My small-program success story with genAI coding is pretty much the opposite of your claim. I used to use a bash script with a few sox instances piped into each other to beat-match and mix a few tracks. Couldn't use a GUI... Then came gpt-5, and I wanted to test it anyway. So I had it write a single-file C++ program that does the track database, offline mixing, limiter and a small REPL-based "UI" to control the thing. I basically had results before my partner was finished preparing breakfast. Then I had a lot of fun bikeshedding the resulting code until it felt like something I'd like to read. Some back and forth, pretending to have an intern and just reviewing/fixing their code. During the whole experience, it basically never generated code which wouldn't compile. Had a single segfault which was due to unclear interface to a C library. Got that fixed quickly.

And now, I have a tool to do a (shuffled if I want) beat-matched mix of all the tracks in my db which match a certain tag expression. "(dnb | jungle) & vocals", wait a few minutes, and play a 2 hour beat-matched mix, finally replacing mpd's "crossfade" feature. I have a lot of joy using that tool, and it was definitely fun having it made. clmix[1] is now something I almost use daily to generate club-style mixes to listen to at home.

[1] https://github.com/mlang/clmix