Instructions Are Not a Harness — Harness Engineering in action

There's a moment every developer hits when building with AI agents. The agent does something wrong. You add a rule to the system prompt. The agent does the same thing wrong again. You make the rule more explicit. It still happens. You start wondering if the model is the problem. It isn't. The rule is the problem. Rules describe what you want. They don't prevent what you don't want. And that distinction — between describing desired behavior and making undesired behavior structurally impossible — is the entire discipline of harness engineering. I learned this the hard way building Skilldeck , a desktop app for managing AI agent skill files. I used Claude Code to build it, gave it a CLAUDE.md project bible with explicit rules, and let it run autonomously. It completed Phase 1 in a few sessions: 18 features, all marked passing in the JSON spec, clean-looking git history. I opened the app and clicked New Skill. Nothing happened. Clicked Add Project. Nothing happened. Nine features marked pa