Context engineering vs prompt engineering: the difference

This post clarifies the distinction between prompt engineering and context engineering for AI agents. It argues that prompt engineering, while valuable, is insufficient for production agents due to their multi-step nature and dynamic inputs. Context engineering, encompassing the curation and maintenance of all data within the model's context window (instructions, knowledge, tools), is presented as the more critical discipline. The post identifies stale and fragmented context as infrastructure problems, not prompt issues, and positions Redis Iris as a context engine that addresses these challenges through efficient assembly of retrieval, memory, and caching mechanisms. It emphasizes that context assembly at runtime, rather than design time, is key to agent performance and reliability.