marcos-wu/ai-agent-daily-mentor — explained in plain English
Analysis updated 2026-05-18
Follow a daily eight-week curriculum with an AI assistant covering Python, APIs, retrieval, and agents.
Build a final project called AI-Interview that parses resumes and runs simulated job interviews.
Get the plan automatically adjusted harder or easier based on daily progress feedback.
Practice packaging a project with Docker and preparing to discuss it in a real interview.
| marcos-wu/ai-agent-daily-mentor | able-rip/cc-visionrouter | adityasharmadotai-hash/docs-reader-rag-agent | |
|---|---|---|---|
| Stars | 29 | 29 | 29 |
| Language | — | JavaScript | Python |
| Setup difficulty | easy | easy | easy |
| Complexity | 2/5 | 2/5 | 2/5 |
| Audience | general | developer | vibe coder |
Figures from each repo's GitHub metadata at analysis time.
Written entirely in Chinese, requires loading the skill file into a compatible AI assistant.
This repository contains a structured learning plan, written entirely in Chinese, designed to take someone from little programming background to a portfolio project suitable for applying to an AI application development internship in eight weeks. It works as a "skill" file that an AI agent can read and follow, meaning the user loads the included file into a compatible AI assistant and then interacts with that assistant daily to receive lesson content, coding exercises, and feedback. The eight-week plan is split into four phases. The first two weeks cover Python fundamentals and building a basic web service backend. Weeks three through five move into working with AI language model APIs, building a retrieval system (which allows software to search a database of text using meaning rather than exact keywords), and combining these into a practical module. Weeks six and seven focus on building agents that can plan and execute multi-step tasks. The final week covers making the project presentable: packaging it with Docker, writing a clear README, and preparing to discuss it in a job interview. The final project that all this work builds toward is called AI-Interview: a simulated job interview system where a candidate uploads their resume, the system parses it, matches them to job descriptions, retrieves relevant interview questions from a database using the retrieval technique, conducts a simulated interview, and generates a scored report at the end. The plan adapts based on daily feedback. If the learner finishes ahead of schedule, the material gets harder. If they get stuck for two consecutive days, the remaining tasks are reorganized and the goal is scaled back to something achievable. Each day's content follows a fixed five-part structure: a core concept explanation, a six-hour schedule broken into morning, afternoon, and evening segments, a working code example, three self-check questions, and a feedback template for the next session. The repository is aimed at Chinese-speaking students looking to break into AI development roles. The license is MIT.
An eight-week Chinese-language AI learning plan, delivered as a file an AI assistant follows, that guides beginners to a portfolio-ready AI interview simulator project.
Use freely for any purpose, including commercial use, as long as you keep the copyright notice.
Setup difficulty is rated easy, with roughly 30min to a first successful run.
Mainly general.
This repo across BitVibe Labs
Verify against the repo before relying on details.