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{ "item_title" : "Coding the Future", "item_author" : [" Ethan V. Cole "], "item_description" : "Unlock the Next Frontier of AI Development In Coding the Future: Model Content Protocol Meets Agentic AI, you'll dive deep into how the latest breakthroughs in AI architecture are transforming the way autonomous agents understand, interact with, and create intelligent outputs. This book bridges the powerful synergy between Model Content Protocol (MCP) and Agentic AI, giving developers, data scientists, and tech strategists a clear roadmap for building scalable, efficient, and context-aware AI systems. What's Inside:- A practical breakdown of the Model Content Protocol and its role in structuring AI interactions- How agentic AI systems can plan, retrieve, and act autonomously in real-world workflows- Real-world examples of content routing, tool use, and agent memory systems- Strategies for integrating retrieval-augmented generation (RAG) and structured knowledge into intelligent applications- Hands-on architecture patterns, prompt engineering techniques, and automation pipelines Who This Book Is For:- AI developers and engineers building next-gen applications- Tech founders, product managers, and architects exploring agent-based workflows- Researchers and students interested in cutting-edge AI design and protocol systems- Anyone aiming to stay ahead in the rapidly evolving AI ecosystem Why You Should Read It: This book is your essential guide to mastering scalable, autonomous AI workflows. Whether you're coding intelligent agents or designing frameworks for knowledge-driven systems, Coding the Future gives you the insights, tools, and mental models needed to lead in the AI era.", "item_img_path" : "https://covers4.booksamillion.com/covers/bam/9/79/827/699/9798276990699_b.jpg", "price_data" : { "retail_price" : "16.99", "online_price" : "16.99", "our_price" : "16.99", "club_price" : "16.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Coding the Future|Ethan V. Cole

Coding the Future : Model Content Protocol Meets Agentic AI. : How Autonomous Agents Leverage Structured Knowledge to Create, Retrieve, and Act with Pr

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Overview

Unlock the Next Frontier of AI Development In Coding the Future: Model Content Protocol Meets Agentic AI, you'll dive deep into how the latest breakthroughs in AI architecture are transforming the way autonomous agents understand, interact with, and create intelligent outputs. This book bridges the powerful synergy between Model Content Protocol (MCP) and Agentic AI, giving developers, data scientists, and tech strategists a clear roadmap for building scalable, efficient, and context-aware AI systems. What's Inside:
- A practical breakdown of the Model Content Protocol and its role in structuring AI interactions
- How agentic AI systems can plan, retrieve, and act autonomously in real-world workflows
- Real-world examples of content routing, tool use, and agent memory systems
- Strategies for integrating retrieval-augmented generation (RAG) and structured knowledge into intelligent applications
- Hands-on architecture patterns, prompt engineering techniques, and automation pipelines Who This Book Is For:
- AI developers and engineers building next-gen applications
- Tech founders, product managers, and architects exploring agent-based workflows
- Researchers and students interested in cutting-edge AI design and protocol systems
- Anyone aiming to stay ahead in the rapidly evolving AI ecosystem Why You Should Read It: This book is your essential guide to mastering scalable, autonomous AI workflows. Whether you're coding intelligent agents or designing frameworks for knowledge-driven systems, Coding the Future gives you the insights, tools, and mental models needed to lead in the AI era.

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Details

  • ISBN-13: 9798276990699
  • ISBN-10: 9798276990699
  • Publisher: Independently Published
  • Publish Date: December 2025
  • Dimensions: 8.5 x 5.5 x 0.16 inches
  • Shipping Weight: 0.22 pounds
  • Page Count: 78

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