Unless your job is cutting-edge research where you are truly making new scientific discoveries and methods, you're just combining other peoples' ideas into a new unique package and selling it.
The truly valuable work is to notice that there is an underserved market and figure out how to meet their needs.
I write a bunch of widgets for my website. They're little calculators that use common components and apply simple logic. Think unit conversion or date arithmetic.
These currently take a few hours to write, and most of the work is just wiring things together in a predictable way: template, tests, common form controls.
I think that this would be a very good case for AI.
I’m not a programmer but that’s what I’ve done. In the past I would’ve needed either to learn how to code or hire someone.
I suppose that generative AI was seen as such a boon to writing boilerplate because it could do so without you having to specifically program anything; it was trained on enough sufficiently-close examples that it could pull it off without a thorough description.