The project's README from github.com/datawhalechina/easy-vibe. As one markdown file: README.md.
Learn AI coding from zero by shipping real products.
从零开始学 AI 编程,把想法真正做成产品。
你好 · Hello · 哈囉 · こんにちは · 안녕하세요 · Hola · Bonjour · Hallo · مرحبا · Xin chào
Our tutorial supports 10 languages. Let's code together!
我们的教程支持 10 种语言,欢迎世界各地的朋友一起 coding!
🚀 Start Exploring · ✨ Interactive Tutorial · 🦞 Learn OpenClaw · 📖 Table of Contents
🚀 开始体验 · ✨ 交互式教程 · 🦞 学习 OpenClaw · 📖 查看目录
A beginner-friendly learning map Clear guidance from zero, so you can stop "learning and forgetting" |
Step-by-step visual tutorials Detailed walkthroughs that feel like learning with a private tutor |
Immersive simulated coding Virtual mouse guidance helps you quickly learn the core IDE workflow |
Visible AI principles Animated explanations make it easy to see how AI generates images |
Learn RAG like a game Interactive components let you click through the full RAG data flow |
Visual terminal concepts Command-line behavior becomes intuitive when the underlying logic is visualized |
Want an expense tracker? Say it.
Need a booking system with WeChat login? Say it.
Want a blog with comments? Say it.
In the AI era, programming starts by describing what you want.
Easy-Vibe teaches you how to turn that into a real product.
llms.txt so OpenClaw, Claude, Cursor, Trae, and other AI agents can quickly understand the repository structure and find the right tutorial content.Best for: Everyone What you will learn: What AI coding actually feels like through a simple, concrete hands-on example What you will get: A clear first impression of vibe coding and how to work with AI by conversation
Best for: Beginners / product managers / founders What you will learn: Learning roadmap, AI IDE tools, idea validation, prototyping, AI capability integration, and full demo iteration What you will get: A demoable AI product prototype you can actually show to users or teammates
Best for: Junior developers / indie hackers / advanced learners What you will learn: Frontend workflows, design-to-code, databases, backend APIs, deployment, billing, and major projects What you will get: The ability to independently ship modern AI-enabled web applications
Best for: Developers interested in AI-native engineering What you will learn: Claude Code, MCP, Skills, Agent Teams, long-running tasks, Spec Coding, and cross-platform app delivery What you will get: A stronger workflow for complex AI-assisted development and automation
Best for: Everyone What you will learn: Computer fundamentals, frontend/backend basics, infrastructure, AI principles, and engineering practices What you will get: A long-term reference knowledge base covering 9 major knowledge areas
| Section | Key Content |
|---|---|
| Learning Map | A guided overview of the full learning journey |
| AI Era: If You Can Speak, You Can Code | Get your first feel for AI coding through examples like Snake |
| Master AI Programming Tools | Learn how AI IDE tools work and build simple local projects with them |
| Find Great Ideas | Learn how to discover and validate product ideas worth building |
| Build Product Prototypes | Move from requirements to single-page and multi-page product prototypes |
| Integrate AI Capabilities | Integrate text, image, and video AI features |
| Complete project practice | Simulate real scenarios, collect user feedback, and iterate on a full project |
| Section | Key Content |
|---|---|
| Product Thinking and Solution Design | Core frameworks for going from zero to one with a product |
| AI Application Scenario Reference (B2B & B2C) | B2B industry and B2C consumer AI application scenarios |
| Section | Key Content |
|---|---|
| Where to find ideas: 3 reference sources that work best for beginners | Build a reliable pipeline for finding concrete product opportunities |
| Double Diamond: first do the right thing, then do it right | Use a structured process to move from scattered inspiration to a workable direction |
| Use Jobs to Be Done to find what users really want done | Analyze user goals through real tasks instead of surface-level feature requests |
| The Mom Test: a user interview method for validating demand | Learn how to ask better questions and avoid false-positive feedback |
| Section | Key Content |
|---|---|
| What to do if you encounter errors | Common vibe coding issues and how to troubleshoot them |
| Comparison of Seven AI Programming Tools | Compare major AI coding platforms through hands-on testing |
| Design Websites with Agents | Learn multi-agent collaboration in practice |
| Section | Key Content |
|---|---|
| Frontend 0: Build Your Own Asset-Production Agent with Lovart | Use Nanobanana and Lovart to batch-generate visual assets and build a drawing agent with intent recognition |
| Frontend 1: Figma & MasterGo Basics | Learn the workflow from design drafts to implementation-ready UI thinking |
| Frontend 2: Build Your First Modern App - UI Design | Learn the UI design foundations behind modern application interfaces |
| Frontend 3: UI Guidelines and Multi-Product Design | Improve consistency and aesthetics across multiple products with shared UI rules |
| Frontend 4: Make Interfaces Beautiful with LLMs and Skills | Use prompts and plugins to make AI generate more polished, distinctive interfaces |
| Frontend 4: Let's Build Hogwarts Portraits | Build an interactive AI-image frontend project from scratch |
| Frontend 6: From Design Prototype to Project Code | Turn design prototypes into frontend code that can really run in the browser |
| [Frontend 7: Upgrade Your UI with Modern Component Libraries](https://datawhalechina.github.io/easy-vibe/en/stage |