Context Engineering

AI coding agents can write code fast, but they need codebases built for collaboration. This book shows experienced engineers how to design, test and maintain software that works seamlessly with tools like Copilot, Cursor and Claude Code. Practical patterns, real projects and proven workflows help you build systems that scale with AI.

Move beyond individual prompts and engineer the full information environment an AI model receives. Learn to design, test, measure, and govern context for reliable AI workflows.

First, memory left the mind and entered marks, books, and digital text. Then a machine met language—but saw no words, stories, or meaning. It saw bytes, tokens, and numbers.The river carried stories farther than any ____.How does AI find traveler? Token follows the hidden journey: learned patterns meet context, tokens are scored, one is selected, and the question begins again—What comes next?

Go beyond prompts and learn how to build AI systems that hold up in production. This book shows how to make context the foundation of reliable LLM applications, covering practical patterns, real trade-offs and proven engineering techniques with clear examples you can put to work right away.

Discover how the Model Context Protocol is transforming the way AI applications connect to tools, data, and external systems. With clear explanations and practical guidance, this book shows you how to build, secure, and deploy production-ready MCP solutions, from your first server to enterprise-scale AI applications.