RAG Learning Academy Built Inside Claude Code with 20 Specialist Agents

Interactive RAG Learning Environment

A developer built a complete RAG learning academy inside Claude Code to address shortcomings in existing tutorials. The project aims to provide a more intuitive, current, and detailed learning experience for developers with software experience.

Key Features

• Knowledge assessment: Run /start to determine whether you should be on beginner, intermediate, or advanced tracks
• Interactive learning: Ask questions along the way, digress if needed, with Claude keeping you on track and logging progress
• 20 specialist agents: Experts jump in when you go deep on specific topics like chunking strategy or reranking
• Open-source tools by default: No API keys required - uses local embeddings (all-MiniLM-L6-v2), ChromaDB, and Claude Code as the LLM
• Swappable components: Can swap in OpenAI embeddings or Pinecone instead of defaults
• Content freshness: Monthly CI checks codebase for deprecated patterns, stale model references, and outdated libraries
• On-demand audit: Run /audit-content for freshness check

Structure and Commands

• 17 slash commands available
• 9-module curriculum
• Multi-language support in progress (Python only currently)

Quick Start

git clone https://github.com/TakaGoto/rag-learning-academy.git
cd rag-learning-academy
claude /start

The project is open source and free. It addresses specific issues the creator found with existing RAG tutorials: unintuitive UI, outdated content, reliance on services like AWS Bedrock that hide details, lack of immediate answers to questions, and assumptions of true beginner status.