Context Engineering for AI Agents: A Deep Dive

The true power of AI agents lies not in larger models, but in the precise management of their context as a precious and finite resource. Without careful management, an agent's performance degrades due to "context rot," where too much information blurs its reasoning long before its memory limit is reached. The solution is "context engineering," which involves techniques like isolating information for subtasks, summarizing history, and ensuring agents communicate through structured data rather than messy shared transcripts. This entire system, known as the "harness," provides a deterministic shell that helps the agent focus its reasoning on the task instead of getting lost in its own state.