Transform from AI beginner to production-ready developer through a structured, hands-on learning path that covers the complete AI application development lifecycle.

By the end of this book, you'll know how to build modern, production-ready AI systems that go far beyond basic prompting. You'll learn how to use DSPy to automatically optimize your AI systems using advanced techniques like MIPROv2 and GEPA that boost accuracy by 20-50%, integrate external tools and APIs through the Model Context Protocol (MCP), and build production-grade RAG applications with vector databases, embeddings, and intelligent retrieval strategies.

You'll master DSPy fundamentals with type-safe signatures and Pydantic models that eliminate prompt fragility, build sophisticated reasoning systems using ChainOfThought, ReAct, and ProgramOfThought modules, and systematically test and evaluate realiability using custom metrics and LLM-as-a-judge techniques.

Gain real-world experience through two comprehensive capstone projects—RepoRank (GitHub analyzer), CRM Auto Reply (customer support system) while mastering MLflow observability, FastAPI deployment, Docker containerization, and autonomous agent architectures for scalable production systems.

11 Chapters, 4 Appendix, 210+ approx. plus page online book. 5 Chapter and 2 Appendix Available. All chapter will be released in 2025 itself.

Digital access to this title, all updates for this edition.

Available for Pre-booking pricing of 29$.

Entire book will be published in December before Christmas.

Publishing Roadmap Dates

Chapter 1: DSPy: From Prompting to Programming - Done

Chapter 2: Core DSPy Modules - Done

Chapter 3: Evaluating Your DSPy Programs - Done

Chapter 4: Capstone Project - RepoRank - Done

Chapter 5: Model Context Protocol (MCP) - Done

Chapter 6: The Secret Sauce: Optimisers - 28th December

Chapter 7: Observability with MLflow - Done

Chapter 8: Retrieval Augmented Generation - 9th Dec

Chapter 9: Capstone Project - CRM Auto Reply - 20th December

Chapter 10: Building AI Agents with DSPy - 15th December

Chapter 11: Scaling and Productionizing - 24th December

Appendix

• Appendix A: Quick Guide To Python - Done
• Appendix B: Essential AI Glossary & Papers - Done
• Appendix C: Book Glossary - 24th December
• Appendix D: Resources - 30th November

Change log

• Fixed typos and asciidoc to pdf rendering issue in Chapter 1 - 14th Oct 2025
• Appendix A added. Chapter 7th date moved by 2 days for review. - 15th Oct 2025
• Updated the schedule and made the chapter release sequential.
• Chapter 7 updated.
• Github Repository Accompanying The Book - https://github.com/originalankur/dspy-book-codebase ( 10th Nov )
• External reviewer engaged for English language review of each chapter - Review received for Chapter 1, 7, Appendix-a and Appendix-b have been incorporated. Updated PDF has been uploaded ( 10th Nov )
• Chapter 2nd released - 11th Nov 2025. Also updated dates of subsequent chapter - extending it by 1/2 days. However overall release of the book is on schedule.
• Chapter 3rd released - 12th Nov 2025. Added Reference links to GitHub repository for chapter 2 as well.
• Chapter 4th released - 16th Nov 2025. Code will be uploaded on 17th November 2025.
• Chapter 4th code added to GitHub repository on 18th November 2025.
• Chapter 5th released - 25th Nov 2025
• Updated dates for roadmap of release. Delayed by two weeks due to review feedback being incorporated. Also new change in how people are building Agents is also being incorporated. 6th December.