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15.8 MB
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2866C1D7F1A54EA432BFFEC268802A8104606145
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April 20, 2026, 6:54 a.m.
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(Last updated: April 20, 2026, 6:58 a.m.)
| File | Size |
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| Vurukonda N. Prompt Engineering in Action (MEAP v4) 2025.pdf | 15.8 MB |
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SOURCE: Vurukonda N. Prompt Engineering in Action (MEAP v4) 2025
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COVER
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MEDIAINFO
Textbook in PDF format 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. PART 1 BASICS FIRST! Introduction to Prompt Engineering Prompt Patterns: Basic Types and Templates Prompt Patterns: Advanced Types and Templates PART 2 CRAFTING PROMPTS Prompting Techniques I Prompting Techniques II Retrieval-Augmented Generation Types of RAG Systems: A Deep Dive PART 3 SCALE, DEVELOP, DEPLOY LLM Agents & Tokenization Develop, and Deploy using LangChain/Llama Case Studies Future of Prompt Engineering Appendix A. Setting up LangChain
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