An OpenAI internal team spent 5 months with 3 people and 0 lines of hand-written code, delivering a complete product using Codex. This article distills their core lessons on AGENTS.md design, repo-local knowledge bases, architecture enforcement, and entropy management.
Claude Code only reads CLAUDE.md; Codex only reads AGENTS.md. Teams using both end up maintaining two identical files. Fix: make CLAUDE.md a symlink pointing to AGENTS.md — one source of truth.
Skill paths are almost always runtime-specific. AGENTS.md is the reliable way to share rules across agents. Put personal reusable capabilities in each agent's supported global directory; put project workflows inside the repo.
Every OpenClaw agent has its own 'home' (Workspace), with personality and behavior defined by bootstrap files like AGENTS.md and SOUL.md. The System Prompt is dynamically assembled each time.
Standing Orders grant an agent permanent authorization to execute defined programs — with explicit scope, triggers, approval gates, and escalation rules, paired with Cron for time-based control.
Hooks are automated safety nets (blocking bad commits), Skills are interactive workflows (running checks + auto-fixing), and instruction files (CLAUDE.md / AGENTS.md) are behavioral guidelines. Each layer operates independently, but together they enable an AI agent to automatically run lint, typecheck, and build checks before every commit.