2025emma/vibe-coding-cn — explained in plain English
Analysis updated 2026-05-18
Read the methodology before starting a new AI assisted coding project to avoid a tangled codebase.
Borrow the day to day working principles, like one module at a time and interfaces before implementation.
Use the linked prompt collections and skill libraries directly in an AI coding tool.
Reference the translated versions if you want the guide in a language other than Chinese.
| 2025emma/vibe-coding-cn | letta-ai/letta | emmabostian/developer-portfolios | |
|---|---|---|---|
| Stars | 22,514 | 22,474 | 22,464 |
| Language | Python | Python | Python |
| Setup difficulty | easy | moderate | easy |
| Complexity | 1/5 | 3/5 | 1/5 |
| Audience | developer | developer | developer |
Figures from each repo's GitHub metadata at analysis time.
Vibe Coding is a Chinese language guide about pairing with an AI assistant to turn an idea into working software. It is not a code library you install, it is a collection of writing on how to plan, structure, and manage a project when an AI is doing much of the coding, so that the codebase does not turn into a mess. The core idea repeated throughout is that planning comes first: letting an AI plan on its own without guardrails tends to produce tangled, hard to manage code, so the guide pushes structure before code and clear goals before implementation. The repository includes a set of principles for how to work day to day, such as breaking work into single modules, defining interfaces before writing the implementation, changing one module at a time, and treating documentation as something written alongside the code rather than added afterward. It also describes a more abstract method for building prompts that can improve themselves over repeated cycles, where one prompt generates new prompts or skills and a second prompt refines them, with the results fed back in to keep improving. Beyond the methodology text, the project links out to a curated collection of prompts and skills for AI coding tools, plus a shared spreadsheet of prompts and a separate repository of system prompts used by various AI coding products. The guide has been translated into many languages, including English, Arabic, Hebrew, Japanese, Korean, Russian, and others, each kept in its own folder. There is also a Telegram group linked for discussion. The README shown here is longer than what was included in this summary, and the tail end of the setup and detailed practices was cut off. Given its scope, this project mainly suits people already writing code with AI assistants like Cursor or Claude who want a repeatable process rather than ad hoc prompting, as opposed to complete beginners with no coding background yet.
A widely shared Chinese language guide on how to plan and structure software projects while pair programming with an AI assistant.
Mainly Python. The stack also includes Markdown, Prompt Engineering.
Unknown from the shown README, check the repository license file for exact terms.
Setup difficulty is rated easy, with roughly 5min to a first successful run.
Mainly developer.
This repo across BitVibe Labs
Don't trust strangers blindly. Verify against the repo.