What makes you think it will work for you?
Unless you review that code carefully, and then we're back to the point about it not saving you any cognitive overhead.
That link I posted upthread, the "developer" did not read the docs "because the LLM wrote the code" and hence did not realise that the token they had was a full access token, not a limited access token.
You're now boasting that you also don't have to read the docs because the LLM wrote the code?
I mean, it's literally the cause of their irreversible production deletion, in a link that you replied to, and you state you do the same?
The “with extra steps” is doing a lot of work in that sentence.
That "almost" is doing a lot of heavy lifting here. This is just "make no mistakes" "you're holding it wrong" magical thinking.
In every project, there is always a gap between what you think you want and what you actually need. Part of the build process is working that out. You can't write better specs to solve this, because you don't know what it is yet.
On top of that, you introduce a _second_ gap of pulling a lever and seeing if you get a sip of juice or an electric shock lol. You can't really spec your way out of that one, either, because you're using a non-deterministic process.
So right now, humans are for sure more reliable. But it is changing. There are things I already trust a LLM more than a random or certain known humans.
But it seems we are heading there. For simple stuff, if I made a very clear spec - I can be almost sure, that every time I give that prompt to a AI, it will work without error, using the same algorithms. So quality of prompt is more valuable, than the generated code
So either way, this is what I focus my thinking on right now, something that always was important and now with AI even more so - crystal clear language describing what the program should do and how.
That requires enough thinking effort.