A developer explores whether AI agents can write significantly faster Rust code through iterative optimization prompts. Testing with Claude Opus 4.5 on algorithms like UMAP, they achieved 2x-20x speedups by having the agent repeatedly optimize Rust implementations, which can be exposed to Python via PyO3 for both speed and usability.
A software engineer demonstrates that Claude Opus 4.5 and newer agentic LLMs can write Rust code significantly faster than state-of-the-art libraries through iterative optimization, achieving 2x-20x speedups. The approach involves asking agents to iteratively improve code with appropriate constraints, exemplified through reimplementing machine learning algorithms like UMAP in Rust with PyO3 Python bindings and criterion benchmarking.