It's funny because of the irony of "prompt engineering" being as close to cargo culting as things get. No one knows what the model is or how it's structured in a higher level (non implementation) sense, people just try different things until something works, and try what they've seen other people do.
This article is at least interesting in that it takes a stab at explaining prompt efficacy with some sort of concrete basis, even if it lacks rigor.
It's actually a really important question about LLMs: how are they to be used to get the best results? All the work seems to be on the back end, but the front end is exceedingly important. Right now it's some version of Deep Thought spitting out the answer '42'.
> 1. the branch of science and technology concerned with the design, building, and use of engines, machines, and structures.
2. the action of working artfully to bring something about.
So you're trying to learn what / how to prompt, in order to "bring something about" (the results you're after).
-A Prompt Architect