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Rust is a bad language to fake your way through with an LLM. Python forgives a wrong guess — code "looks right," runs, and you fix the type error later. Rust doesn't negotiate: it's correct or it's a compile error, and the gap between "almost right" and "right" is frequently a single & , mut , or lifetime annotation.

So instead of asking which AI coding tool "feels" best for Rust, we measured something falsifiable: how often does each tool's suggestion actually compile on the first try.

What we ran

Five tools — Cursor , GitHub Copilot , Windsurf , Tabnine , and Claude Code — against four real project types: a clap -based CLI, an axum async web server with database pooling and JWT auth, a systems library with unsafe blocks and FFI via bindgen , and a wasm-bindgen WebAssembly module.…