Lucaswang81/CS146S_CN

动手学CS146S中文版课程，包含assignments，vibe coding工具等，本项目将长期持续维护，致力于打造中文最好的vibe coding教程。

What it solves

This project solves a language barrier for Chinese-speaking learners who want to study Stanford's CS146S course, which covers the fast-moving field of "vibe coding" — building software with the help of coding agents powered by large language models. The original course is taught in English and is not easily accessible to non-English speakers, so this repository provides a complete, translated version of the syllabus, slide decks, assignments, reading materials, and guest lecture transcripts.

The course itself addresses the shift from manual code writing to a collaborative process where developers and AI agents work together. It explains the key technologies and practices for AI-native software development, such as MCP (Model Context Protocol), Agent Skills, spec-driven development, loop engineering, and the concept of a software factory.

How it works

The repository is organized as a static resource hub. It contains the translated course schedule for Fall 2025 (archived) and Fall 2026 (currently tracked), with links to translated slides, assignments, and reading materials. Each weekly topic includes a list of concepts, links to original and translated articles or videos, and the corresponding assignment files in the Assignments/ folder. Slides and other resources are stored in the Resource/ directories.

The project is explicitly non-official and maintained by volunteers. It tracks the official Stanford course website for updates and integrates all new materials as they are released. Users can access the entire course content for free, and the repository encourages contributions via pull requests to keep the translations up to date.

Who it's for

This resource is designed for Chinese-speaking developers, students, or anyone curious about vibe coding and AI-assisted programming. It is especially useful for those who have basic programming experience (equivalent to Stanford's CS111) but may not have strong English proficiency. The course also assumes some familiarity with AI concepts, as recommended by the prerequisite mentioning CS221/229 knowledge.

Highlights

  • Full Chinese translation of the Stanford CS146S course materials, including lecture slide transcripts, assignments, and reading links.
  • Covers the latest topics in AI-native development: MCP, Agent Skills, spec-driven development, loop engineering, and software factory practices.
  • Includes both archived (Fall 2025) and current (Fall 2026) semester content, with references to official course updates.
  • Freely accessible and community-driven; long-term maintenance is promised, with active WeChat group for discussion and support.

Related

  • Project
    BeaconBay/ck

    ck is a Rust‑based CLI/TUI tool that builds local embeddings of source code and lets you search by meaning (semantic search) as well as by traditional regex. It supports incremental indexing, multiple embedding models, AI‑agent integration via an MCP server, and outputs results in JSON/JSONL for automation.

  • Project
    3641397194-wq/gpt6-Astra

    冷咖啡是一款桌面工作台，通过一键修改多款 AI 编码助手（如 Codex、Claude Code、Grok 等）的配置文件，注入预设的提示词和技能库，并支持一键卸载还原，同时内置工具箱和 API 中转功能。

  • Project
    rstudio/reticulate

    A tool that enables seamless interoperability between R and Python by embedding a Python session within R, allowing for shared data, objects, and code execution.

  • Project
    Twigpine/zero

    Zero is a Go‑based terminal AI coding agent that lets you pick any LLM (OpenAI, Anthropic, local Ollama, etc.) to inspect, edit, and run code in your repository. It offers a rich TUI, a scriptable `zero exec` mode, sandboxed permissions, persistent local sessions, and extensibility via plugins and MCP servers. Install via npm, a one‑line script, or by building from source, and keep full control over what files or commands the agent can access.