#3232nd of 55 in Learning and cookbooks
agentguide
Chinese-language study guide and interview prep for AI agent engineering roles
- Stars
- 11.1k
- License
- no license
- Last commit
- Sep 2026
- Language
- MDX
Missed the latest GitHub check; these facts may be older.
Overview
A documentation repository (MDX) that organizes AI agent learning into role-based roadmaps for development and algorithm tracks, with tutorials on LangGraph, RAG, context engineering, SFT and RL. It also collects 1500+ interview questions, resume advice and links to external courses and projects. Content is in Chinese and no runnable software is shipped.
Who it is for: Chinese-reading engineers preparing for AI agent, RAG or LLM app job interviews
Strengths
- Separate development and algorithm roadmaps, stated as 8-12 and 10-15 weeks
- Covers agent harness, context engineering, MCP, RAG, eval and agentic RL topics
- Includes an interview question bank (1500+ claimed) and resume guidance
- Links to external resources such as learn-workbuddy and hello-agents instead of duplicating them
Weaknesses
- Written in Chinese; English readers need translation
- No license detected, so reuse terms are unclear
- Much of the README is job-search advice rather than runnable code
- Many topics point to third-party material rather than original content
What it needs
- no GPU
Also in Learning and cookbooks
See all 55| Rank | Project | Score |
|---|---|---|
| 1 | ai-engineering-from-scratchHands-on AI engineering curriculum with 542 lessons across 20 phases | 90 out of 100 |
| 2 | generative-ai-for-beginners21-lesson course on building generative AI apps in Python and TypeScript | 81 out of 100 |
| 3 | ai-agents-for-beginners18-lesson course on building AI agents with Microsoft Agent Framework | 79 out of 100 |
| #4 | cs249r_bookOpen textbook and course materials for machine learning systems engineering | 79 out of 100 |
| #5 | llms-from-scratchCode for the book on building a GPT-style LLM in PyTorch | 77 out of 100 |