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Rohan Paul· @rohanpaul_ai · X· · Original publication time AI score54

Salesforce paper catalogs 20 failure modes in AI agent collaboration across partiesMachine translation

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Across more than 2,500 agent-to-agent sessions in 488 scenarios, the study found that agents did not re-fetch documents to check peers’ factual claims and mainly contacted peers when prompted. In one service-level dispute, a $24,000 settlement passed all 10 outcome checks while the vendor agent leaked confidential details.

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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"

ReplyRohan 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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