Data structures and algorithms go hand in hand. Like analytics and simulation. Events versus locks. Declarative versus procedural.

Stuff happens in cycles. Light casts a shadow, so there is always something else.

The basics always matter. It's communication in the end, and you have to speak the same language. Know what O(log N) means. Know when you pick a BFS vs DFS. Why do we use hash maps and why they work. Why Markov chains and state machines simplify design. How you can use Monte Carlo to make an efficient search in a game.

Many people think AI is going to be a singularity. But Amdahl's Law and Gustafson's Law suggest otherwise. You get diminishing gains with more power, and yet more power unlocks new things. Better CPUs didn't lead to instant simulations and word processing, they led to social networks and TVs that spy on you.

But you have to internalize these algorithms well enough to understand how the world works.