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AI CURATED HOT STORY · 11/11/2026

Amazon Paper Finds Single Agents Usually Beat Multi-Agent Setups in Enterprise Workflows

1 reports archived1 independent sourcesupdated 11/11/2026, 22:03:13
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1 Sources Cross-Validated

A controlled Amazon study compared four agent architectures (eight variants) across 13 enterprise procedures and found multi-agent or skill-based setups consumed 1.4x to 4.7x the tokens of a single agent for mostly marginal gains. The first multi-agent build actually lost to the single agent on task success (58.2% vs 67.4%), while a repaired version won but at the highest token cost. The authors recommend starting with a single agent, measuring success per workflow, and fixing implementation bugs before paying for complexity.

LATEST/A controlled Amazon study compared four agent architectures (eight variants) across 13 enterprise procedures and found multi-agent or skill-based setups consumed 1.4x to 4.7x the tokens of a single agent for mostly marginal gains. The first multi-agent build actually lost to the single agent on task success (58.2% vs 67.4%), while a repaired version won but at the highest token cost. The authors recommend starting with a single agent, measuring success per workflow, and fixing implementation bugs before paying for complexity.

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Total 1 reports · Latest first
  1. Rohan Paul (@rohanpaul_ai)T2·72 pts

    Amazon Paper Finds Single Agents Usually Beat Multi-Agent Setups in Enterprise Workflows

    • Multi-agent or skill-based setups used 1.4x to 4.7x the tokens of a single agent for mostly small gains
    • The first multi-agent build scored 58.2% task success versus 67.4% for the single agent; a repaired version won but cost the most tokens
    • Start with a single agent, measure success per workflow, and fix implementation bugs before adopting a more complex architecture