The article discusses the evolution from prompt engineering to context engineering in AI, defining context engineering as a systematic approach to optimizing the information provided to Large Language Models (LLMs). It emphasizes the importance of constructing a comprehensive context for effective AI performance, contrasting single-turn prompts with multi-layered context strategies to enable robust applications across diverse sectors.
