There is a misunderstanding going here. A linked list is a pure form of knowledge. What we see today is an explosion of arbitrary complexity that is the fruit, mostly, of bad design. If I learn the internals of React, I'm not really understanding anything fundamental. If I get to know the subtleness of Rust semantics and then Rust goes away, I'm left with nothing: it's not like learning Lisp. Think to all the folks that used to master M4 macros in the Sendmail, 30 years ago. I was saying the same, back then: this is garbage knowledge.
Today we have a great example in Kubernetes, and all the other synthetic complexity out there. I'm in, instead, to learn important ML concepts, new data structures, new abstractions. Not the result of some poor design activity. LLMs allow you to offload this memorization out of your mind, to make space for distilled ideas.
Spot on - it is one of the main reasons I haven't enjoyed programming in recent years, so much of it is learning what you call "garbage knowledge". Yet another API, yet another DSL, yet another standard library. Endless reading of internal wiki pages to learn the byzantine deployment system of my current company. Even worse, when I know exactly what I want, but some little dependency or piece of tooling is bad and I spend hours, or days, trying to debug it.
I, too, find LLMs a balm for this pain. They have kind-of-basic level of knowledge, but about everything.
In short, it allows for a more efficient expenditure of mental and emotional energy!
Much of programming, coding and developing is done by a person who is a knowledge worker and writes code. A good proportion of code to be written, will be written just once and never again. The one-off code snippet will stay in a file collecting dust forever. There is no point in trying to remember it in the first place, because without constant repetition of using it, it will be forgotten.
LLMs can help us focus our knowledge where it really matters, and discard a lot of the ephemeral stuff. That means that we can be more of knowledge workers and less of coders. I will push it even further and state that we will become more of knowledge workers and less of coders until we will be, eventually and gradually, just knowledge workers. We will need to know about algorithms, algorithmic complexity, abstractions and stuff like that.
We will need to know subjects like that Rust book [1] writes about.
Today we have a great example in Kubernetes, and all the other synthetic complexity out there. I'm in, instead, to learn important ML concepts, new data structures, new abstractions. Not the result of some poor design activity. LLMs allow you to offload this memorization out of your mind, to make space for distilled ideas.