@slashui: I really wish I’d seen this tutorial a year ago. If you’ve ever had an AI coding agent confidently break your codebase, completely forget everything from before when you switch sessions, or tell you "done" without having tested anything… then this project is for you. Learn Harness Engine…
Summary
Introducing the open-source course project Learn Harness Engineering (21K+ ⭐), which teaches you how to build engineering environments that enable AI coding agents to run reliably through 14 lessons and 8 hands-on projects, with Chinese language support.
View Cached Full Text
Cached at: 10/29/26, 11:56 AM
I wish I’d seen this tutorial a year ago. 😭
If you’ve ever had an AI coding agent confidently break your codebase, forget everything from before as soon as you start a new session, or tell you “Done” when it hasn’t even tested anything… then this project is for you.
Learn Harness Engineering: a complete, free, open-source course (21K+ ⭐) that teaches you to build an engineering environment that makes AI agents truly reliable.
14 lessons, 8 hands-on projects, and 8 progressive learning stages.
It doesn’t just have you read about concepts—it walks you through building a harness step by step, from start to finish, around a single real-world application. 🔥
And it supports Chinese, so you don’t have to struggle through translating it yourself.
You’ll learn: → Writing agent instructions + planning repository structure → Context management and persistent memory → Cross-session continuity and task handoffs → Task planning, scope control, and progress tracking → Testing, verification, and observability → Automated coding loops + maker-checker workflows → Graph orchestration, parallel execution, and rollbacks
Also included: reusable templates, a harness-creator skill, and technical breakdowns of how Claude Code, Codex, Pi, and DeepSeek build their respective harnesses. 🤯
Prompts can get you a demo; harness engineering gets you an agent you can truly trust.
Similar Articles
@FakeMaidenMaker: A GitHub open source course called "Learn Harness Engineering" recently made it to the front page of Hacker News (155 points, 5.1k stars). The topic is reliability engineering for AI coding agents—that is, OpenA…
Learn Harness Engineering is an open source course that systematically organizes the concept of AI coding agent reliability engineering (Harness Engineering) proposed by OpenAI and Anthropic. It includes 12 lectures and 6 projects, aiming to help developers build reliable AI agent environments.
@cevenif: Using Claude Code or Codex for development, but feel like AI is running wild? This course might be the missing piece you need. There's an open-source course on GitHub called Learn Harness Engineering, which teaches you to establish a controllable workflow framework for AI coding assistants, centered around five core mechanisms...
GitHub open-source course Learn Harness Engineering teaches you to build a controllable workflow framework for AI coding assistants (e.g., Claude Code, Codex). It includes 12 theory lessons and 6 hands-on projects, covering core mechanisms: instruction, state, validation, scope, and session.
@astaxie: Today the group discussed how to learn Harness. For Harness Engineering, I'm studying these two resources: 1. https://github.com/walkinglabs/learn-harness-engineering… to understand the core mechanisms of each Harness…
A project-based course repository on Harness Engineering for AI coding agents, covering environment setup, state management, verification, and control mechanisms to make AI coding agents work reliably. The course synthesizes best practices from OpenAI and Anthropic on building effective harnesses for long-running agents.
@Xudong07452910: Want to train your own Agent that truly knows how to use tools, but don’t know where to start? I think this set of tutorials recently put together by Hugging Face is just what many people need. It’s called “A curriculum for post-training agents,” and uses Coding Ag…
The tweet shared Hugging Face’s tutorial “A curriculum for post-training agents,” which centers on coding agents and covers SFT, distillation, GRPO, OpenEnv multi-turn interactions, and training with a real harness, using experiments to clearly demonstrate the risks of reward hacking.
@IndieDevHailey: This might be the hardest-core open-source AI engineering course on the internet. The GitHub trending project: ai-engineering-from-scratch has already gained 17.4k+ Stars. It's not another AI tutorial that teaches you how to call APIs; instead, it truly guides you to build AI systems from scratch.
Introduces the trending open-source AI engineering course project ai-engineering-from-scratch on GitHub, which has earned 17.4k+ Stars. It offers 435 lessons across 20 stages, covering mathematical principles to hand-built AI systems, supports multiple languages, and aims to help learners deeply understand the underlying principles of AI.