by walkinglabs
Harness engineering beginner tutorial, from 0 to 1
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# Add to your Claude Code skills
git clone https://github.com/walkinglabs/learn-harness-engineeringGuides for using ai agents skills like learn-harness-engineering.
Last scanned: 5/23/2026
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}🌍 This course is available in 15 languages: English, 简体中文, 繁體中文, 日本語, 한국어, Español, Français, Русский, Deutsch, العربية, Tiếng Việt, Oʻzbekcha, Türkçe, Portuguese (BR), Українська. Choose your language from the badges above.
Frontier Harness Design Breakdowns — new section (4 breakdowns)
| What | Details |
|---|---|
| New section | Frontier Harness Design Breakdowns — Apply the course's five-subsystem framework (instructions, tools, environment, state, feedback) to reverse-engineer how four frontier products build real harnesses. |
| Pi | How Pi builds its harness — a minimal kernel, programmable expansion, and context engineering behind "ask Pi to build what you want." |
| Claude Code | How Claude Code builds its harness — four-layer memory, five-level compaction, hooks, and sub-agent isolation. |
| Codex | How Codex builds its harness — the repository as source of truth, AGENTS.md as a directory page, and worktree isolation. |
| DeepSeek | How DeepSeek builds its harness — "everything is a plugin," capability seams, and an event pipeline. |
| All 15 languages | Full translation coverage across all supported languages. |
Key idea: The course gives you a framework; these breakdowns show you how the same principles actually play out in production harnesses.
Graph Engineering Update — 1 new lecture, 1 new project
| What | Details |
|---|---|
| Lecture 14 | From Single Loops to Graph Engineering — Why a single loop grows into a graph: the four stacked layers (prompt → context → loop → graph) and where harness sits in that stack, the four parts of a graph (nodes, edges, shared state, routing), why in-loop checkpoints can't fix the three structural failures at scale (Goodhart, blindness upward, conflict), a framework-agnostic six-step walkthrough for building your first graph, graph vs. workflow, anchors, which open-source "graph engineering" projects existed before the name vs. after it, the orchestration tax, and when a graph is actually worth drawing. |
| Project 08 | Draw Your Workflow as a Graph — Three progressive experiments: draw your maker-checker loop as an explicit graph, add a parallel fan-out/fan-in node, then add a conditional rollback edge and a human-approval node. |
Key idea: A loop is a graph with one node. When your task needs specialization, parallelism, shared state, verification, and recovery — it has stopped being a loop. It's a graph.
Loop Engineering Update — 1 new lecture, 1 new project
| What | Details |
|---|---|
| Lecture 13 | Why You Need to Stop Prompting Your Agent — From /goal to the six primitives of loop engineering (automations, worktrees, skills, connectors, sub-agents, external state), the generator/evaluator split, four silent costs, and a step-by-step guide to building your first loop. |
| Project 07 | Build Your First Automated Loop — Three progressive experiments: goal loop, timer loop, and maker-checker loop. Compare manual vs. automated, measure intervention reduction, and learn to step outside the loop. |
| Code templates | goal-template.md, loop-state-template.md, maker-prompt.md, checker-prompt.md — drop-in templates for building loops immediately. |
| All 15 languages | Full translation coverage across all supported languages. |
Key idea: Harness engineering builds the vehicle. Loop engineering designs the road it drives on — and you design the road from outside the car.
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:
Quick start? The
skills/harness-creator/skill can help you scaffold a production-grade harness (AGENTS.md, feature lists, init.sh, verification workflows) for your own project in minutes.
A comprehensive course outline and introduction to core philosophies, providing a clear path to get started.

Deep dives into real-world pain points and hands-on projects (like Project 01) for an immersive learning experience.

Templates and reference configurations designed to solve common pitfalls in multi-turn AI agent development, such as context loss and premature task completion.

The repository now includes a PDF build pipeline for the course content.
npm run pdf:build to generate the currently configured PDF coursebooks locally.artifacts/pdfs/.npm run screenshots:readme if you want to refresh the README preview images.release-course-pdfs.yml can build the PDFs and publish them to GitHub Releases.There's a hard truth most people learn the hard way: the strongest model in the world will still fail on real engineering tasks if you don't build a proper environment around it.
You've probably seen this yourself. You give Claude or GPT a task in your repo. It starts well — reads files, writes code, looks productive. Then something goes wrong. It skips a step. It brea
learn-harness-engineering is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by walkinglabs. Harness engineering beginner tutorial, from 0 to 1. It has 13,303 GitHub stars.
learn-harness-engineering returned warnings in SkillsLLM's automated security scan. It has no critical vulnerabilities, but review the flagged issues in the Security Report section before adding it to your workflow.
Clone the repository with "git clone https://github.com/walkinglabs/learn-harness-engineering" and add it to your Claude Code skills directory (see the Installation section above).
learn-harness-engineering is primarily written in TypeScript. It is open-source under walkinglabs on GitHub, so you can review or fork the full source.
Yes. SkillsLLM lists many other AI Agents skills you can browse and compare side by side. Open the AI Agents category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh learn-harness-engineering against similar tools.
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