I think that PID hits a certain sweet spot between cleverness, ease of implementation and practical utility that makes it catnip for the typical programmer's mind.
I liked it so much that when we had to implement it, I downloaded an open source driving simulator to see it work there instead of the simpler python environment we were using.
Sounds like he made a bag with the first AI craze and retired.
It's easy to implement, but hard to tune.
PID controllers can be built from analog pneumatic components, and often are.[1] This predates computer control. The I term is called "Reset" and the D term is called "Rate" in classical control.
[1] https://control.com/textbook/closed-loop-control/pneumatic-p...
It's sold as something completely different though that will revolutionize autonomous decision-making which it clearly isn't, it's just trying to re-invent the wheel but with neural nets this time around.
I'll confess I didn't understand what you meant with the part of your comment after the semi-colon.
https://mitp-content-server.mit.edu/books/content/sectbyfn/b...
A common hiring anecdote we share with people outside tech is literally: “A CS degree doesn’t teach you how to code.”
For me, ~25 years ago in the UC system, it was all math/science/theory-oriented. Some C++/Java that was introduced to get you through all that theory. Learning how to code/actual software engineering comes with practical experience.
(I am quite happy to have gotten the software engineering education.)
Keep in mind that plenty of people on HN and in the industry did not take CS degrees in college. We did learn about PIDs, if briefly.