Mastering Agentic AI Workflows with DSPy

Mastering Agentic AI Workflows with DSPy is the definitive hands-on guide to building reliable, transparent, and constraint-driven AI agents using DSPy. This volume focuses on the fundamentals of declarative agent engineering-teaching you how to design modular predictors, define precise behaviors with signatures, and construct stable workflows that eliminate the unpredictability of raw prompting.
You'll learn how DSPy organizes reasoning, manages constraints, and structures outputs through signatures and modules. Step by step, the book walks you through building zero-shot and few-shot modules, designing retrieval-enhanced workflows, shaping behavior with curated datasets, and evaluating agent consistency through DSPy's built-in optimization and evaluation tools.
The book emphasizes correctness, verification, and reproducibility at every stage-showing how to architect workflows that are explainable, debuggable, and maintainable in real production environments.
What You Will Learn

• How declarative signatures enforce predictable agent behavior
• Zero-shot and few-shot module construction with structured I/O
• DSPy-powered RAG pipelines that eliminate prompt instability
• Dataset creation for behavior shaping, evaluation, and benchmarking
• Multi-step workflow design using modular DSPy components
• Debugging, testing, and validating agent outputs with confidence
• Techniques for optimizing agent performance and reducing hallucinations