That's interesting.
It's controversial to say that in 2024, but not all opinions have the same value. Some are great, but some are plain dumb. The current corporate right opinion is to praise LLMs as end-all be-all. I've been asked to advise a private banking family office wanting to get into LLMs. For advising their clients' financial decisions. I politely declined. Can there be a worse use case? LLMs are parrots with the brain size of the internet. With thoughts of random origin mixed together randomly. It produces wonderful form, but abysmal analysis.
IMHO as LLMs will begin to be indistinguishable from real users (and internet dogs), there's going to be a resurging need to trace origin to a human; and maybe to also rank their opinions as well. My money is on some form of distributed social proof designating the high priests.
When we read about history of Fortran, there are several remarks on the amount of work put into place to win over those developers, as otherwise Fortran would have been yet another failed attempt.
LLMs seem to be at a similar stage, maybe their Fortran moment isn't yet here, parrots as you say, but it will come.
Android has learnt to have both, and thanks to PGO being shared across devices via Play Store, the AOT/JIT outcome reaches the ideal optimum for a specific application.
Azul and IBM have similar approaches on their JVMs with a cluster based JIT, and JIT caches as AOT alternative.
Also stuff like GPGPU is a mix of AOT and JIT, and is doing quite alright.
I am not so confident with LLMs, when they get good enough programmers will be left out of the loop, and will have to contend to similar roles as when doing no-code SaaS configs or some form of architects.
A few programmers will remain as the LLMs high priests.