Writing Rust code that's faster than state-of-the-art libraries by asking agents to make the code faster
Summary
The article explains how agentic prompting and constraint-based techniques can push LLMs to generate faster Rust code, backed by benchmarking and explanations of guardrails. It covers iterative speedups across domains, benchmarking integrity, subagents, and prompts that drive deep optimization, with multiple real-world example domains and a plan for open-sourcing the work.