Context engineering in AI focuses on providing models with the most relevant, structured information needed to deliver accurate and meaningful outputs. It involves techniques like prompt optimization, retrieval-augmented generation (RAG), dynamic memory management, and context compression to overcome token limitations. By intelligently selecting, assembling, and maintaining contextual data, context engineering enhances AI’s reasoning, personalization, and reliability, making it a critical component of modern AI system design. Read more..
Context Engineering
