this post was submitted on 16 Oct 2026
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[–] aanes_appreciator@hexbear.net 5 points 1 week ago

If the code is good enough you wouldn't know, but then it's likely the LLM code was audited and fixed by a skilled human so 🤷‍♂️.

In my experience there are smells:

  • Comments are oddly explanatory of basic concepts.
  • Making an unusually large number of changes in a single commit (specifically, changes that arent related to the goal of the commit)
  • Writing new infrastructure code that duplicates the work of old code for no reason.
  • Using old library or language conventions unexpectedly.

Most importantly:

  • A contributor who has no idea what their code does.

A lot of it you learn from using AI yourself. I use it for inline hints, and i see what goes wrong in that and from testing agentic crap - the stuff that stinks of bad AI use that you can then see in the work of colleagues.