ended4월 26일· 1 sources
Lessons from 221 AI Agents: The Hidden Limits of Multi-Agent Scalability
AI 에이전트 221명의 난투극: 대규모 Multi-agent 시스템의 비용과 성능 한계
Why it matters
Scaling multi-agent AI systems reveals critical failure modes where output plateaus while operational costs explode due to context window demands. This experiment proves that effective AI coordination requires sophisticated architectural design rather than simply increasing agent counts or refining prompts.
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Multi-agent AIAI AgentsContext WindowScalabilitySmallville