That already happens here. I am old dev who was the goto guy for people with certain business and technical questions. Not anymore (which is part good, as I'm interrupted much less, and part bad, as sometimes they regard the wrong answer as truth).

I think you hit the nail on the head, it's probably right, most of the time. Or, maybe 89% right, 91% of the time.

The more I use AI, the more I see mistakes. I've noticed others see these same mistakes, correct them, then when queried say "Oh, it gets it right all of the time!". No, having to point out "you got this wrong, re-write that last bit" isn't "getting it right". And it's not that the code is wrong overtly, it's subtle. Not using a function correctly, not passing something through it should (and the default happens to just work -- during testing), and more. LLMs are great at subtle bugs.

So moving forward with this isolation you mention, ensures that maybe the guy in the company, the 'answer guy' about a thing, never actually appears. Maybe, he doesn't even get to know his own code well enough to be the answer guy.

And so when an LLM writes a weird routine, instead of being able to say "No, re-write that last bit", you'll have to shrug and say "the code looks fine, right?", because you, and the answer guy, if he exists, don't know the code well enough to see the subtle mistakes.

In a large codebase it‘s probably next to impossible to get people who fully understand the code to explain it to you with unerring accuracy.

AI can get a pretty good picture, near instantly, whenever you need it.

It’s not just competent-sounding, it is reasonably competent, and certainly very useful for tasks like that.

That's a valid point. Dev/team member isolation, not a great environment to build