Context Engineering Improves AI Agent Reliability

This article defines context engineering and explains how designers should structure system prompts, memory, tools, retrieval, and conversation history to improve AI agents' consistency and reasoning. It describes best practices—clean context, focused retrieval and reranking, and stable system prompts—and provides step-by-step guidance for planning agents, designing workflows, and balancing automation with control to make agents more reliable and scalable.