A few resources on harness engineering I’m really enjoying learning from recently: * https://walkinglabs.github.io/learn-harness-engineering/en/… - excellent course that covers how to constrain agent behavior in a productive way, what the challenges are using LLMs especially maintaining context, and how to make the harness more agentic and work to the proper conclusion of a task * https://twotimespi.dev - build a simplified agent in Python (Tau). start with “uv tool install tau-ai” * https://humanlayer.dev/blog/skill-issue-harness-engineering-for-coding-agents… - lessons and learnings from failing and succeeding to build harnesses for coding agents over 12+ months * https://langchain.com/blog/the-anatomy-of-an-agent-harness… - higher-level overview of the many components that need to come together properly in a harness to make an agent work

Welcome to Learn Harness Engineering

Source: https://walkinglabs.github.io/learn-harness-engineering/en/ Learn Harness Engineering is a course dedicated to the engineering of AI coding agents. We have deeply studied and synthesized the most advanced Harness Engineering theories and practices in the industry. Our core references include:

• OpenAI: Harness engineering: leveraging Codex in an agent-first world
• Anthropic: Effective harnesses for long-running agents
• Anthropic: Harness design for long-running application development
• Awesome Harness Engineering

Through systematic environment design, state management, verification, and control systems, this course teaches you how to make agentic coding tools like Codex and Claude Code truly reliable. It helps you build features, fix bugs, and automate development tasks by constraining your AI coding assistant with explicit rules and boundaries.

Get started​

Choose your learning path to get started. The course is divided into theoretical lectures, hands-on projects, and a copy-ready resource library.

The Core Mechanism of a Harness​

A harness doesn’t “make the model smarter”; rather, it establishes a closed-loopworking systemfor the model. You can understand its core workflow through this simple diagram:

What you will learn​

Here are some of the key concepts you will master:

• Constrain agent behaviorwith explicit rules and boundaries.
• Maintain contextacross long-running, multi-session tasks.
• Stop agentsfrom declaring victory too early.
• Verify workusing full-pipeline tests and self-reflection.
• Make runtime observableand debuggable.

Next steps​

Once you understand the core concepts, these guides help you go deeper:

• Lecture 01: Why Capable Agents Still Fail: Start with the theory behind harness engineering.
• Project 01: Baseline vs Minimal Harness: Walk through your first real task.
• Templates: Grab the minimal harness pack (AGENTS.md, feature_list.json, claude-progress.md) for your own projects.