The very first thing I did was create a AGENTS.md for Rust by telling Opus 4.5 to port over the Python rules to Rust semantic equivalents. This worked well enough and had the standard Rust idioms: no .clone() to handle lifetimes poorly, no unnecessary .unwrap(), no unsafe code, etc. Although I am not a Rust expert and cannot speak that the agent-generated code is idiomatic Rust, none of the Rust code demoed in this blog post has traces of bad Rust code smell. Most importantly, the agent is instructed to call clippy after each major change, which is Rust’s famous linter that helps keep the code clean, and Opus is good about implementing suggestions from its warnings. My up-to-date Rust AGENTS.md is available here.
我们要把以前 30 万、40 万级别才有的配置和体验，带给更广泛的消费者，打破虚高的品牌溢价，真正实现科技平权、豪华平权。
。WPS官方版本下载对此有专业解读
Rhys urged Americans to mark St David's Day by following the patron saint's motto, "gwnewch y pethau bychain" or "do the little things", on 1 March.
Раскрыты подробности похищения ребенка в Смоленске09:27，这一点在搜狗输入法下载中也有详细论述
instead of the heap. Stack allocations are considerably cheaper to
Many people reading this will call bullshit on the performance improvement metrics, and honestly, fair. I too thought the agents would stumble in hilarious ways trying, but they did not. To demonstrate that I am not bullshitting, I also decided to release a more simple Rust-with-Python-bindings project today: nndex, an in-memory vector “store” that is designed to retrieve the exact nearest neighbors as fast as possible (and has fast approximate NN too), and is now available open-sourced on GitHub. This leverages the dot product which is one of the simplest matrix ops and is therefore heavily optimized by existing libraries such as Python’s numpy…and yet after a few optimization passes, it tied numpy even though numpy leverages BLAS libraries for maximum mathematical performance. Naturally, I instructed Opus to also add support for BLAS with more optimization passes and it now is 1-5x numpy’s speed in the single-query case and much faster with batch prediction. 3 It’s so fast that even though I also added GPU support for testing, it’s mostly ineffective below 100k rows due to the GPU dispatch overhead being greater than the actual retrieval speed.，推荐阅读同城约会获取更多信息