To be honest you don't need to know the lower level things. It's just removing the need to remember the occasional boilerplate. If I need to parse a file I can

To be honest you don't need to know the lower level things. It's just removing the need to remember the occasional boilerplate. If I need to parse a file I can just chuck it a couple lines, ask it to do it with a recommended library and get the output in 15 minutes total assuming I don't have a library in mind and have to find one I like. Of course verification is still needed but I'd need to verify it even if I wrote it myself anyway, same for optimization. I'd even argue it's better since it's someone else's code so I'm more judgemental. The issue comes when you start trying to do complex stuff with LLMs since you then tend to halfass the analysis part and get led down the development path the LLM chose, get a mish mash of the AIs codestyle and yours from the constant fixes and it becomes a mess. You can get things implemented quickly like that, which is cool, but it feels like it inevitably becomes spaghetti code and sometimes you can't even rewrite it easily since it used something that works but you don't entirely understand.