Hands-On Context Engineering with DSPy: Build Self-Improving AI Pipelines, RAG and Agentic Workflows for Developers and Data Practitioners
Master the Future of AI Systems with DSPy and Context Engineering
In today's fast-moving world of large language models, context engineering is the key to building reliable, scalable, and intelligent applications. This hands-on guide shows you how to unlock the full potential of DSPy, the framework designed to simplify, optimize, and automate AI pipelines.
Whether you're a developer, data scientist, or AI enthusiast, this book takes you step by step through building self-improving pipelines, tuning prompts and parameters automatically, integrating with Langfuse and MLflow, and deploying at scale in cloud environments. Every concept is paired with practical, executable examples-so you don't just learn the theory, you apply it immediately to real-world scenarios like retrieval-augmented generation (RAG).
What sets this book apart is its clear, professional style and its focus on production-ready systems. By the end, you'll know how to monitor, improve, and maintain DSPy applications with confidence-turning prototypes into robust, enterprise-grade solutions.
Why this book?
Comprehensive yet practical: Covers everything from DSPy basics to advanced optimization loops.
Future-proof skills: Learn how to scale across multiple models, providers, and production environments.
Author credibility: Written by Roberto Pizzlo, a technology author known for distilling complex systems into clear, actionable guides.
This isn't just another AI book-it's your hands-on companion for mastering the art of context engineering and building intelligent systems that get better with time.
Inside the Book (Table of Contents Highlights)
Chapter 1: Foundations of Context Engineering with DSPy
Chapter 4: Building Retrieval-Augmented Generation Pipelines
Chapter 6: Ensuring Reliability with Assertions and Evaluation
Chapter 8: Experiment Tracking with Langfuse and MLflow
Chapter 9: Building Self-Improving Pipelines with DSPy Compilers
Chapter 10: Deploying and Maintaining DSPy Applications in Production
Appendices: API Quick Reference, Troubleshooting, Tools, and Glossary
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