The pitch for AI-assisted development is usually about speed: a model can draft a component, a migration, or a whole feature in the time it takes to write the prompt. That part is true, and it’s genuinely useful. What it doesn’t do on its own is guarantee the result is correct, secure, or maintainable six months from now.
In practice, AI is excellent at the first draft — scaffolding a component, wiring up a form, refactoring a messy function into something readable. It’s much less reliable at the decisions that don’t show up in the diff: whether an edge case matters, whether a dependency is worth adding, whether this is the right abstraction for where the product is going next.
That’s the split we work with. The model handles implementation velocity. An engineer reviews every change for the things a model can’t reliably judge — security implications, architectural fit, and whether the code is something a human could debug at 2am without the original context. Nothing ships without that review.
The result isn’t ‘AI wrote our website.’ It’s closer to a senior engineer working with a very fast, occasionally overconfident pair programmer — and still being the one who signs off on what goes to production.