generally i think advice that will always be applicable:

- learn and use a profiler before there are performance issues, not after (dont treat performance as an afterthought).

- internalize which patterns are faster and which are slower, and when it matters.

- for any runtime with a GC, reduce repetitive memory allocation and GC pressure. prefer shallow structures. mutation instead of immutability (thus, mem allocation).

- cache/memoize whenever possible.

- don't use algorithms that scale poorly with data size.

finally, beware of following any performance advice older than 6 months; JITs advance constantly, so make sure to re-bench/measure continuously to avoid doing unnecessary refactors, and test with real code; there are lies, damned lies, and micro-benchmarks.