Introduction
Preface, how to use this book, prerequisites, and complete setup instructions to get started.
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The definitive guide to programming—rather than prompting—language models. Build robust, optimized, and self-improving AI applications.
Start ReadingWhat You Will Learn
01. Fundamentals
Understand the core philosophy of DSPy and why "programming" beats "prompting" for complex LLM tasks.
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Learn to define the input/output behavior of your AI modules structurally and type-safely.
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Discover the building blocks of DSPy programs, from simple Predictors to ChainOfThought and Agents.
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Master the art of measuring performance with custom metrics and systematic evaluation loops.
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Use compilers like MIPRO and BootstrapFewShot to automatically optimize your prompts and weights.
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Build RAG systems, classifiers, and intelligent agents ready for production deployment.
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Explore adapters, caching, async operations, debugging, and deployment strategies.
Read Chapter →08. Case Studies
Real-world case studies from enterprise RAG systems to AI code assistants and more.
Read Chapter →09. Appendices
API reference, troubleshooting guide, additional resources, glossary, and community links.
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