Rag Learning Academy

RAG Learning Academy

A structured, multi-agent learning environment for mastering Retrieval-Augmented Generation (RAG) — powered by Claude Code.

Inspired by Claude Code Game Studios, reimagined as an interactive learning guide for RAG systems.

What Is This?

RAG Learning Academy transforms Claude Code into a personal RAG tutor with 20 specialized AI agents, 22 interactive slash commands, and a 9-module curriculum that takes you from "what is RAG?" to production deployment.

Every concept is paired with a hands-on exercise. Every exercise is paired with evaluation metrics. You learn by building.

Quick Start

That's it. No API keys, no pip install, no setup. Dependencies get installed when you need them (the first hands-on lesson will guide you).

What's Inside

20 Specialist Agents

Agents don't auto-route — they answer directly when asked, and Claude will suggest the right specialist when a question goes deep into their domain.

22 Slash Commands

9-Module Curriculum

Each lesson is tagged core or optional. The core path (~8.5 hours) gets you to a working, evaluated RAG system. Optional lessons add depth when you're ready.

Core path: ~8.5 hours | Full curriculum: ~31 hours

8 Milestones + 4 Proficiency Levels

The curriculum is broken into milestones — concrete checkpoints that mark real capability, not just lessons read.

Complete milestones to earn proficiency levels:

See milestones.md for full requirements and bonus milestones.

3 Guided Projects

Progress Dashboard

Run make dashboard to generate an HTML progress page showing your milestones, proficiency level, module completion, and quiz scores.

Tech Stack

No API keys required to start. The defaults work out of the box:

Running models locally? Ollama is free but needs 8-16GB RAM for LLMs. Close heavy apps…