This is no different then carpentry. Yes, all furniture can now be built by machines. Some people still choose to build it by hand. Does that make them less productive? Yes. Will they ever carve furniture by hand for a business? Probably not. Can they still enjoy the act of working with the wood? Yes. If you want to code by hand, then do it! No one's stopping you. But we shouldn't pretend that you will be able to do…
There's going to be minimal "junior" jobs where you're mostly implementing - I guess roughly equivalent to working wood by hand - but there's still going to be jobs resembling senior level FAANG jobs for the foreseeable future.
Someone's going to have to do the work, babysit the algorithm, know how to verify that it actually works, know how to know that it actually does what it's supposed to do, know how to know if the people who asked for it actually knew what they were asking for, etc.
Will pay go down? Who knows. It's easy to imagine a world in which this creates MORE demand for seniors, even if there's less demand for "all SWEs" because there's almost zero demand for new juniors.
And at least for some time, you're going to need non-trivial babysitting to get anything non-trivial to "just work".
At the scale of a FAANG codebase, AI is currently not that helpful.
Sure, Gemini might have a million token context, but the larger the context th worse the performance.
This is a hard problem to solve, that has had minimal progress in what - 3 years?
If there's a MAJOR breakthrough on output performance wrt context size - then things could change quickly.
The LLMs are currently insanely good at implementing non-novel things in small context windows - mainly because their training sets are big enough that it's essentially a search problem.
But there's a lot more engineering jobs than people think that AREN'T primarily doing this.