Mastering LLM Tool Calling
Language: English
Published by Independently Published, 2026
- Softcover
- New

Seller: PBShop.store US, Wood Dale, IL, U.S.A.PBShop.store US
AbeBooks seller since April 7, 2005
Condition: New
£ 22.88
Quantity: Over 20 available
Add to basketItem description from seller
Seller Inventory # L2-9798245118710
- Title
- Mastering LLM Tool Calling
- Author
- Andrew Hooper
- Publisher
- Independently Published
- Publication year
- 2026
- Condition
- New
- Binding
- PAP
- Language
- English
- ISBN 13
- 9798245118710
- Item weight
- 422 grams
What if deploying an AI system was more dangerous than building it?
This book is a practical, experience-driven guide to designing, deploying, and scaling real-world LLM systems that rely on tools, workflows, and agentic behavior—where small changes can cause cascading failures, silent cost explosions, or unpredictable outcomes.
Rather than focusing on toy demos or surface-level theory, this book shows you how modern AI systems actually behave in production. You’ll learn how agentic LLMs interact with tools, APIs, databases, and orchestration layers—and how to design them to remain reliable, observable, and safe as they evolve.
Through clear explanations, concrete examples, and battle-tested patterns, the book breaks down complex topics such as tool calling, context management, deployment strategies, failure handling, and system evaluation—without unnecessary jargon or academic abstraction.
What You’ll GainBy the end of this book, you’ll be able to:
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Design LLM systems that reason, act, and recover reliably in production
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Safely deploy prompt, model, and tool changes using canary and staged rollouts
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Reduce hallucinations, retries, and runaway tool calls
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Build systems that are observable, debuggable, and cost-aware
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Apply proven architectural patterns used in real agentic AI platforms
Most AI books stop at model usage. This one goes further—into system behavior, operational risk, and long-term maintainability. It treats LLMs not as magic APIs, but as probabilistic components that must be engineered with discipline.
The focus is not on trends, but on enduring design patterns you can reuse across tools, models, and frameworks—whether you’re building internal copilots, autonomous workflows, or customer-facing AI products.
Who This Book Is For-
Software engineers building LLM-powered applications
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AI engineers working on agentic or tool-augmented systems
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Technical leads responsible for reliability, deployment, and scale
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Anyone moving from prototypes to production-grade AI systems
If you’re ready to stop guessing how your AI behaves in production—and start building systems you can trust—this book will show you how.
Build smarter. Deploy safer. Scale with confidence.
"Synopsis" may belong to another edition of this title.
PBShop.store US
Wood Dale, IL, U.S.A.
AbeBooks seller since April 7, 2005
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