Prompt Engineering in Action you own this product

Shivendra Srivastava and Naresh Vurukonda
  • MEAP began December 2024
  • Publication in Summer 2025 (estimated)
  • ISBN 9781633435919
  • 300 pages (estimated)
  • printed in black & white

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Look inside
Tested techniques for writing excellent AI prompts!

Each LLM seems to have a mind of its own, and it can be challenging to get the exact results you want. Prompt Engineering in Action teaches you to write prompts that generate the text and code you want, regardless of the LLM you choose. In it, you’ll discover structured and reusable prompt patterns that reduce hallucinations, customize LLMs to specific tasks, and improve the quality of your code generation.

Prompt Engineering in Action teaches you practical prompt engineering skills including:

  • Designing context-aware prompts tailored for specific tasks
  • Understanding and minimizing hallucinations
  • When to use prompt patterns such as Persona, Recipe, Template, and Game-Play
  • Utilizing templates to ensure consistent and reusable outputs
  • Integrating external knowledge bases with Retrieval-Augmented Generation (RAG)
  • Building and deploying practical LLM-based apps using LangChain

Prompt Engineering in Action presents patterns, templates, and techniques that help you get consistent, valuable responses from LLMs. You’ll learn how to design precise and context-aware prompts, discover metrics you can use to assess prompt quality, learn methods to scale and collaborate on prompts, and build advanced and agentic AI apps using LangChain.

about the book

Prompt Engineering in Action teaches universal prompting principles, each illustrated with concise examples of a prompt in action. You’ll find more than just simple prompt-and-response methods. It goes beyond the basics of prompting to explore reusability, scaling for prompts, and managing stochastic responses. Dive into prompt patterns such as Persona, Game-Play, and Recipe patterns, and into emerging techniques such as Retrieval-Augmented Generation (RAG) and dynamic agents. You’ll soon be building solutions that are efficient, accurate, and highly adaptable for real-world applications.

about the reader

For readers familiar with the basics of working with LLMs. No specialist knowledge required.

about the authors

Naresh Vurukonda is a Principal Architect at Amgen, where he focuses on building deep learning models and LLM solutions to enhance engineers’ productivity and serve patients on drug accessibility. He holds a master’s degree in computer science from Southern Arkansas University.

Shivendra Srivastava is an Engineering Manager at AWS, where he focuses on building highly available, low-latency, and scalable serverless solutions that power AWS Lambda, Athena, Glue, and Bedrock. He holds a Master’s degree in computer science from Georgia Institute of Technology.

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choose your plan

team

monthly
annual
$49.99
$399.99
only $33.33 per month
  • five seats for your team
  • access to all Manning books, MEAPs, liveVideos, liveProjects, and audiobooks!
  • choose another free product every time you renew
  • choose twelve free products per year
  • exclusive 50% discount on all purchases
  • Prompt Engineering in Action ebook for free