Foundations in Harness Engineering

Lessons in this section

1. Coding Agents

   What an AI coding agent is, the read, plan, act, observe loop it runs, how you approve or deny its tool calls, and the two-line rules file that turns a guessing agent into a careful one.

2. Failure Gallery

   The one formula of this course, Agent = Model + Harness. Watch six real ways coding agents fail, tag each one as a guide gap or a sensor gap, and pick the harness part that fixes it for good.

3. Rules Files

   Why the agent only knows what is written in the repo, how one rules line fixes the wrong test command, and why a 600-line AGENTS.md gets half-ignored. You turn it into a short map that points into docs/.

4. Agent Skills

   Why an agent does the same job differently each time, and how a SKILL.md fixes it: a description that says when to load it, and steps that say how. You write a skill that loads on the right requests, stays quiet on decoys, and gets every step done.

5. Tests and Linters

   Why an agent says "done" while a team rule is broken, how a definition of done makes it run the checks first, and how a lint message that names the fix lets the agent repair its own mistake. Includes sensors for testing, UI, planning, APIs and CI.

6. Hooks and Permissions

   Rules are requests; hooks and permissions are walls. You watch an agent in a hurry with and without guards, write a guard config that blocks only the dangerous calls, see the same guards in Claude Code, Cursor and Codex, then check and download your v1 harness.