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A practical breakdown of coordination patterns for multi-agent AI systems in production, emphasizing infrastructure over model choice, with patterns like shared memory, async message boards, self-improvement loops, crash-resume checkpoints, and cross-session deduplication.
Anyscale published a technical guide on deploying production-ready AI agents using Ray Serve, MCP, and A2A protocols. The article addresses common infrastructure bottlenecks by proposing a decoupled microservices architecture that enables independent scaling of LLMs, tools, and agents.