Only then should teams optimize, and only with measurements. Profilers, tracing, and realistic benchmarks reveal hot paths; Amdahl’s Law (1967) warns that speeding a small fraction yields limited gains. Donald Knuth’s caution about premature optimization (1974) underscores why evidence matters. Often, algorithmic choices, better data access patterns, or judicious caching provide outsized wins, while micro-optimizations merely add complexity. Because correctness and design are already solid, performance tweaks remain localized and safer to revert. Moreover, the test suite built earlier quickly catches regressions introduced by optimization. [...]
