AI Is Writing Your Code, But Who's Testing It?

InnovationAI Is Writing Your Code, But Who's Testing It?ByKhurram Javed Mir,Forbes Councils Member.for Forbes Technology CouncilCOUNCIL POSTExpertise from Forbes Councils members, operated under license. Opinions expressed are those of the author. | Membership (fee-based)May 11, 2026, 07:45am EDTKhurram Mir is the founder of Kualitatem and Kualitee, focused on software quality engineering, product development & tech entrepreneurship. gettyFor the past three years, I've watched a pattern repeat itself across software engineering organizations—from early-stage startups to publicly traded software companies. The team adopts an AI coding tool. Velocity climbs, leadership celebrates and QA headcount gets quietly frozen or reduced. Then, six to nine months later, a production incident exposes a logic error that looked perfectly reasonable, passed review and sailed through the rest of the suite.GitHub research found that AI-assisted developers ship code up to 55% faster. However, output speed and output reliability aren't the same measurement, and most organizations are only tracking one of them.Those cutting QA investment argue that AI writes cleaner code than rushed humans, so there's less to catch. That argument misunderstands what AI actually does.What AI Actually Does To Your CodebaseThe failure mode here isn't obvious, and that's precisely what makes it dangerous.AI code generators are pattern completion engines. They're extraordinarily good at producing code that resembles correct code. They're not reasoning about your business logic, your edge cases or the system-level assumptions that a developer—who has since left—baked into your architecture three years ago. The output looks clean because it's syntactically fluent, not because it's contextually accurate.The practical consequence is what I call the "looks right" problem. In code reviews, there's social pressure to approve. When AI-generated code...