Mastering LLM Tool Calling
Andrew Hooper
Sold by PBShop.store US, Wood Dale, IL, U.S.A.
AbeBooks Seller since April 7, 2005
New - Soft cover
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Add to basketSold by PBShop.store US, Wood Dale, IL, U.S.A.
AbeBooks Seller since April 7, 2005
Condition: New
Quantity: Over 20 available
Add to basketNew Book. Shipped from UK. Established seller since 2000.
Seller Inventory # L2-9798245118710
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:
Design LLM systems that reason, act, and recover reliably in production
Safely deploy prompt, model, and tool changes using canary and staged rollouts
Reduce hallucinations, retries, and runaway tool calls
Build systems that are observable, debuggable, and cost-aware
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 ForSoftware engineers building LLM-powered applications
AI engineers working on agentic or tool-augmented systems
Technical leads responsible for reliability, deployment, and scale
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.
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