No doubt the earliest pioneers of computer science, emerging from the (relatively) primitive cave of electrical engineering, stridently believed that all future computer scientists would need to command a deep understanding of semiconductors, binary arithmetic, and microprocessor design to understand software.

This is disappointing, although not unexpected. Computer scientists, in general, are tragically bad at the history of their own field, although all of science is like that and it is not specific to computer science. Compare Alan Turing, who wrote in 1945, before there was any actual computer to program:

This process of constructing instruction tables should be very fascinating. There need be no real danger of it ever becoming a drudge, for any processes that are quite mechanical may be turned over to the machine itself.

That is, the earliest pioneers of computer science thought about automating programming tasks, before any of actual programming. As far as I know zero actual pioneers of computer science believed programmers would need to understand hardware design to understand software. It would be especially unlike for Alan Turing, since the big deal about Turing machine was that universal Turing machine can be built such that underlying computing substrate can be ignored. Misconceptions like this seem specific to people like Matt Welsh who came after the field was born and didn't bother to study the history of how the field was born.

A lot of things humans do are AGI-complete, they won't be automated in a business-as-usual world, before everything else changes too, around the same time. There is no timeline where some of them happen 4 years from now, while others 7 years after that. Possibly even good self-driving cars are AGI-complete, but certainly programming.

Thus there is no straightforward fire alarm: anything that actually happens before AGI is not AGI-complete, and so doesn't directly demonstrate the possibility of an AGI; and anything that is AGI-complete won't work before AGI.

Programming has already been automated several times. First off, as indicated above, it was automated by moving from actual electronics into machine code. And then machine code was automated by compilers, and then most of the manual busywork of compiled languages was automated by the higher-level languages with GC, OO, and various other acronyms.

In other words, I fully expect that LLM-driven tools for code generation will become a standard and necessary part of the software developers toolkit. But I highly doubt that software development itself will be obsoleted; rather, it will move up to the next level of abstraction and continue from there.

Well, I very much doubt that the entire programming world will get access to a four-quintillion-parameter code-generating model within five years. However, I do foresee the descendants of OpenAI Codex getting much more powerful and much more used within that timeframe. After all, Transformers just came out only five years ago, and they've definitely come a long way since.

Human culture changes more slowly than AI technology, though, so I expect businesses to begin adopting such models only with great trepidation at first. Programmers will almost certainly need to stick around for verification and validation of generated code for quite some time. More output will be expected out of programmers, for sure, as the technology is adopted, but that probably won't lead to the elimination of jobs themselves, just as the cotton gin didn't lead to the end of slavery and the rise of automation didn't lead to the rise of leisure time.

Eventually though, yes, code generation will be almost universally automated, at least once everyone is comfortable with automated code verification and validation. However, I wouldn't expect that cultural shift to be complete until at least the early 2030's. That's not to say we aren't in fact running out of time, of course.

Still at least good recreation.