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Multi-Agent Orchestration: Three Patterns for Complex AI Workflows

Multi-Agent Orchestration: Three Patterns for Complex AI Workflows

via Dev.toMuhammad Arslan

Building production-grade AI systems with HazelJS Agent Runtime Introduction The future of AI isn't single-purpose chatbots—it's coordinated teams of specialized agents working together to solve complex problems. Just as modern software systems evolved from monolithic applications to microservices, AI systems are evolving from single-agent interactions to multi-agent orchestration. But building multi-agent systems is hard. You need to: Route tasks to the right specialist Coordinate execution across multiple agents Handle failures gracefully Maintain state across agent boundaries Observe what's happening in your system This is where HazelJS Agent Runtime shines. It provides three complementary patterns for multi-agent orchestration, each designed for different use cases: @Delegate — Peer-to-peer agent delegation AgentGraph — DAG-based workflow pipelines SupervisorAgent — LLM-driven dynamic routing In this article, we'll explore each pattern, understand when to use them, and build a comp

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