Are you tired of unpredictable prompts, brittle logic, and AI systems that behave differently every time you run them? What if you could build AI agents that behave consistently, follow well-defined constraints, and can be engineered like reliable software?
Building Agentic AI with DSPy introduces a practical, engineering-driven approach for constructing predictable, modular, and testable AI agents using DSPy’s declarative programming model. Instead of relying on prompt experimentation, DSPy allows you to define exact behaviors using structured Python modules—enabling agents that are stable, auditable, and easy to maintain.
This book walks you step-by-step through the fundamentals of DSPy and gives you everything you need to design robust agent workflows, build predictive modules, and manage retrieval, datasets, and integration without prompt chaos.
✅ What You’ll Learn
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Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de America
Paperback. Condición: new. Paperback. Are you tired of unpredictable prompts, brittle logic, and AI systems that behave differently every time you run them? What if you could build AI agents that behave consistently, follow well-defined constraints, and can be engineered like reliable software?Building Agentic AI with DSPy introduces a practical, engineering-driven approach for constructing predictable, modular, and testable AI agents using DSPy's declarative programming model. Instead of relying on prompt experimentation, DSPy allows you to define exact behaviors using structured Python modules-enabling agents that are stable, auditable, and easy to maintain.This book walks you step-by-step through the fundamentals of DSPy and gives you everything you need to design robust agent workflows, build predictive modules, and manage retrieval, datasets, and integration without prompt chaos. What You'll LearnHow DSPy eliminates brittle prompts through declarative I/O modelingHow predictive modules and signatures create reliable agent behaviorHow to design reusable components for modular AI workflowsHow to build zero-shot and few-shot modules with structured constraintsHow to integrate Retrieval-Augmented Generation (RAG) the correct wayHow to create datasets, benchmarks, and evaluations for predictable agentsHow to build complete end-to-end workflows for real-world tasksHow to test, debug, and validate agent behavior with confidenceHow to prepare your work for optimization, scaling, and production Who This Book Is ForAI engineers building serious, reliable applicationsPython developers moving from prompts to agent engineeringML practitioners deploying structured workflowsTechnical founders and team leads designing AI systems at scaleWhether you're new to DSPy or upgrading from traditional prompt engineering, this book gives you the clear mental model and hands-on patterns required to build dependable, production-ready agents.If you want predictable AI behavior, modular workflows, and a foundation for advanced agent systems, this is your starting point. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Nº de ref. del artículo: 9798274025430
Cantidad disponible: 1 disponibles
Librería: PBShop.store UK, Fairford, GLOS, Reino Unido
PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000. Nº de ref. del artículo: L2-9798274025430
Cantidad disponible: Más de 20 disponibles
Librería: CitiRetail, Stevenage, Reino Unido
Paperback. Condición: new. Paperback. Are you tired of unpredictable prompts, brittle logic, and AI systems that behave differently every time you run them? What if you could build AI agents that behave consistently, follow well-defined constraints, and can be engineered like reliable software?Building Agentic AI with DSPy introduces a practical, engineering-driven approach for constructing predictable, modular, and testable AI agents using DSPy's declarative programming model. Instead of relying on prompt experimentation, DSPy allows you to define exact behaviors using structured Python modules-enabling agents that are stable, auditable, and easy to maintain.This book walks you step-by-step through the fundamentals of DSPy and gives you everything you need to design robust agent workflows, build predictive modules, and manage retrieval, datasets, and integration without prompt chaos. What You'll LearnHow DSPy eliminates brittle prompts through declarative I/O modelingHow predictive modules and signatures create reliable agent behaviorHow to design reusable components for modular AI workflowsHow to build zero-shot and few-shot modules with structured constraintsHow to integrate Retrieval-Augmented Generation (RAG) the correct wayHow to create datasets, benchmarks, and evaluations for predictable agentsHow to build complete end-to-end workflows for real-world tasksHow to test, debug, and validate agent behavior with confidenceHow to prepare your work for optimization, scaling, and production Who This Book Is ForAI engineers building serious, reliable applicationsPython developers moving from prompts to agent engineeringML practitioners deploying structured workflowsTechnical founders and team leads designing AI systems at scaleWhether you're new to DSPy or upgrading from traditional prompt engineering, this book gives you the clear mental model and hands-on patterns required to build dependable, production-ready agents.If you want predictable AI behavior, modular workflows, and a foundation for advanced agent systems, this is your starting point. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Nº de ref. del artículo: 9798274025430
Cantidad disponible: 1 disponibles