Overview

Unlock the full potential of modern AI by mastering context engineering-the discipline that turns raw language models into reliable, memory-aware, and production-ready systems. In this hands-on guide, you will: Learn how to design prompts that maintain coherence under complex multi-turn scenarios. Implement short-term, long-term, and hybrid memory systems for AI continuity. Build retrieval-augmented generation (RAG) pipelines with vector databases. Integrate external tools and APIs with the Model Context Protocol (MCP). Gain practical templates, reusable snippets, and architectural patterns for production-ready AI applications. Written for developers, AI researchers, and professionals, this book bridges theory and practice, providing step-by-step guidance, working code examples, and real-world projects that transform your AI models into systems you can trust.

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