[toogan]

I mean ... most code out there is pretty bad, so LLM assistants contributing pretty bad code just keeps the mean where it is. And obviously it has to be, how can anybody expect an LLM to produce output with quality that's higher than its training input? Expecting that is appealing to magic or some consciousness that doesn't actually exist or just plain anthropomorphising.

If you are working at a place where that quality level is standard -- and let's face it, a large number of companies produce average or below-average quality code (by definition) -- then using an LLM assistant isn't that bad. At least if such an assistant doesn't have some extra flaws beyond producing the best summary of its training data, which is exactly what an LLM does. It actually justifiably replaces developers in such an average-or-below place. But if you are aiming for the top end of the quality scale then there is no way this can be achieved by LLM output. Purely on principle.

This shouldn't even be a controversial opinion. I'm quite surprised every time this is questioned or even just debated.

[nextts]

"Bad" is doing s lot of work in your sentence. Do you mean slow? Or buggy? Or unmaintainable? Or unextendable? Uses patterns the tech lead hates? Hard to read? High cyclomatic complexity? Doesn't meet requirements? Security issues? Uses out of date libraries? Too much reliance on 3rd party code? Too much NIH? ...

I think "one shot ready for production code" is what AI cannot do yet. Which is why I am not worried for another 12 months at least :)

[toogan]

Any badness metric you like. LLMs average over that since their training input does.