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

Build Smarter AI Systems—from Blueprint to ProductionAI 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 deploymentsThis Book Is For:• AI engineers and software developers• Data scientists transitioning into AI productization• Technical PMs and architects building scalable LLM-powered applicationsIncludes diagrams, code templates, performance metrics, and best practices. No fluff—just actionable AI engineering knowledge. Read more