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When teams start using AI in QA, the first results often feel almost great. You ask for a Playwright test, the model generates something reasonable, and it looks like you’ve just accelerated your entire testing process overnight - that feeling rarely lasts. After a few iterations, cracks begin to appear: failures are “fixed” in ways that don’t actually work, flaky tests start to multiply instead of disappear and slowly confidence in the system begins to erode. At that point,

You know how testing can feel like a never-ending repetitive actions of writing the same scripts, updating tests after every feature...

Working in tech is often framed as a dream job — solving hard problems, shaping the future, and building cool stuff. But in fast-paced...

In today’s fast-paced agile environments, selectively rolling out new features is more than a convenience—it’s a necessity. Feature flags...