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Rohan Paul (@rohanpaul_ai)· · 原发布时间

微软论文称:无主管编码智能体团队扩大后得分更高、完成更快

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AI 辅助摘要

微软一篇论文称,在 ProgramBench 的 200 道任务中选取的 5 道最难题上,无主管编码智能体团队从 1 个扩至 128 个时,平均得分每一步都提高。其 Agensh 方案让智能体自行认领子任务,并通过共享 Git 仓库和任务板协作;论文未报告大型团队的成本。

正文 · 原文

Turns out coding agents don't need a boss:

New Microsoft paper finds that bigger teams of coding agents score higher and get there sooner when agents claim their own tasks without a central manager.

Even on the 5 hardest of ProgramBench's 200 tasks, scaling a manager-free team from 1 to 128 agents raised the average score at every step.

so for big jobs, add agents and let them coordinate through shared tools with no lead agent.

Popular multi-agent coding tools send all work through 1 lead agent, which can only manage so many helpers.

Agensh drops the lead agent. Each agent claims a sub-task, builds and tests it, merges it into a shared Git repo, and logs findings on a shared board.

Every run used 1 model, and the paper does not report what large teams cost.

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