AI Engineering In Practice: Multi-Agent System, RAG, MCP, and LLMs

By: Stride, Noa

Build Smarter AI Systems--from Blueprint to Production

AI Engineering in Practice is your hands-on guide to designing, building, and deploying intelligent systems using Multi-Agent Architectures, Retrieval-Augmented Generation (RAG), the Model Context Protocol (MCP), and Large Language Models (LLMs).

Whether you're a machine learning engineer, AI product lead, or aspiring technical founder, this book gives you practical tools, proven design patterns, and expert insights to go beyond theory and deliver real-world AI solutions.

What You'll Learn:

- How to build and orchestrate multi-agent systems with context-aware collaboration
- Step-by-step RAG workflows using external knowledge sources
- Techniques for effective prompt engineering and managing LLM output
- Applying MCP to structure intelligent communication between agents
- Real-world case studies from enterprise AI deployments

This Book Is For:

- AI engineers and software developers
- Data scientists transitioning into AI productization
- Technical PMs and architects building scalable LLM-powered applications

Includes diagrams, code templates, performance metrics, and best practices. No fluff--just actionable AI engineering knowledge.

• Format: Paperback
• Language: English
• ISBN: B0FBS7RBBM
• ISBN13: 9798286260560
• Release Date: June 2025
• Publisher: Independently Published
• Length: 158 Pages
• Weight: 0.84 lbs.
• Dimensions: 0.3" x 8.5" x 11.0"