This is patently false per my experience generating code with LLMs. It was not a lot; it changed one line to update a global variable to a new value per my request. It was exactly the “correct” change per the stated instructions. (Okay, not exactly because it added an extra new line that wasn’t there and which I didn’t want.)

It is certainly a fallacy to say that “no code generated by an AI is correct”. Unless you are making a point about the semantics of what is making the code “correct” (as in, is it the human reviewer or AI generator?), my point is that, in theory, the human reviews the code and submits changes for further review. The code was still generated by an AI and it can still be precisely “correct” for a given intended change.

It is understandable that you misunderstood my meaning because I was rather unclear about it (though “correct” is still the closest word I can think of to mean what I mean). However, it’s a bit wild that you say you do understand that meaning before turning around to say that it actually supports your point with a vague claim of a “variety of factors”. I actually get the feeling, based on this response, that your argument is effectively refuted by the point I raised. I’m willing to keep an open mind if you’d like to show me that I’m wrong; maybe I’m just missing something.