I Built an AI That Maintains My Obsidian 24/7 (Claude Code + LLM Wiki)

RAG is not enough. LLM Wiki builds a persistent AI knowledge base that reads, organizes, and updates your research 24/7 — automatically. Inspired by Andrej Karpathy's viral tweet, I built an LLM Wiki system using Claude Code + Obsidian that doesn't just retrieve information — it synthesizes, cross-references, and compounds knowledge over time. In this video I break down the full architecture and show you live demos. 🧠 What you'll learn: → Why RAG fails for personal knowledge management (and what to replace it with) → The 3-layer LLM Wiki architecture: Raw Sources, Wiki, and Schema → The 3 operations: Ingest, Query, and Link (maintenance) → Full setup walkthrough inside Claude Code → Live demo: Synthesizing scattered DeepWork notes into a structured wiki → Use case: AI-automated research + content generation from YouTube transcripts → Why this workflow beats NotebookLM for serious knowledge work Whether you're an Obsidian power user, a founder drowning in research, or a content creator building a content engine — this AI knowledge management workflow will change how you work. 📌 Timestamps: 0:00 - What is LLM Wiki? (and why it's a game changer) 1:20 - RAG vs LLM Wiki: The Key Difference 2:45 - The 3-Layer Architecture Explained 4:00 - The 3 Operations: Ingest, Query, Link 4:58 - Setup with Claude Code (step-by-step) 6:25 - Demo: Synthesizing DeepWork Notes 9:18 - Use Case: Research + Content Generation 10:09 - AI Topia Community 13:08 - Where to Get the Full Step-by-Step Guide 🔗 Resources: → YouTube: https://www.youtube.com/@joonahn_ai → Newsletter: https://aitopia.substack.com → Skool Community (full guide inside): https://www.skool.com/ai-topia-5405 → Book an AI Transformation Call: https://calendly.com/joon-getaitopia/30min #LLMWiki #ClaudeCode #ObsidianAI #AIAutomation #PersonalKnowledgeBase #RAG #AIKnowledgeManagement #LLMObsidian #AIProductivity #AndrejKarpathy