[bee_rider]

Can we make an LLM do it?

“You are a cranky senior software engineer who loves to nitpick change requests. Here are your coding standards. You only sign off of a change after you are sure it works; if you run out of compute credits before you can prove it to yourself, reject the change as too complex.”

Balance things, pit the LLMs against each other.

[postflopclarity]

I do this all the time. I pass my code into "you are a skeptic and hate all the code my student produces: here is their latest PR etc.. etc.."

[osn9363739]

I have devs that do this and we have CI AI code review. Problem is, it always finds something. So the devs that have been in the code base for a while know what to ignore, the new devs get bogged down by research. It's a net benefit as it forces them to learn, which they should be doing. It def slows them down though which goes against some of what I see about the productivity boost claims. A human reviewer with the codebase experience is still needed.

[mywittyname]

Slowing down new developers by forcing them to understand the product and context better is a good thing.

I do agree that the tool we use (code rabbit) is a little too nitpicky, but it's right way more than it's wrong.

[bee_rider]

I don’t use any of these sorts of tools, so sorry for the naive questions…

What sort of thing does it find? Bad smells (possibly known imperfections but least-bad-picks), bugs (maybe triaged), or violations of the coding guides (maybe known and waivered)?

I wonder if there’s a need for something like a RAG of known issues…

[baq]

GPT 5+ high+ review bots find consistently good issues on average for me, sometimes they’re bogus, but sometimes they’re really, really good finds. I was impressed more than once.

[filoeleven]

This response fails entirely to answer the question.

[jjmarr]

We do this at work and it's amazing.

[cm2012]

This would probably catch a lot of errors