You've asked AI to write the code. Then spent an hour debugging it. Everyone has. Now imagine your entire test suite written that way - unmaintainable code that rots by the month. Multiply that by your team's size.

This was our reality when starting a large e2e test migration. The question wasn't whether engineers would use AI to write tests (they would). The question was: how do we stop this from becoming technical debt?

You'll leave understanding:
• Why AI-generated code becomes unmaintainable
• The mistakes we made that didn't survive contact with reality
• What worked, and more importantly, why it worked
• How the problem generalizes beyond just test automation
• What questions you should be asking about AI in your workflow

This isn't an AI hype talk. It's about the unglamorous work of keeping AI-generated code maintainable when everyone on your team is using it.

Target audience: Engineers, QA professionals, and tech leads using AI for code and worried about what happens next.