Context Engineering: A Definitive Guide

Context engineering is a systematic approach to building AI systems that goes beyond prompt engineering by designing the complete environment in which AI operates. It involves structuring data sources, integrating tools, maintaining memory across interactions, and ensuring AI agents have access to relevant information when needed. The article explains how context engineering differs from prompt engineering and RAG systems, introduces the Model Context Protocol (MCP) as a standardized interface for managing data sources, and demonstrates building context-aware workflows using SingleStore as a long-term memory layer with vector search capabilities.