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Module Overview

You’ve built reliable single agents: They follow business rules, select tools accurately, and handle errors gracefully. But real enterprise applications often require multiple specialized agents working together—a research agent feeding an analysis agent, a coordinator routing to domain experts, or agents from different organizations collaborating on complex workflows. Here’s the challenge: Coordinating multiple agents introduces new complexity: workflow orchestration, agent-to-agent delegation, cost management, debugging non-deterministic behavior, and standardized communication protocols. Most multi-agent projects fail not because of individual agent quality, but because of poor coordination architecture. In this module: You’ll learn production-grade patterns for multi-agent systems. We cover workflow orchestration (code-controlled flows), agent orchestration (LLM-controlled delegation), and standardized communication protocols (A2A). You’ll understand when to use each approach, how to prevent delegation loops, manage costs, and build hybrid systems that combine the best of both worlds.

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Learning Objectives

By the end of this module, you will be able to: ✅ Design workflows using sequential, parallel, and conditional patterns
✅ Build hierarchical agent systems with clear role separation
✅ Implement agent orchestration with automatic delegation
✅ Prevent delegation loops and manage orchestration costs
✅ Use standardized A2A protocols for cross-framework integration
✅ Choose between workflow and agent orchestration appropriately
✅ Monitor, debug, and optimize multi-agent systems
✅ Build hybrid architectures combining multiple coordination patterns
💡 Final Note: Multi-agent systems are powerful but complex. The most successful production deployments start simple (2-3 agents), prove value, then scale deliberately. Resist the temptation to build elaborate agent networks before validating that simpler approaches won’t suffice. The goal isn’t maximum agents—it’s maximum impact per dollar and per unit of complexity.