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.
Automated systems are causing real harm. “Request review” processes shouldn’t require detective work to find contact forms, forum registrations, and email addresses. A 15-day resolution time for a false positive is unacceptable for businesses that depend on web traffic.
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Anthropic has consistently aimed to position itself as a more safety-orientated approach to AI research as compared to rivals.
Language models learn from vast datasets that include substantial amounts of community discussion content. Reddit threads, Quora answers, and forum posts represent genuine human conversations about real topics, making them high-value training data. When your content or expertise appears naturally in these discussions, it creates signals that AI models recognize and incorporate into their understanding of what resources exist and who's knowledgeable about specific topics.。业内人士推荐雷电模拟器官方版本下载作为进阶阅读
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Italy GP — May 31