1. Sufficiently obscure technical details in some field of research. There are several high-quality sources, but each of them uses its own terminology with subtly different definitions. Many immediate consequences are also left unsaid, because you can't say everything if you want to keep the paper readable. Anyone with sufficient background should see them anyway.
2. Word etymologies. There are often many competing explanations with varying degrees of plausibility and popularity, and many sources with varying degrees of credibility. The things the LLM hallucinates are often quite interesting.
3. Questions with well-defined answers that are overshadowed by something far more popular. Like, for example, what did Caesar do on the night before crossing Rubicon.
The way I experience AI is that it's like a super-powered search. It's like having an undergrad with limited knowledge read everything and come back to you with an answer.
Based on their own limited knowledge on complex topics, they're not always going to come back to you with the correct answer, but it gives you a heck of a better starting point than if you were to search for it yourself from scratch.
So what that means regarding esoteric knowledge is that the specific detail you were looking for is no longer hidden beneath 5 layers of obscura - you at least get pointed to the general area of the solution, and then maybe you have to read a paper or two to get the details you need. And instead of having to read 5 other papers to understand that one, you can ask questions and get decent answers about the terms you don't understand etc.
So imo it becomes less valuable to yourself be an encyclopedia of esoteric knowledge, since that knowledge becomes more accessible. It's like how being an expert on any road system become much less valuable with the advent of GPS.
I have to be honest I never heard of Stack Canaries before - it seems like a fairly specific term of art and I would have a hard time thinking of it as "common trivia"
In contrast, stack canaries are potentially relevant to a large number of developers. They are also accessible: many developers should be able to figure out the details on their own once they have heard of the idea.
Imo stack canaries is esoteric, at least relative to myself. On reading the first google result, I can understand the jist of the intent, but it would certainly take me time to understand the details of how it works, and to come up with an implementation. And if I didn't see it mentioned in this thread I never would have even known to search for it, and probably would have had to dig through a lot of domain knowledge to even know it's something that exists. That's the same way something can be esoteric, even if it's written about and available to everyone with access to a university library, because anyone without domain knowledge would not even know it exists or why it's relevant.
And I'm sure you can agree that if Google did not exist, probably stack canaries would be unknown and inscrutable to a vast, vast majority of developers. So if we go with your definition, the invention of Google certainly greatly reduced the amount of esoteric knowledge in existence, by making information easier to access in general. So I would argue that generative AI further reduces the scope of which information could be considered generally inaccessible,
Other topics may be difficult and advanced, but they are not esoteric, because they are more universal. You don't need a specific context to understand them, only the basic expertise.
The internet turned much esoteric knowledge into common trivia by making information more accessible. I don't think AI will have a similar effect. At least not the public models that are mostly trained using information that is already accessible. Large organizations may achieve something with internal models, but in many cases, esoteric knowledge is esoteric because it's implicit.