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Comment by softwaredoug | Hacker News Reader

IMO slop usually comes from overly defensive programming from LLMs. They’re loath to remove code and simplify, because unless we humans tell them some code / use case is unimportant, they have no reason to not care about it.

So agents can make these overly complex solutions trying to make bulletproof implementations and prevent regressions.

It requires a human to look at code, ask about complexity, and guide simplification by subtracting requirements implicit in the code.

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They also seem to really bias towards tacking on new code to "work around" what's there, rather than breaking down what's there into smaller more composable bits that can serve the pre-existing use case and the new requirement elegantly.

LLMs write. It sounds glib but it's what they do, and so every problem they encounter they will try to write their way out of it without lots of hand holding.

they yearn to create content, generate more tokens, etc etc - agree

Yea I say something similar. LLMs have a tendency to add, because there are many more tokens than a stop token. They can remove, they can edit, but their bias is to add. My suspicion is that training them when to stop when it is best to stop is harder than training them to make a plausible sounding story.

It's like we took the worst behavior of our colleagues, and went and said "yes, let's automate _that_ part" and patted ourselves on the back.

It’s more likely emergent behavior.

Yes exactly. And I’m not sure we want agents with that level of autonomy to decide what functionality is important and what to leave in place.

No, but it would sometimes be nice if they sometimes raised questions about what is important and what isn't

Agree, and I am worried about what happens when that old code is written by LLMs, approved by a human who pretended to have read it, and now needs to be touched by another human who is completely reliant on LLMs to understand existing code.

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