I've found ChatGPT useful – I want to write some code to do X, and I often find it is a less mentally taxing to write an English prompt and let ChatGPT do the rest than to write the code myself. But I don't just trust ChatGPT's code – I always modify it, refactor it a bit. ChatGPT is rather human in that sometimes it makes the kind of dumb mistakes that humans do–like inverting a test. I know how to catch those mistakes when I make them myself, so I know how to catch them when ChatGPT does them too.

I think that's where LLM is most useful – a tool to save time and mental effort for developers who understand the code it generates and can tell when it is wrong or needs improvement. I don't think it is going to work well in the hands of non-developers, because sometimes the code it generates doesn't even compile, or just crashes–and how is a non-developer going to fix that? Even worse, sometimes it can be subtly wrong–the code runs but it produces incorrect data–and the risk is a non-developer might not even notice.