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{ "item_title" : "AI Engineering In Practice", "item_author" : [" Noa Stride "], "item_description" : "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.", "item_img_path" : "https://covers1.booksamillion.com/covers/bam/9/79/828/626/9798286260560_b.jpg", "price_data" : { "retail_price" : "17.99", "online_price" : "17.99", "our_price" : "17.99", "club_price" : "17.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
AI Engineering In Practice|Noa Stride

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

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Overview

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.

This item is Non-Returnable

Details

  • ISBN-13: 9798286260560
  • ISBN-10: 9798286260560
  • Publisher: Independently Published
  • Publish Date: June 2025
  • Dimensions: 11 x 8.5 x 0.34 inches
  • Shipping Weight: 0.84 pounds
  • Page Count: 158

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