It seems that machines are much faster at learning how to do low level stuff(compilers, generic problem solvers, etc) - than they are at doing the high level stuff - understanding the problem and build a high level spec/system for the solution.
And of course we're becoming more capable of letting the domain users enter more and more details of the system themselves, either by visual programming, scripting or giving data to machine learning systems, etc.
So if those trends are to continue , professional programmers will specialize in creating more and more , highly abstract generic solutions.
It's not like the machines are just /learning/ how to do low level stuff. People are doing deliberate research, modifying them, and testing them to make that happen.
Low-level optimizations are the least automated process I can think of.
I'm talking about trends , not absolutes(not a sith).
The share of programmers who are doing high level stuff(understanding users and encoding that ) versus those who optimize the low-level is always growing.
Maybe it's ~90% today , vs less than 10% in the early years of computing when every byte counted and systems were less complex.
> Low-level optimizations are the least automated process I can think of.
And compilers automate low-level optimizations every day.
It seems that machines are much faster at learning how to do low level stuff(compilers, generic problem solvers, etc) - than they are at doing the high level stuff - understanding the problem and build a high level spec/system for the solution.
And of course we're becoming more capable of letting the domain users enter more and more details of the system themselves, either by visual programming, scripting or giving data to machine learning systems, etc.
So if those trends are to continue , professional programmers will specialize in creating more and more , highly abstract generic solutions.