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{ "item_title" : "Developing Agentic AI", "item_author" : [" Ethan Quan "], "item_description" : "Master the art of building scalable and reliable autonomous systems with Developing Agentic AI: Patterns and Architectures for Autonomous Systems, a definitive guide tailored for AI engineers. Authored by Ethan Quan, this 14-chapter book explores cutting-edge workflow patterns and architectures, diving into goal decomposition, ReAct reasoning, and reflection loops to create intelligent agentic systems. Learn to implement tool chaining, orchestrate multi-agent collaborations, and manage short-term and long-term memory layers with practical code snippets in Python and TypeScript.The book addresses scalability strategies like rate limiting and sandbox execution, self-healing deployments, and monitoring for drift with performance optimization techniques. Discover governance models for responsible AI, cost optimization in agentic workflows, and the power of low-code agent factories for rapid development. Enriched with real-world case studies-such as scaling DevOps and customer support agents-this guide bridges the gap from ad-hoc scripts to robust, production-ready solutions. Ideal for AI engineers seeking to design resilient, maintainable agentic systems, this book requires no advanced prerequisites-just a drive to innovate. With concise tutorials and actionable checklists, achieve impactful results quickly.Key Topics: Agentic systems, workflow patterns, goal decomposition, ReAct reasoning, reflection loops, tool chaining, multi-agent collaboration, memory management, scalability, rate limiting, self-healing deployments, drift monitoring, governance, cost optimization, low-code development, real-world case studies.Who This Book Is For: AI Engineers designing autonomous workflows.Developers building scalable agentic architectures.Data Scientists optimizing multi-agent systems.Product Leaders overseeing AI system reliability.No prior agentic system expertise needed-just a passion for AI innovation.Why Choose This Book?Comprehensive Approach: From workflow patterns to production-ready systems.Practical Insights: Hands-on tutorials and code for immediate application.Future-Focused: Explores emerging trends in agentic system design.Ready to develop scalable, reliable agentic AI? Get Developing Agentic AI: Patterns and Architectures for Autonomous Systems today and revolutionize your AI engineering projects", "item_img_path" : "https://covers4.booksamillion.com/covers/bam/9/79/829/601/9798296018151_b.jpg", "price_data" : { "retail_price" : "19.00", "online_price" : "19.00", "our_price" : "19.00", "club_price" : "19.00", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Developing Agentic AI|Ethan Quan

Developing Agentic AI : Patterns and Architectures for Autonomous Systems: A Practical Guide for AI Engineers to Build Scalable and Reliable Agents

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Overview

Master the art of building scalable and reliable autonomous systems with Developing Agentic AI: Patterns and Architectures for Autonomous Systems, a definitive guide tailored for AI engineers. Authored by Ethan Quan, this 14-chapter book explores cutting-edge workflow patterns and architectures, diving into goal decomposition, ReAct reasoning, and reflection loops to create intelligent agentic systems. Learn to implement tool chaining, orchestrate multi-agent collaborations, and manage short-term and long-term memory layers with practical code snippets in Python and TypeScript.
The book addresses scalability strategies like rate limiting and sandbox execution, self-healing deployments, and monitoring for drift with performance optimization techniques. Discover governance models for responsible AI, cost optimization in agentic workflows, and the power of low-code agent factories for rapid development. Enriched with real-world case studies-such as scaling DevOps and customer support agents-this guide bridges the gap from ad-hoc scripts to robust, production-ready solutions. Ideal for AI engineers seeking to design resilient, maintainable agentic systems, this book requires no advanced prerequisites-just a drive to innovate. With concise tutorials and actionable checklists, achieve impactful results quickly.
Key Topics: Agentic systems, workflow patterns, goal decomposition, ReAct reasoning, reflection loops, tool chaining, multi-agent collaboration, memory management, scalability, rate limiting, self-healing deployments, drift monitoring, governance, cost optimization, low-code development, real-world case studies.
Who This Book Is For:

  • AI Engineers designing autonomous workflows.
  • Developers building scalable agentic architectures.
  • Data Scientists optimizing multi-agent systems.
  • Product Leaders overseeing AI system reliability.
  • No prior agentic system expertise needed-just a passion for AI innovation.
Why Choose This Book?
  • Comprehensive Approach: From workflow patterns to production-ready systems.
  • Practical Insights: Hands-on tutorials and code for immediate application.
  • Future-Focused: Explores emerging trends in agentic system design.
Ready to develop scalable, reliable agentic AI? Get Developing Agentic AI: Patterns and Architectures for Autonomous Systems today and revolutionize your AI engineering projects

This item is Non-Returnable

Details

  • ISBN-13: 9798296018151
  • ISBN-10: 9798296018151
  • Publisher: Independently Published
  • Publish Date: July 2025
  • Dimensions: 10 x 7 x 0.47 inches
  • Shipping Weight: 0.87 pounds
  • Page Count: 222

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