Most teams don't fail at AI because they lack models-they fail because they cannot turn models into reliable, scalable autonomous systems that actually run real business operations. Building agents that can reason, use tools, coordinate workflows, and operate safely inside enterprise environments is where most projects break down.
AI Agent Engineering with Microsoft Foundry delivers a practical, systems-first approach to solving this gap. It shows you how to design and deploy autonomous AI agents that move beyond chat interfaces and become fully functional enterprise execution systems. Using Microsoft Foundry as the foundation, the book explains how to build agent architectures that connect tools, manage workflows, maintain context, and operate with production-grade reliability at scale.
Inside, you will learn how to design AI agents that are not just intelligent, but operationally sound. You will gain the ability to:
Architect autonomous agents that plan, reason, and execute multi-step workflows
Integrate enterprise tools, APIs, and business systems into agent pipelines
Build reliable multi-agent systems that coordinate tasks across complex environments
Implement memory, context management, and retrieval systems for grounded decision-making
Apply guardrails, governance, and safety constraints for production deployment
Optimize performance, latency, and cost in large-scale AI systems
Design observability, logging, and debugging systems for agent-driven workflows
Deploy and scale AI agents in enterprise environments using Microsoft Foundry
Rather than focusing on isolated model capabilities, this book trains you to think like an AI systems engineer-someone who understands how intelligence becomes infrastructure inside modern organizations.
If you are ready to move beyond experimental AI prototypes and build autonomous systems that can support real business operations at scale, this book is your practical blueprint.
