AI agent?

Regression testing for an agent is re-running a fixed set of cases, each with an expected behavior, after every change, to catch behavior that used to work and stopped.

It differs from a unit test in what it asserts. The same input doesn't produce the same output twice, so a case is judged rather than asserted, and the result is a pass rate over repeated runs instead of one green tick. [A passing unit test doesn't rule a regression out](/answers/regression-detection/does-a-passing-unit-test-rule-out-a-regression): it checks the code path, not what the model did once it got there.

The cases come from production. A failure that already happened is a real failure rather than a guess at one, and [turning a failed turn into a standing check](/answers/failure-replay/how-do-i-turn-a-failed-production-tool-call-into-a-regression-test) is how the set grows.

What it cannot catch is a change it has nothing to run against, since [a regression can arrive with an empty diff](/answers/regression-detection/can-a-regression-happen-without-a-code-change).

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Source: https://tessary.ai/answers/regression-detection/what-is-regression-testing-for-an-ai-agent
More on Regression detection: https://tessary.ai/answers/regression-detection
From Tessary, agent reliability for AI agents in production: https://tessary.ai