3 parts · reading order ↓
Better prompts help, but they're only part of the story. Context engineering is the craft of designing what an AI agent sees, when it sees it, and how that changes across the session. The goal isn't a bigger context window. It's a more effective one.
Context engineering gets more useful when the knowledge it depends on is packaged for reuse. In this post I map the portable core (AGENTS.md and SKILL.md), Copilot-specific concepts like custom instructions, agents and prompt files, and how to decide what knowledge belongs where.
Conversation state and retrieved context lead naturally into memory, but only if we're clear about what memory is for. Rules, skills, and instruction files package what you already know. Memory should capture what the work itself teaches the system, and that means reflection, verification, and forgetting matter just as much as recall.