What’s missing from this AI-driven E2E testing workflow?
I’m designing an AI-assisted Playwright workflow for E2E/regression testing and want expert criticism before we push it further.
High-level flow:
• AI explores the UI
• AI generates scenarios and Playwright tests
• AI runs tests and gathers evidence
• AI attempts self-healing on failures
• Humans validate business correctness and approve bug reporting
• The result is a regression-ready suite
This sounds good on paper, but I’m sure there are practical issues I’m underestimating.
My current assumptions are:
• the biggest risk is weak business-intent coverage
• the first failure mode is flakiness / shallow assertions
• self-healing should only fix locators and synchronization, not assertions or expected outcomes
• AI-generated tests should require human review before entering the stable regression suite
For those with deep QA / automation experience: which of these assumptions do you agree or disagree with, and what am I still missing?
I’d really appreciate blunt feedback.