Yours is pretty much the best-case scenario for AI:

• Super small project, maybe a few dozen lines at most
• Greenfield: no dependencies, no old code, nothing to consider apart from the problem at hand
• Disposable: once the job is done you discard it and won’t need to maintain it
• Someone most likely already did the same thing or did something very similar and the LLM can draw on that, modify it slightly and serve it as innovation
• It’s a subject where you are good enough that you can verify what the LLM spits out, but where you’d have to spend hours and hours to read into how to do it

For that kind of stuff it’s totally OK to use an LLM. It’s like googleing, finding a ready-made solution on Stackexchange, running that once and discarding it, just in a more modern wrapping. I’ve done something similar too.

But for real work on real projects, LLM is more often than not a time waster and not a productivity gain.