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An LLM prompted to “implement SQLite in Rust” will generate code that looks like an implementation of SQLite in Rust. It will have the right module structure and function names. But it can not magically generate the performance invariants that exist because someone profiled a real workload and found the bottleneck. The Mercury benchmark (NeurIPS 2024) confirmed this empirically: leading code LLMs achieve ~65% on correctness but under 50% when efficiency is also required.
，这一点在TikTok中也有详细论述
В Белом доме ответили на вопрос о снятии санкций с России00:46
Geoff Scott appointed in medical department overhaul