Overview

This book is a rigorous, workflow-driven manual for mastering modern prompt engineering. Context Prompt Engineering treats prompts as modular, testable software components and guides readers through the design, orchestration, and evaluation of prompts for large language models (LLMs). It explores context management, reproducibility, and system integration, showing how to build scalable, efficient, and reliable prompt systems for real-world applications. Through detailed examples and practical methods, you will learn how to design reusable prompt templates, chain prompts for complex workflows, manage context effectively, and evaluate outputs using accuracy, safety, and cost metrics. You will also discover how to integrate your prompts with Retrieval-Augmented Generation (RAG), agent systems, and multi-model pipelines for production environments. Whether you are an engineer, researcher, or AI product lead, this book provides the tools and frameworks needed to build persuasive, optimized, and reproducible prompt systems that scale efficiently. Who This Book Is For Prompt engineers and AI developers building robust prompt stacks for production. Researchers focused on prompt evaluation and reproducible experiments. Product teams optimizing token costs, reliability, and output quality. What You Will Learn How to design modular, reusable prompt templates and meta-prompts for diverse tasks. How to implement prompt chaining and orchestration for multi-step workflows. How to manage context using chunking, compression, and token budgeting techniques. How to build evaluation frameworks using accuracy, helpfulness, safety, and cost metrics. How to apply versioning, automated testing, and A/B experimentation to prompts. How to integrate prompts with RAG systems, AI agents, and hybrid pipelines. How to optimize performance for scalability and cost efficiency in production.

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