Context Engineering is the practice of providing minimal, focused context to AI agents at each step of their execution. The article breaks down six types of context that need management: system prompts, user prompts, retrieved context, short-term memory, long-term memory, tools, and structured output. Each type presents unique challenges like context poisoning, token limits, relevance filtering, and format reliability. The practice evolved from prompt engineering to address complex multi-turn interactions and tool usage in production AI systems.
Sort: