What's worse in backend AI: a wrong answer, or a dependency that doesn't exist in your project?

One failure mode we keep noticing is the model recommending a package, module, or integration that sounds plausible but isn't really there.

The answer feels smart, but it creates even more cleanup.

Have you run into that more than generic architecture mistakes?