[vineyardmike]

I've seen an uptick in LLM generated bug reports from coworkers. A employee of my company (but not someone I work with regularly) used one of the CLI LLMs to search through logs for errors, and then automatically cut (hundreds!) of bugs to (sometimes) the correct teams. Turns out it was the result of some manager's mandate to "try integrating AI into our workflow". The resulting email was probably the least professional communication I've ever sent, but the message was received.

The only solution I can see is a hard-no policy. If I think this bug is AI, either by content or by reputation, I close without any investigation. If you want it re-opened, you'll need to IRL prove its genuine in an educated, good-faith approach that involves independent efforts to debug.

> "If you put your name on AI slop once, I'll assume anything with your name on it is (ignorable) slop, so consider if that is professionally advantageous".

[theshrike79]

That's just stupid.

IF you want LLM code reviews, there are bots for codex, copilot, claude etc that plug straight into Github PRs and review the code automatically.

Some of them are actually useful, some just plain wrong and some are subtly wrong and you need to spend some time figuring out whether it's right or wrong :)

IMO it's still a net positive because LLMs tend to pick up really weird subtle errors that humans easily gloss over.

[PeaceTed]

Alas this is an issue of LLM generated code. Increased productivity but lessened understanding. If you can increase productivity while also increasing understanding then that will be a decent middle ground.

All comes down to accountability.