Excerpt: AI-generated tests can raise coverage and still miss the failure that matters. Strong assertions, state checks, and deliberate review are what turn automation into trustworthy software quality. #softwaretesting #ai #qualityassurance #pytest #devtools #testing

AI is changing how developers write code, review pull requests, and generate tests. In many teams, that shift feels like a productivity breakthrough. A coding assistant can scaffold test cases in seconds, suggest edge conditions, and even push coverage numbers higher with very little manual effort.

But there is a quieter problem hiding behind those gains: a test can pass, coverage can improve, and the bug can still survive.

That tension matters in real software projects. It is especially important in workflows where teams ask AI tools to