Large language models have made intelligent agents practical at scale, but early frameworks like AutoGen and Semantic Kernel revealed critical gaps when moving from demos to production: runaway token costs, unreliable execution, missing governance, and no built-in persistence for multi-day workflows. The Microsoft Agent Framework solves these problems by unifying the best ideas from both predecessors into a single, production-ready platform. Agents become composable microservices, workflows become deterministic graphs, human oversight becomes a first-class citizen, and external integration becomes standardized through the Model Context Protocol (MCP) and Agent-to-Agent (A2A) protocol. This comprehensive guide takes you from foundational concepts to advanced multi-agent patterns, enterprise-grade security, observability, and a complete capstone project-an automated employee onboarding system that provisions accounts, orders equipment, waits for HR approval, and runs reliably for days. You'll learn how to: Migrate existing AutoGen and Semantic Kernel code to the new framework with minimal changesBuild deterministic workflows that guarantee termination and predictable costImplement human-in-the-loop gates for compliance and governanceConnect agents to internal APIs and external services using MCPExpose agents as reusable services with the A2A protocolSecure your systems with RBAC, content safety, and managed identitiesTrace every agent decision with OpenTelemetry and Azure MonitorControl token spend and context windows across long-running processesWhether you're an enterprise architect designing governed AI platforms, a developer migrating legacy agent code, or a team leader building production multi-agent systems in finance, healthcare, logistics, or government, this book provides the patterns, code examples, migration cheat sheets, protocol references, and glossary you need to build reliable, observable, and secure agent systems at scale. Perfect for readers interested in: Multi-agent systems architectureLLM orchestration and workflow automationHuman-in-the-loop AIAutoGen migration to productionSemantic Kernel to Microsoft Agent FrameworkEnterprise AI governance and observabilityStart building production-ready agent systems today with the unified platform Microsoft created for the real world.
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