Thinking Mode：选中 Ring 模型后，你会发现它多了一个“深度思考”的 toggle。这背后是基于 RLVR（Reinforcement Learning with Verifiable Rewards）训练的 Dense Reward 机制，能让模型在输出结果前，进行多步推理和自我反思。
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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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