I wrote a fairly detailed spec for some software and told it what dependencies to use, what it should do, and what command-line options it should use. The base was a decent starting point, but after several hours of back-and-forth, after actually reading the code, I realized it had completely misinterpreted my spec somehow and implemented a similar feature in a completely broken way, as well as making a few mistakes/redundancies elsewhere. I tried to coach it to fix these issues, but it just couldn't cope.

I spent about 3 hours getting this base code generated, and about 5 hours re-writing it and implementing the features properly. The reason I turned to ChatGPT is because I needed this software written by the end of the day, and I didn't have time to read all the different docs for the dependencies I needed to use to write it. It likely would have taken me at least 2 days to write this program myself. It was an interesting learning experience, but my only ChatGPT usage in the future is likely to be with individual code blocks.

You really need to pay attention if you're using LLMs to generate code. I've found it usually gets at least one thing wrong, and sometimes multiple things horribly wrong. Don't rely on it; look for other sources to corroborate all of its explanations. Additionally, please do not feed proprietary, copyrighted code into ChatGPT. The software I was writing was released under a free license. OpenAI will use it as training data unless you use their API and opt out of it. ChatGPT isn't really a tool; it's a service which is using you as much as you're using it.