[leoedin]

This matches my experience too. The models write code that would never pass a review normally. Mega functions, "copy and pasted" code with small changes, deep nested conditionals and loops. All the stuff we've spent a lot of time trying to minimise!

You could argue it's OK because a model can always fix it later. But the problem comes when there's subtle logic bugs and its basically impossible to understand. Or fixing the bug in one place doesn't fix it in the 10 other places almost the same code exists.

I strongly suspect that LLMs, like all technologies, are going to follow an S curve of capability. The question is where in that S curve we are right now.