Generative AI for PRs

Posted Nov 13, 2025 15:26 UTC (Thu) by khim (subscriber, #9252)
In reply to: Generative AI for PRs by emk
Parent article: About KeePassXC's code quality control (KeePassXC blog)

> It occupies roughly the same space as a diligent intern.

Can you clarify? Diligent intern is someone you spend time on today, to, hopefully, get a good colleague in the future.

I fail to see how spending your time on LLM can be a good time investment.

> If you give it clear instructions, achievable goals and sufficient feedback, it can write a lot of OKish code quickly.

There's a problem with that idea: it's actually faster to write code than to give a clear instructions, achievable goals and sufficient feedback if your code doesn't include bazillion copy-paste lines that are more-or-less identical.

And if your code does include bazillion copy-paste lines then the proper way is to find a way to not have that code duplication and not bring intern or LLM into your project.

I guess both intern and LLM can be useful for tests writing, where some copy-paste may be better to ensure that each individual test is simpler, in isolation… but that's it.

> This includes things like property tests, which can easily generate a few million test cases.

And how is that in improvement? Every time I need to pass VK-GL-CTS I want to cry because there are million tests that only are good to report ten thousands of errors if one mistake is made. So I need to spend thousand times more resources to get the exact same effect.

And it's like that everywhere: most of the “improvements” from the use of LLMs are net negative. They are doing and improving things that are not needed in the first place.

If, once a while, in the pile of garbage generated there are something nice it's a good thing, sure, but most of the time it's just garbage!