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.
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Integration between different search modalities is accelerating. Google is bringing AI answers into traditional search results. Bing is integrating ChatGPT-powered features. New platforms are emerging that combine search, AI chat, and traditional browsing in unified experiences. This convergence means optimization strategies must account for hybrid discovery experiences where users might see both traditional results and AI-generated answers, potentially in the same interface.
Zoe Langley-Wathen
而 Qwen3.5-122B-A10B 与 27B 版本进一步缩小了中等规模模型与前沿模型的差距，尤其在复杂代理场景中表现优异。