Where Does Truth Live in AI-Generated Code?

The Problem Isn't Tests—It's Authority Talk about AI-generated code long enough, and you'll hit this question. "Tests pass, so what's the problem?" Not wrong. But it misses the core issue. In AI-generated code, the real question is: who decides 'this is correct'? Tests? Reviewers? Another LLM? None of them. This isn't about improving accuracy. It's about where the authority to declare truth lives. What We're Actually Doing 1. Trusting Tests "Tests pass, so we're fine." In practice, this translates to: "Wechecked a few cases and nothing broke." This pattern repeats. Especially after adding LLMs. Most teams have been here. Tests sample. They miss edge cases. They rarely cover invariants. So this happens: All tests pass. Production breaks. Not an exception. A structural result. Test passage is observation. Correctness is a property. 2. Trusting Human Review "A person reviewed it, so it's fine." Even less stable. Humans don't scale. LLM code output explodes. Reviews drift toward "looks abo