AI Agents Excel at Exploratory Testing but Fall Short for Regression Suites

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AI agents have proven effective for exploratory testing by dynamically navigating interfaces, reacting to unexpected states, and investigating bugs without fully predefined steps. However, regression testing demands repeatable, documented action sequences and consistent checks so that results across multiple runs can be meaningfully compared. When an agent adaptively chooses alternate paths or accepts different signals as proof of success, it undermines the comparability that regression testing requires. Experts argue teams should use AI agents for ambiguous, one-off, or investigative tasks while investing in structured test assets for workflows that must be verified before every release. The key question for testing teams is not whether to use agents or automation, but which work benefits from flexibility and which requires repeatability.

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ProgrammingDEV Community ·

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