Context Engineering

STOP PROMPTING, START ENGINEERING: MASTER THE ART OF CONTEXT TO BUILD PRODUCTION-READY AI.
Are you a developer who has mastered the basics of Large Language Models (LLMs) but is now hitting a wall? Are you frustrated by hallucinations, outdated knowledge, and the inability to connect powerful models like GPT-4 to your private data? It’s time to move beyond simple prompt engineering and learn the architectural patterns that power professional-grade AI applications.
This book is the definitive, hands-on guide to Context Engineering, the critical discipline of building systems that provide LLMs with the right information at the right time. Forget trial-and-error prompting. Learn to build robust, scalable, and factually-grounded applications using the industry-standard Retrieval-Augmented Generation (RAG) architecture. We cut through the hype and provide you with battle-tested techniques, from-scratch code examples, and the strategic mindset needed to build truly intelligent systems.
Inside, you will master the complete development lifecycle:
BUILD A RAG PIPELINE FROM SCRATCH: Go beyond frameworks and learn the fundamental mechanics of loading, chunking, embedding, and retrieving knowledge to eliminate hallucinations and connect your private documents to any LLM.
MASTER ADVANCED RETRIEVAL: Move beyond simple vector search. Implement sophisticated techniques like Hybrid Search and Re-ranking to dramatically improve the accuracy and relevance of your retrieval system.
ARCHITECT AUTONOMOUS AGENTS: Learn the cognitive architecture behind modern AI agents. Implement the ReAct framework and master structured Tool Use to build systems that can reason, plan, and interact with external APIs to solve complex, multi-step problems.
CHOOSE THE RIGHT TOOLS: Get a practical guide to the modern AI toolkit. Understand the trade-offs between leading Vector Databases like Pinecone, Weaviate, and Chroma, and learn when to use orchestration frameworks like LangChain and LlamaIndex.
PRODUCTIONIZE YOUR AI: Learn the essential, non-negotiable skills for deploying real-world applications. Implement robust evaluation pipelines with the RAGAs framework and optimize your system for speed, cost, and reliability.
NAVIGATE THE ETHICAL LANDSCAPE: Understand the critical responsibilities of the modern AI engineer, from mitigating contextual bias in your data to ensuring privacy, security, and transparency in your applications.
This book is for software engineers, AI/ML practitioners, and data scientists who are ready to level up. If you have intermediate Python skills and want to move from building simple AI toys to architecting sophisticated, context-aware systems, this is your guide.
Don’t just prompt the future-build it. SCROLL UP AND GRAB YOUR COPY TODAY TO TRANSFORM YOUR AI PROTOTYPES INTO POWERFUL, RELIABLE, AND PRODUCTION-READY SYSTEMS.