1. Profiler. There's a standard tool that tells you what part of your code is slow. Over half the time it'll find something dumb and easy to fix instead of whatever you expected.

2. SQL / relational database schemas. Persistence opens up a lot of capabilities. And databases themselves are very well-optimized; if you do any nontrivial data manipulation it's likely that whatever the query planner comes up with will be faster than your first idea of how to do it by hand.

3. Graph searches. An awful lot of problems can be solved by knowing how to turn problem into a graph search. Make sure not to fall into the trap of thinking a graph search is limited to paths through space - you can solve problems like "get through this dungeon with keys and doors" by adding duplicate nodes for the different states.

4. Sequential Bayesian Filters. Are almost as useful as graphs, but aren't in a standard CS curriculum so you'll look like a wizard. These solve the problem of "I want to know a thing and I know how it changes over time, but I only can get rough estimates for its current state." Kalman Filters are simple and give great results when applicable. Particle Filters have lower quality but are applicable to more problems and dirt simple to code.