[lukeschlather]

I can't speak to LLMs, but one of my first tasks was debugging a race condition in a piece of software. (I had no idea that it was a race condition, or even what part of the code it was in.) I spent months babysitting the service and reading the codebase. When I finally fixed the issue the source turned out to be a comment that said the opposite of what the code actually did. The code was a very convoluted one-line guard involving a ternary if / several || && statements. If the comment hadn't been there I think I would've read the code sooner and realized the issue.

Personally, I remove redundant comments AI adds specifically to demonstrate that I have reviewed the code and believe that the AI's description is accurate. In many cases AIs will even add comments that only make sense as a response to my prompt and don't make any sense in-context.

[jychang]

That's the kind of thing LLMs would HELP with, though.

Comments may go out of date, but LLMs can quickly generate comments that are up to date. LLMs are more likely to prevent the situation that you described.

> In many cases AIs will even add comments that only make sense as a response to my prompt and don't make any sense in-context.

Yeah, this is a common issue to be fair.