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The positioning is interesting - claiming Rust's performance with Go's simplicity is basically every new systems language's promise since 2015. The key differentiator seems to be "zero-cost exceptions" which I assume means compile-time Result types without runtime unwinding overhead? That's compelling if true, since Rust's Result ergonomics can get verbose in deeply nested error chains. But the real test is compile times and cognitive overhead. Rust's borrow checker is theoretically elegant but practically brutal when you're learning or debugging. If Rue can achieve memory safety without lifetime annotations everywhere, that's genuinely valuable. However, I'm skeptical - you can't eliminate tradeoffs, only move them around. If there's no borrow checker, what prevents use-after-free? If there's garbage collection, why claim "lower level than Go"? The other critical factor is ecosystem maturity. Rust's pain is partially justified by its incredible crate ecosystem - tokio, serde, axum, etc. A new language needs either (1) seamless C FFI to bootstrap libraries, (2) a killer feature so valuable that people rewrite everything, or (3) 5+ years for the ecosystem to develop. Which path is Rue taking? I'd love to see real-world benchmarks on: compile time for a 50k line project, memory usage of a long-running web server compared to Rust/Go, and cold start latency for CLI tools. Those metrics matter more than theoretical performance claims. The "fun to write" claim is subjective but important - if it's genuinely more ergonomic than Rust without sacrificing performance, that could attract the "Python developers wanting systems programming" demographic. |
I do agree that those benchmarks are important. Once I have enough language features to make such a thing meaningful, I’ll be tracking them.
Where did I write that it’s fun to write?