Welcome to Projects

This is the hands-on section of Learn Harness Engineering. Reading the lectures isn't enough—you need to build the environments yourself and observe how Codex, Claude Code, or other AI agents behave under different rules.

Project Overview

This course features 6 progressive, hands-on projects that teach you how to build a reliable agentic working environment from scratch:

1. Prompt-Only vs. Rules-First: Compare how an agent performs with just a prompt versus a basic harness.
2. Agent-Readable Workspace: Learn how to structure your repository to make it AI-friendly and establish handoff mechanisms.
3. Multi-Session Continuity: Design state files and initialization scripts so your agent can resume work seamlessly across sessions.
4. Runtime Feedback and Scope Control: Introduce tools that allow the agent to test its own code and correct errors during execution.
5. Self-Verification and Role Separation: Build an independent review mechanism to prevent hallucinations and early declarations of victory.
6. Complete Harness (Capstone): Assemble a final, observable, end-to-end agent working environment.

How to Proceed

Each project folder typically contains:

• starter/: Your starting workspace.
• solution/: A reference implementation (if you get stuck).
• Task instructions detailing your background and specific goals.

Use your preferred AI Coding Agent (e.g., Claude Code, Cursor, Trae) to complete the tasks inside the starter/ directory.