[mingusrude]

> ...badly architected, often redundant, feature-bloated code which always looks good, even upon earnest review, but actually sucks and becomes extremely difficult to maintain in ways which are not obvious in code review.

I can only judge from my own experience but with or without LLMs, these are the codebases that I have worked with during most of my career. To me, much of the question is whether LLMs produce worse code than the me and my colleagues have done in the past and I don't think that's the case. It is however very common that people hold LLMs to a higher standard than human colleagues and then it's not a useful comparison.

[torginus]

LLMs can produce bad code in ways no human ever would. I remember working on headscratcher problem of walking a tree while gradually building up state, and since LLMs are supposed to be good at algorithms, I asked Claude.

It came up with a correct LC-hard tier solution that involved dynamic programming, and was essentially an unreadable dense mess that was impossible to reason through as a human.

It worked, but it was so bad, that I sat down and realized after a bit that with maintaining a small cache, and being very particular about how the nodes are traversed, I reduced the solution to like a 10 line modified DFS, that I could understand.

[socalgal2]

I’ e written bad code and I’ve reviewed bad code by other humans. In both of those cases the code gets re-written. In the first the reviewer tells me the code is hard to understand, can it please refactor. In the 2nd I tell the person I’m reviewing the same thing, maybe with some suggestions.

I do the same with the LLM. I tell it that solution is convoluted and hard to understand, if I have a concrete suggestion I suggest one, otherwise I ask it for ideas. We get there just like I do with humans

[x3ro]

In my experience, even if the code is not worse, there is so much more of it that people quickly stop understanding what is going on. Now you could argue „the LLM knows“, but that comes at an insane token cost, even if it works well.

This is in the interest of big AI companies: if they quasi-monopolize the skills entire sectors of the economy need in order to function, that will be great (for them).

Everyone keeps comparing this to compilers, but I don’t need a multiple-hundred dollar subscription to use LLVM. And people didn’t stop understanding how computers work either, just because they used C. And yeah, maybe local LLMs will become the norm, and I hope so. But market forces (hardware prices) certainly are working against that right now.