Ok, given your university background in CS, it sounds like you have a good base of understanding. I think there are many narrow verticals, but I think you're th

Ok, given your university background in CS, it sounds like you have a good base of understanding. I think there are many narrow verticals, but I think you're through the base of understanding. I think people can answer specific questions, but not more general ones. Traditionally, try response would be: have you taken databases, compilers, operating systems, or more extensive computational complexity theory. Honestly, the complexity theory enables napkin math for quick mental, or mid-discussion, feasibility arguments. I would recommend AI and ML familiarity, including transformers, which I view at first glance as an interesting amalgamation of applied statistics and computational complexity. Numerical stability was (and is) a hard problem about practices needed to get consistent and useful results from numerical algorithms. I think your bases are covered. It sounds like you know what you don't know. I might recommend collecting interesting problems, and learning how knowledge from each of those fields contributes to solving a class of problems, quickly, easily, simply, or efficiently. What do you hope to do, to direct your mental energies toward?