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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Prompt Engineering in Practice: Design, Test, and Improve AI Prompts

Prompt Engineering in Practice: Design, Test, and Improve AI Prompts

Fischer, Rafael
Davies, Richard

Paperback

Series: In Practice

General Computers

Currently unavailable to order

ISBN10: 1633436306
ISBN13: 9781633436305
Publisher: Manning Publications
Published: Oct 20 2026
Pages: 248
Weight: 0.74
Height: 0.91 Width: 7.31 Depth: 9.21
Language: English
Get the eBook free when you register your print book at Manning.

A thoughtful, practical guide to prompt engineering as a real discipline.
--Che Gamble, Davies Group

Sometimes your LLMs return brilliant responses. Other times, not so much. Do you know why? Prompt Engineering in Practice shows you how to move from accidental AI results to reliable, production-grade systems you can deploy with confidence. Written by AI veterans Richard Davies and Rafael Fischer, this book introduces a unique approach: treat prompts as engineered, self-contained interfaces that you can compose, evaluate, and refine. This shift reframes model interactions as a strict software design discipline rather than a series of fuzzy trial-and-error exercises.

Spanning 11 comprehensive chapters, Prompt Engineering in Practice establishes a logical design stack that builds from microscopic syntax to macroscopic system architecture. You'll start by learning to define the structural elements of a prompt, including delimiters and falsifiable constraints, along with linguistic characteristics like precision, directness, and brevity. These techniques equip you to write well-specified prompts that you can successfully incorporate into reusable production components.

You'll then explore the foundational patterns that form the core of prompt engineering and enable you to build robust, scalable agentic workflows. Reviewer Dewang Sultania, Senior Machine Learning Engineer at Netflix, noted The nine-pattern taxonomy provides genuinely useful composable prompt engineering strategies. It's also a great introduction on how LLM-powered systems actually work!

Because LLM responses are consistently inconsistent, the book provides a practical framework to diagnose prompt failures systematically by treating prompts as specifications and investigating sources of variance. Throughout the book, you'll practice a process to systematically analyze and troubleshoot prompt failures as you navigate four distinct phases of the prompt engineering lifecycle--Design, Test, Iterate, Manage. By the time you reach the deployment and operations chapters that conclude the book, you'll be treating unexpected outputs as valuable debuggable system signals that help you isolate where a prompt is underspecified.

Ultimately, Prompt Engineering in Practice shows you how to treat prompts as first-class, maintainable software artifacts. You will learn to eliminate prompt debt by building version-controlled, audited prompt libraries that can be reviewed in pull requests, secured against injection, and managed using role-based access controls. By bridging the gap between prototype experimentation and production operations, this guide provides the exact tools needed to collaborate with cross-functional teams and maintain consistent, safe AI integrations over time.

What's inside

- Eliminate prompt debt with version-controlled, audited prompt libraries

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