It doesn’t matter whether that specific use case is fruitful or not. I wasn’t making a case for it.

And yet, I've gotten help from LLMs with code in two different ways: 1) Where I check everything at the door and manually write out or rewrite in my own words, only using the AI as an assistant for the method at most. 2) Where I don't know enough in the language, so I go back and forth, trying a solution it gives me and then going back to it when corrections are needed.

2 is definitely more painful and I would probably be extra wary of using it in production business code and insist on review from someone who is literate in the language. BUT, there have been occasions where if I didn't have 2 as an option, I may have never written the solution at all, or it would have taken me weeks or months of learning to get there. If I could be assured the "personal learning then completion" path would happen, that would lessen the value of 2, but being real, I cannot remotely guarantee it. Whether it's a matter of time, motivation, etc., even someone who is already literate in some programming like myself, will not necessarily find it easy to learn every new language, library, etc., or always find it to be a motivating pursuit worth doing.

In other words, sometimes we are not talking about space-faring code and we're talking about whether something with largely trivial consequences for mistakes, and a low friction path to fixing them, will ever get made at all. This is the kind of area where LLMs shine, since they don't need to be without error, they just need to be "good enough" that it empowered somebody to make something that wouldn't otherwise have gotten made.