How to QA AI-Generated Code Before Production
AI-generated code should pass functional, regression, security and dependency checks before production. A working demo is only the first gate.
Read experimentAI can accelerate coding and debugging when the task is bounded and testable. This section follows the path from generation and diagnosis through regression control and production QA.
AI can write working code, but reliability depends heavily on scope, context and testing. Here's what we learned using it on real projects.
Read the starting experimentAI-generated code should pass functional, regression, security and dependency checks before production. A working demo is only the first gate.
Read experimentNew code gives AI freedom. Existing code requires preserving relationships it may not see. Here's why modification can be deceptively harder.
Read experimentExact error messages give AI concrete debugging evidence. We found they work far better than simply saying the code doesn't work.
Read experimentAI can solve a local code problem while damaging shared behavior elsewhere. Here's why regression testing became part of our AI coding workflow.
Read experimentA screenshot can give AI valuable evidence about a broken website layout. We tested when visual debugging works and when the underlying code is still necessary.
Read experiment