[nielsbot]

Not advocating for AI code slop--but if AI coded software works correctly, maybe it doesn't matter? Except sometimes when a specialist will have to get involved. Not a perfect analogy, but most people don't write assembly these days--they have a compiler do that. Assembly still has a place, but it's a specialist task.

[tasuki]

> if AI coded software works correctly, maybe it doesn't matter?

The problem isn't the amount of code, it's how fitting/unfitting the abstractions are. Wrong abstractions are bugs in waiting. If there's much code with wrong abstractions, future change becomes difficult.

Source: me, I've created many bad abstractions and they led to much pain...

[josephg]

Yeah. Its kind of strange - claude is great at some tasks, but it seems really rubbish at coming up with good abstractions a lot of the time. I've often caught it making a conceptual mistake (like "X cannot do Y") - then spending hundreds of lines working around an issue that doesn't actually exist.

Its also really bad at inventing and leaning on invariants. I make rules in my code all the time - "by the time we get to path X, we know Y and Z are true.". In aggregate, these invariants make code simpler and easier to reason about. But claude doesn't do that. It just kind of - slops through and adds bespoke "just in case" workarounds all over the place. Every time I read through code its written - without fail - I find bad design / architectural choices.

Maybe mythos will change this. But for now I've slowed way down on my claude code usage. You can't build a skyscraper on a foundation of mud.

[toraway]

Yeah, I have a contract project for a webapp/integration to legacy Excel tool with an API endpoint for exchanging data with Excel. Over time, I notice issues or need to add functionality in the data processing and hadn't been closely watching the code changes Claude Code made to the API as long as it worked as expected/tests passed.

When I eventually read through the current state of the upload processing code it was like an absurd tree of checks on checks on fallbacks on triple checks added in response to whatever bug I reported in a bizarrely additive way and could be massively simplified (which would also make it less brittle to edge cases that then demanded more checks and workarounds).

The other issue is that for the upload API, there is documentation but not for every little bug or edge case so each time the model "wakes up" and loads everything into context it sees that crazy web of checks and edge cases as the only source of truth for the API so is hesitant to touch anything unless 100% necessary which then leads to more conservative behavior of additive code which makes the problem worse over time.

Codex seems a bit better but I still have to guide it towards proper abstractions/refactors to avoid that piling on cruft effect.

[lobocinza]

They have no illative sense like we do.

[SAI_Peregrinus]

More verbose code takes up more space in the context. It's harder for humans to review, but also harder for future AIs to edit. Unless you manage to keep the AI to firm module boundaries & have it replace modules wholesale it's not really equivalent to how assembly gets replaced wholesale when a compilation unit changes. Compilers aren't editing the `.o` files when you rebuild, they throw the old ones out & replace them. But when you prompt an AI it is reading & editing the source files, so excess verbosity in the source files is detrimental.

[overgard]

Well, if tokens = cost, and verbosity = more tokens, then smaller code is a financial (and human!) win. Although I'm worried vibe coders are just going to have LLMs modify minified code in caveman mode so they can have 100 agents in a swarm..

On a more serious note, I wonder if this might eventually encourage people to use languages that are a little harder to write but much more concise (functional languages for instance). When you're paying per-token enterprise bean java style verbosity totally sucks

[ponector]

But the truth is: it doesn't work correctly. I see quality of software dropped significantly.

At work we are integrating with third party platform to automate excel-powered calculations. It is awful. Rendering the table in browser takes 10s or one click on Export button will throw backend in OutOfMemory state.

[verdverm]

Ai mirrors the code around it. So if there is bad code or good abstractions, it's going to do the same. Even with good code, it will do bad things, you have to remain in the loop and catch these. It can write good code, it just needs nudging.

I don't disagree there is a lot of slop being produced right now, but I'm still optimistic in the long-run.