Two developers can both say 'I use AI tools' in an interview and mean completely different things. One pastes an error message into a chat window, copies whatever comes back, and moves on without reading it closely — that code tends to work right up until it doesn't, usually in production, usually at the worst time, usually in a part of the system nobody thought to double-check because it 'already worked.' The other uses the same tools to skip the tedious first draft of a function they already understand deeply, then reviews, tests, and reshapes the output with the same scrutiny they'd apply to their own code, catching the subtle assumptions an AI model has no way of knowing are wrong for this specific project. The output might look nearly identical in a five-minute demo. It does not look similar six months later, when one codebase is still holding up under real usage and the other has quietly accumulated the kind of bugs nobody can quite explain.