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Salesforce 论文梳理跨主体 AI 智能体协作的 20 类失败模式

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研究在 488 个情境中运行逾 2,500 次智能体间会话,发现智能体不会主动重新获取文件以核查同伴的事实主张,联系同伴也主要依赖提示词要求。一个服务争议案例中,2.4 万美元的和解通过全部 10 项结果检查,但供应商智能体泄露了机密细节。

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– arxiv. org/abs/2610.19342

Title: "Why Do Agent Teams Fail Across Boundaries? A Failure Taxonomy for Agent-to-Agent Systems with Private States"

回复Rohan Paul@rohanpaul_ai
New Salesforce paper finds that agents acting for different parties never verify each other's claims unprompted, so teams inherit their weakest agent's errors. Agents increasingly coordinate with agents that represent other people or companies, each with private files, tools, and goals. Existing failure studies assume 1 orchestrator or a shared workspace. They ran over 2,500 agent-to-agent sessions across 488 scenarios, using Claude Code, Codex, and Cursor in separate sandboxes. They catalogued 20 failure modes from the traces. No agent re-fetched a document to test a peer's factual claim, and agents contacted peers mainly when the prompt told them to. In 1 service-level dispute, a $24,000 settlement passed all 10 outcome checks while the vendor agent leaked confidential details. If your agent talks to outside agents, build checks into the protocol and score each agent against the party it serves, not the team result.
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