How To Build LLM Wiki In Obsidian? A Memory Layer For Any Agentic AI

Walk-through showing how to build an LLM wiki: a three-layer shared memory system (raw sources, structured wiki, and schema) for agentic AI. The video demonstrates ingesting transcripts into Obsidian, setting up Git versioning, defining schema and templates, and automating maintenance with coding agents. It covers repeatable workflows, agent skills, linting, and optional local model integration for private, cost-free operation.

– Three-layer architecture: raw sources captured unchanged, a structured wiki extracting concepts, and a schema that enforces naming, front matter, and agent rules.
– Ingestion demo: shows clipping a transcript into Obsidian, auto-extracting concepts, linking sources, and visualizing growth in the knowledge graph.
– Setup essentials: install Python, Git, Obsidian, and a coding agent; initialize the vault as a Git repo and add schema, templates, and skills.
– Automation & maintenance: agentic skills (ingest, maintain, lint, query) ensure repeatable updates; Git provides checkpoints and optional local models and agentic firewalls protect privacy.

Quotes:

AI is only as good as the information we give it.

A separate brain that AI agents build and maintain automatically.

The LLM wiki, a structured system that you can build once and then use forever.