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About<br>About the Book
AI agents are everywhere, or at least everyone claims they are. But building an agent that reliably uses external tools, APIs, and databases to complete real tasks is a fundamentally different engineering challenge than writing prompts or fine-tuning models. This book bridges the gap between hype and reality. It walks you through five production-grade frameworks (DSPy, Pydantic AI, Claude Agent SDK, OpenAI Agents SDK, Google ADK), showing how each one approaches tool use, orchestration, and safety with runnable code examples, architectural comparisons, and hard-won lessons from teams deploying agents at scale.<br>Forward-Looking Disclaimer: This book was written with the agent framework landscape as it exists in mid-2026. Model versions, pricing tiers, API surfaces, and feature availability change rapidly. Where this manuscript references specific model names (for example, “GPT-5” or “Claude Sonnet 4”), these are illustrative projections based on publicly announced roadmaps and should be treated as such. All framework documentation URLs and code examples have been verified against live sources at the time of writing, but API surfaces may evolve. The engineering principles, patterns, and trade-off analyses presented here remain valid regardless of which specific model versions or framework releases you are using.<br>On “War Stories” and Illustrative Scenarios: Throughout this book, you will encounter anecdotes framed as consulting experiences. These are composite scenarios built from documented production issues, community forums, and engineering postmortems across the agent ecosystem. They are intended for pedagogical illustration to demonstrate real failure modes and debugging patterns rather than as specific verifiable case studies of named organizations. The underlying technical lessons, however, reflect genuine production challenges that teams face when deploying agents at scale.
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Author<br>About the Author
Steve T.Steve T. is an experienced IT and cybersecurity professional with more than 20 years of hands-on expertise spanning application security, infrastructure security, and vulnerability management. Having started his career during the early evolution of modern web technologies, he has witnessed firsthand the transformation of enterprise systems, software development practices, and the cybersecurity landscape.<br>His technical background covers a broad range of disciplines, including web application security, penetration testing, security architecture reviews, secure software development, incident response, and vulnerability research. With extensive experience analyzing complex systems at both the application and operating system levels, Steve combines deep technical knowledge with a practical understanding of real-world business and security challenges.<br>Throughout his career, he has worked across multiple industries, helping organizations identify, assess, and remediate security risks in critical environments. His approach emphasizes pragmatic security, balancing robust protection with operational and business requirements. Through continuous engagement with emerging technologies and evolving threats, Steve remains committed to advancing secure and resilient IT environments.
Contents<br>Table of Contents
Building Systems That Use Tools and APIs with DSPy, Pydantic AI, Claude SDK, OpenAI Agents SDK, and Google ADK<br>A Unified Guide to DSPy, OpenAI Agents SDK, Claude Agent SDK, Google ADK, and Beyond<br>Introduction: The Agent Revolution: Why Tools Change Everything<br>Chapter 1: The Anatomy of an AI Agent<br>Chapter 2: Designing Tools That Agents Can Use Well<br>Chapter 3: DSPy: Programming LLM Pipelines, Not Prompts<br>Chapter 4: Pydantic AI: Type-Safe Agents the Python Way<br>Chapter 5: Claude Agent SDK: In-Process Tools and Built-in Execution<br>Chapter 6: OpenAI Agents SDK: Lightweight Orchestration with Handoffs<br>Chapter 7: Google ADK: Graph-Based Workflows for Enterprise Scale<br>Chapter 8: Cross-Framework Patterns: What Works Everywhere<br>Chapter 9: Productionizing Agent Systems<br>Chapter 10: The Future of Agent Tool Use<br>Conclusion: Choosing Your Path<br>Glossary of Key Terms<br>Index<br>References
Framework Documentation<br>DSPy (Declarative Self-improving Python)<br>Pydantic AI<br>Claude Agent SDK<br>OpenAI Agents SDK<br>Google ADK (Agent Development Kit)<br>MCP Ecosystem
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