It depends on your use case, as always. Correctness is not always black and white (hence my favourite compilation flag, -funsafe-math-optimizations) and time complexity can be misleading (O(log N) with a large base is O(1) in practice), but a correct, theoretically optimal algorithm might still be leaving a lot of performance on the table. If you're a hyperscaler, a high-frequency trader, or perhaps a game programmer pushing the limits of the platform, small gains can accumulate meaningfully, as can the thousand cuts caused by small inefficiencies spread out over the codebase.