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Multi-Agent Coordination Patterns: 5 Powerful Architectures Driving Scalable AI Systems

As AI systems evolve from single-model applications into complex ecosystems, multi-agent coordination patterns have become foundational to scalability and performance. These patterns define how agents collaborate, divide tasks, and share information across systems. From tightly controlled orchestrations to decentralized communication models, each approach offers distinct advantages depending on the use case. This article explores five key multi-agent coordination patterns and explains how they enable more flexible, resilient, and scalable AI systems.