The Context Engineering Lab: Hands-On Projects in Prompt Design, Memory Systems, RAG, MCP, and Multi-Agent Workflows to Build Real-World AI Applicatio
The Context Engineering Lab: Hands-On Projects in Prompt Design, Memory Systems, RAG, MCP, and Multi-Agent Workflows to Build Real-World AI Applications
How do you turn a language model into a dependable system that remembers, retrieves, reasons, and collaborates? The answer lies in context engineering-a discipline that transforms raw AI capabilities into real-world applications.
This book is a practical guide for developers, researchers, and professionals who want to move beyond theory and build AI systems that actually work at scale. Through hands-on projects, it shows how to design prompts that hold up under pressure, implement memory systems that preserve continuity, construct retrieval-augmented generation (RAG) pipelines, integrate external tools with the Model Context Protocol (MCP), and coordinate multi-agent workflows for complex tasks.
What sets this book apart is its focus on building, not just explaining. Each chapter is structured around applied learning:
Foundations of Context Engineering explains why context is the missing piece in modern AI.
Prompt Design as a Systematic Discipline shows how to structure prompts and evaluate their reliability.
Memory Systems for AI Continuity introduces short-term, long-term, and hybrid approaches with working code examples.
Retrieval-Augmented Generation in Practice walks through core RAG pipelines and vector database integration.
Model Context Protocol (MCP) demonstrates how to connect AI systems with external APIs and tools.
Multi-Agent Workflows teaches architectures for agent collaboration, role assignment, and communication.
Building Production-Ready Applications covers scaling with serverless infrastructure, reliability, and security.
Real-World Projects put it all together with examples like research copilots, automated workflows, and customer support assistants.
By the end, readers will not only understand the principles of context engineering but also have the practical templates, reusable snippets, and architectural patterns to apply them directly to their own projects.
If you are serious about building AI systems that are reliable, scalable, and trusted in production, The Context Engineering Lab will give you the foundation and the tools to make it happen. Grab your copy today and start building AI that works in the real world.
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