> I have anecdotally found this to be true as well, that an LLM greatly accelerates my ramp up time in a new codebase, but then actually leads me astray once I am familiar with the project.

How does using AI impact the amount of time it takes you to become sufficiently familiar with the project to recognize when you are being led astray?

One of the worries I have with the fast ramp-up is that a lot of that ramp-up time isn't just grunt work to be optimized a way, it's active learning, and bypassing too much of it can leave you with an incomplete understanding of the problem domain that slows you down perpetually.

Sometimes, there are real efficiencies to be gained; other times those perceived efficiencies are actually incurring heavy technical debt, and I suspect that overuse of AI is usually the latter.