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Agentic AI Engineering with Microsoft Foundry: Design, Build, Evaluate, Monitor, and Deploy Enterprise AI Agents That Solve Real Business Problems
Paperback
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Publisher: Independently Published
Pages: 210
Weight: 0.82
Height: 0.44 Width: 7.00 Depth: 10.00
Language: English
Build AI agents that do more than answer prompts. Build agents that solve real business problems with structure, reliability, evaluation, monitoring, and production discipline.
Many developers can create a quick chatbot, but turning that chatbot into a useful enterprise AI agent is a different challenge. How do you connect agents to trusted business data? How do you give them tools without creating risk? How do you evaluate quality, monitor behavior, control cost, and deploy systems that teams can actually depend on?
Agentic AI Engineering with Microsoft Foundry gives you a practical, step-by-step guide to building enterprise-ready AI agents with Microsoft Foundry, Azure AI services, retrieval-augmented generation, custom tools, evaluation workflows, tracing, and production monitoring.
This book is written for builders who want clear implementation guidance, not vague theory. You will learn how to design agentic AI systems around real business needs, connect models to documents and data, add safe tool use, build code-first agents, create multi-agent workflows, evaluate performance, and prepare agent systems for deployment.
Inside, you will learn how to:
- Set up Microsoft Foundry projects for agent development
- Build code-first agents with practical Python and .NET workflows
- Connect agents to files, Azure AI Search, tools, APIs, and Azure Functions
- Design retrieval-augmented agents that answer from trusted sources
- Create structured outputs for tickets, reports, reviews, and decisions
- Build workflow-based and multi-agent systems with clear responsibilities
- Evaluate groundedness, relevance, tool behavior, safety, and task completion
- Trace, debug, monitor, and improve agents after deployment
- Use checklists, templates, and production-readiness practices to reduce guesswork
What makes this book different is its engineering-first approach. Instead of treating AI agents as impressive demos, it shows how to build them as maintainable software systems with configuration, testing, observability, governance, human review, and measurable quality.
This book is ideal for software developers, AI engineers, cloud engineers, solution architects, enterprise IT teams, technical leads, and anyone responsible for building practical AI applications with Microsoft Foundry and Azure.
If you want to move beyond simple prompts and build enterprise AI agents that can retrieve knowledge, use tools, support workflows, and operate with confidence, get this book and start building agentic AI systems the right way.
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