alt Hacker NewsI am spending about 10h per day solving chemical engineering problems (dynamic simulation, model predictive control, etc.). The programming is hard on top of hard science. Even after 25 years of experience, it is still hard to find the right abstraction to implement everything.
Still, one thing I really like with LLM/AI, is that now, I can allow myself to test different abstractions a bit faster. I can allow myself to "try" more complex refactoring on a feature branch, because if I describe correctly the abstraction I want, the LLM/AI tool will be normally good at producing it. But to describe my abstraction, I need to pull all my programming and engineering years of experience.
But at the end of the day, I always tell my wife, that with these new tools, which I could not imagine so powerful 3 years ago, I live in the future :-)
I suppose the complexity of the domain is the main driver of the difficulty level. Perhaps that's the intuition that I'm trying to pin down: programming itself, the typing of words for the compiler, the act of converting pure thought into code, seems mechanical at best. But if you include the act of abstraction itself, then I concede it changes the equation. I don't find it to be all that clear what is and isn't programming to be honest.
Especially once you get to describe your abstractions in plain (or slightly technical) English instead of code I find it hard to say "programming" is being performed, but in many ways the case could be made that it remained the same and only the shape of the artifacts is different now.