The Complete Agentic RAG Build: 8 Modules, 2+ Hours, Full Stack

Description

👉 Get access to our complete code files for Modules 3-8 & join hundreds of builders creating production-grade RAG systems in our community https://www.theaiautomators.com/?utm_source=youtube&utm_medium=video&utm_campaign=tutorial&utm_content=claude-code-rag In this comprehensive masterclass, we collaborate with Claude Code to build a full-featured Agentic RAG application from the ground up. No frameworks, no shortcuts — just raw code and real-world implementation patterns. 🔗 Get Started: GitHub Repo (PRD, Prompts & Full Setup): https://github.com/theaiautomators/claude-code-agentic-rag-masterclass Module 1 & 2 Code Files: https://drive.google.com/drive/folders/1jHdWmKSNOXRsA_Ga05stRlDFrA9pGAVw 🎯 What You'll Learn: ✅ Complete Agentic RAG architecture (React + Python + Supabase) ✅ Claude Code development workflow — plan, build, validate, iterate ✅ Document ingestion with DocLing (PDFs, DOCX, PPTX, images) ✅ PG Vector embeddings with hybrid search & re-ranking ✅ Metadata extraction for precision filtering ✅ Text-to-SQL with database-level security ✅ Sub-agents for full document analysis ✅ Local model support (LM Studio, Qwen3) or cloud (OpenAI, OpenRouter) ✅ LangSmith observability for debugging your RAG pipeline ✅ Multi-user authentication with row-level security 🔗 Links: Supabase: https://supabase.com/ DocLing: https://docling.io/ LangSmith: https://smith.langchain.com/ OpenRouter: https://openrouter.ai/ LM Studio: https://lmstudio.ai/ ⏱️ Timestamps: 00:00:00 Intro 00:05:39 High Level Architecture 00:23:10 Module 1 - App Shell 00:51:51 Module 2 - RAG Ingestion 01:11:44 Module 3 & 4 - Records & Metadata 01:20:44 Module 5 & 6 - Docling & Hybrid Search 01:28:26 Module 7 - Additional Tools 01:36:31 Module 8 - RAG Sub-Agent 💬 Questions or Comments? Where do you stand on this — autonomous coding agents vs. actually collaborating and staying in the loop? Let me know below!