Quan, E: Developing Agentic AI
Language: English
Published by Independently Published, 2025
- Softcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
AbeBooks seller since August 14, 2006
Condition: New
£ 23.88
Quantity: 2 available
Add to basketItem description from seller
Neuware - 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.…
Seller Inventory # 9798296018151
- Title
- Quan, E: Developing Agentic AI
- Author
- Ethan Quan
- Publisher
- Independently Published
- Publication year
- 2025
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 13
- 9798296018151
- Item weight
- 395 grams
- Dimensions
- 254x178x12 mm
- Series
- Book 2 of 3: AI Agent Mastery Series: Building, Scaling, and Integrating Intelligent AI Systems with Transformers and Context-Aware AI
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.
- 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.
"Synopsis" may belong to another edition of this title.
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