Learning computer science theory is probably going to be more important for the future than writing code yourself, because LLM coding is here to stay, and the human's job is going to be guiding the LLMs effectively: the AIs are writing code that pass tests, but how would you know that you are having the LLMs coding the right things?

Personally, I think learning specific implementation of algorithms probably should take less of a priority compared to fundamental architectural understanding why these things are done in the first place: data structure, automata theory, interpreter/compiler methodologies, etc. You still have to learn how to code, even if you won't be doing a lot of coding directly yourself, because the fastest way to learn how to evaluate code is by writing code yourself.