[simple-thoughts]

For code I’ve found LLM mostly useless, since if I don’t understand something I need to read the docs anyway, and the generated code tends to be buggy even in react.

Where I have found LLM useful is in generating text. Where I used to use a thesaurus I now use LLM to find words to name things in themed UX. But it’s not great at function or variable names, it tends to pick names that look good but don’t precisely describe what something is. LLM is also great at generating text for role play.

[GuB-42]

I had a lot more success writing some code and have ChatGPT document it than doing the opposite. The documentation tends to be much better written than what I would have done by myself.

Indeed because ChatGPT is excellent at writing text. And because I know exactly what I want to see even if I have a hard time putting it into words myself, I can easily catch the mistakes and hallucinations.

I don't get why there is so much focus on code generating AIs and so little on code analysis. Have AIs do code reviews, write tests and analyze the results, etc... LLMs are awesome at reviewing code, they are able to tell you what's unexpected. And what is unexpected has a good chance of either being a bug or some key element of the code that needs attention. I think I have seen a single article about that, out of hundreds that are about code generation.