Performance topic is very trendy right now. Chance is you already heard it - use lazy loading, prefetch everything with partially hydrated server-side rendered static islands. Ship zero bytes of JavaScript! But what if your code is not running in the browser or your performance is bad at runtime?

This talk will share several (un)conventional tricks you can apply to speed up the application when the size of your data grows. I will show you how to measure performance and squeeze out those last excessive milliseconds.

Learn how usual "bad practices" can become your ally when battling performance.

This talk shows a contrast to typical time-to-interactive performance talks. It focuses on the performance of the code rather than ways of shipping fewer bytes over HTTP and making the application faster to interact. In the intro, I explain what the talk is not about by listing all the techniques commonly used.

The talk focuses on the following flow:
- What is big O, and how to count the number of loops
- How mutating is faster than using immutable code, and when to use it
- Why is implicit code faster than explicit, and when can we omit it
- Performance comparison between arrays and objects, and where each excels
- Maps vs. Objects (hashmaps) performance
- Why higher-order functions are usually too slow
- Finally, how to benchmark and performance time our code

Each of the topics is explained with a small code snippet that links to benchmarking results, followed by real-life situations where this was applied.