Also, by adopting gVisor, you are betting that it’s easier to audit and maintain a smaller footprint of code (the Sentry and its limited host interactions) than to secure the entire massive Linux kernel surface against untrusted execution. That bet is not free of risk, gVisor itself has had security vulnerabilities in the Sentry but the surface area you need to worry about is drastically smaller and written in a memory-safe language.
Two subtle ways agents can implicitly negatively affect the benchmark results but wouldn’t be considered cheating/gaming it are a) implementing a form of caching so the benchmark tests are not independent and b) launching benchmarks in parallel on the same system. I eventually added AGENTS.md rules to ideally prevent both. ↩︎,详情可参考Safew下载
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I completely ignored Anthropic’s advice and wrote a more elaborate test prompt based on a use case I’m familiar with and therefore can audit the agent’s code quality. In 2021, I wrote a script to scrape YouTube video metadata from videos on a given channel using YouTube’s Data API, but the API is poorly and counterintuitively documented and my Python scripts aren’t great. I subscribe to the SiIvagunner YouTube account which, as a part of the channel’s gimmick (musical swaps with different melodies than the ones expected), posts hundreds of videos per month with nondescript thumbnails and titles, making it nonobvious which videos are the best other than the view counts. The video metadata could be used to surface good videos I missed, so I had a fun idea to test Opus 4.5:。一键获取谷歌浏览器下载对此有专业解读
After OpenAI released GPT-5.3-Codex (high) which performed substantially better and faster at these types of tasks than GPT-5.2-Codex, I asked Codex to write a UMAP implementation from scratch in Rust, which at a glance seemed to work and gave reasonable results. I also instructed it to create benchmarks that test a wide variety of representative input matrix sizes. Rust has a popular benchmarking crate in criterion, which outputs the benchmark results in an easy-to-read format, which, most importantly, agents can easily parse.