From Hype to Metrics: Real-World AI Adoption in Testing

AI-powered test case generation has long ceased to be an experiment and has become a distinct marketplace of tools. However, beautiful demos often conceal issues of quality, trust in the results, and actual effectiveness. In this talk, I'll share practical experience in implementing AI in testing processes: what has been accelerated, what approaches haven't worked, and why the number of tests generated isn't an indicator of success.

Using the development of TestWriter as an example, we'll explore key performance metrics, the "AI tests AI" approach, typical implementation mistakes, and the limitations of modern solutions. This talk will be useful for those who want to use AI in testing consciously, rather than following the latest hype.