Academic papers are frustrating to me in that they seem to use esoteric language in order to create a veneer of importance, sometimes above trivial real content.
This stands against that trend and harkens back to papers of old.
It's kind of true, but also I think the real answer is that you're not the target audience.
A lot of time you use esoteric language because part of the problem being solved for in these conversations are:
1. what are useful and meaningful abstractions?
2. which abstractions are seeing uptake?
3. Who gets credit for the abstraction?
This mean papers are very often introducing new terminology as part of an exploratory conversation. Communication is optimized for the people engaging in that process.
As time passes most of these terms fall into disuse and the field circles around a few winners which then pass into the wider world. This stage is much more approachable and this content is what most of us are used to consuming.
Nobody complaints when you invent words or phrases to add clarity, but most academic papers are NOT doing this. It's an academic circle-j** where all the authors play the same game to try to fit in with each other.
And in this respect, you're 100% right. Professionals who make a living doing work, even the ones who know more about the topic than the researchers, are not the target audience. The target audience is the others participating in the circle-j** who determine if the paper should be published.
And no, I'm not saying that researchers are worthless and don't know anything. Merely that they have different purposes and standards for their work. And it has always been this way, in every field.
You know what's the shittiest spot to be in? A PhD student that's also one of those working class professionals. Can you imagine working on something you know represents a significant technical challenge in industry and then writing a paper on it and then it get rejected because it's "just engineering".
My personal favorite (ie in my area) is the original pytorch paper isn't publishable for this reason (but simultaneously is the highest cited - through it's arxiv orcid - ML compiler paper of all time).
Brian Greene is probably considered a pariah around here but I really enjoyed reading his book The Elegant Universe.
All of this stuff needs to be extremely clear, precise, and readable by professionals. That's not the same as being "fun to read", and certainly not by laypeople. You can't really know whether an academic paper is clear, precise, and readable unless you're a professional in the sub-discipline the paper was written for.