context-engineering

# Context Engineering ## Overview Feed agents the right information at the right time. Context is the single biggest lever for agent output quality — too little and the agent hallucinates, too much and it loses focus. Context engineering is the practice of deliberately curating what the agent sees, when it sees it, and how it's structured. ## When to Use - Starting a new coding session - Agent output quality is declining (wrong patterns, hallucinated APIs, ignoring conventions) - Switching between different parts of a codebase - Setting up a new project for AI-assisted development - The agent is not following project conventions ## The Context Hierarchy Structure context from most persistent to most transient: ``` ┌─────────────────────────────────────┐ │ 1. Rules Files (AGENTS.md, etc.) │ ← Always loaded, project-wide ├─────────────────────────────────────┤ │ 2. Spec / Architecture Docs │ ← Loaded per feature/session ├─────────────────────────────────────┤ │ 3. Relevant Source Files │ ← Loaded per task ├─────────────────────────────────────┤ │ 4. Error Output / Test Results │ ← Loaded per iteration ├─────────────────────────────────────┤ │ 5. Conversation History │ ← Accumulates, compacts └─────────────────────────────────────┘ ``` ### Level 1: Rules Files Create a rules file that persists across sessions. This is the highest-leverage context you can provide. **AGENTS.md** (for OpenAI Codex): ```markdown # Project: [Name] ...