> I don't think the OP meant iterating on performance problems specifically, just generally iterating on code as one does when they write it. Also, every progra

> I don't think the OP meant iterating on performance problems specifically, just generally iterating on code as one does when they write it. Also, every programmer at some point iterates about performance problems, not matter their experience, or language (or implementation), or runtime that's being used. Exactly, on both accounts, thanks. It strikes me as odd that GP would describe "iterating on performance" as "underperforming", unless GP is in a very specific domain where the performance requirements are always known in advance and where they never change. Getting the last drop of performance from code is a trade-off. It impacts the readability and maintainability of code. To get the last drop, it can depend on the shape of your expected input data, and it requires looking at the produced assembly and performance profiling results to find bottlenecks and act on them. This alone implies iteration. If you're telling me that your engineers know their compiler so well that they can tell in advance what assembly code will be generated when changing seemingly unrelated parts of the code, eg they know the inlining limits of their compiler, I call BS. Iterating on performance takes time to develop and maintain, which is why it should be done just enough to meet the requirements, in particular in the hot loop and to reduce bottlenecks. If your developers are optimizing all the code they write to the ASM instruction, they are probably underperforming (unless specific domain where so little code is written or the target is so small that the benefit is worth the cost). Understanding that trade-off is part of seniority (aka juniors will often both "prematurely pessimize" by writing inefficient code without increasing maintenability or in the hot loop and "prematurely optimize" by avoiding allocation at all costs in CLI argument parsing).