Evidence record 14151 · automatically gathered

Toward an Organizational Science of Multi-Agent LLM Systems: Decoupling Who, How, and Which Algorithm

Multi-agent frameworks built on large language models (LLMs) routinely entangle three logically distinct concerns: who is on the team (organization), how members align (coordination), and which algorithm fuses their work (collaboration protocol). IMACS (Intelligent Multi-Agent Collaboration System) separates the three into orthogonal, independently swappable layers. Classic organizational theory (Belbin roles, Mintzberg coordination, RACI accountability) becomes executable, validated configurati

Record details

Published: 28 July 2026
Source: arXiv
Category: Research
Topics: Agents & autonomy · Transparency
Retrieved: 29 July 2026

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ethics.ai (28 July 2026), “Toward an Organizational Science of Multi-Agent LLM Systems: Decoupling Who, How, and Which Algorithm,” evidence record 14151, https://ethics.ai/record/14151 (originally published by arXiv).

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