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Stanford's DeLM framework lets AI agents coordinate directly without a central orchestrator, cutting multi-agent task costs by 50%. A shared knowledge base replaces the central controller, reducing inference dollars and coordination latency. The approach challenges the assumption that agents require a boss at the center.
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