In this Nim tutorial (Part 56), I walk you through what “threads” actually mean in practice, and I spend a bit of time up front making sure we’re not mixing up concurrency and parallelism. If you’ve ever heard people use those words interchangeably and felt like something was off—yeah, same. I break down the mental model I use when I’m deciding whether I need threads at all, and what kind of speed-up I can realistically expect. After that, we get into actual thread programming in Nim: creating a basic thread, passing work to it, and then scaling the idea up to multiple threads. I also talk about the garbage collector, because if you ignore memory + GC behavior while doing threaded code, you’re going to have a bad time. The takeaway is simple: threads are powerful, but you need to be intentional about what data is shared, what’s copied, and how you structure your program so it stays predictable. I also point you to solid references and a couple of threadpool alternatives if you want higher-level tooling.