Cursor uses Apple’s Seatbelt (sandbox-exec) on macOS and Landlock plus seccomp on Linux. It generates a dynamic policy at runtime based on the workspace: the agent can read and write the open workspace and /tmp, read the broader filesystem, but cannot write elsewhere or make network requests without explicit approval. This reduced agent interruptions by roughly 40% compared to requiring approval for every command, because the agent runs freely within the fence and only asks when it needs to step outside.
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Testing LLM reasoning abilities with SAT is not an original idea; there is a recent research that did a thorough testing with models such as GPT-4o and found that for hard enough problems, every model degrades to random guessing. But I couldn't find any research that used newer models like I used. It would be nice to see a more thorough testing done again with newer models.
刘年丰:不太行,主要有两层理由。,更多细节参见91视频