Episode 429: Getting started with LLM Wikis

by [Scott](/content/author/scottmsclouditpro/ "Posts by Scott"/index.html) | Jun 4, 2026 | Podcast

Welcome to episode 429 of the Microsoft Cloud IT Pro podcast recorded live on 05/29/2026. This is a show about Microsoft three sixty five and Azure from the perspective of IT pros and end users, where we discuss a topic or recent news and how it relates to you. In this episode, Ben and Scott dig into the concept of LLM wikis, specifically building personal knowledge management vault using Obsidian, markdown, and AI tooling like Cloud Code, GitHub Copilot CLI, and Copilot Cowork. Scott walks through how he wired up Obsidian Web Clipper and an RSS dashboard plugin to feed articles into his vault automatically, then had the LLM help build a Python script to automate the ingestion workflow and cut down on token usage.

Then he expands into how Copilot Cowork fits into this workflow as a scheduling harness with practical examples of using it to pull email from an inbox daily, convert messages to markdown, and generate a prioritized to do list. Let's dive into the world of LLM wikis. Scott discusses various models like Type Whisper and how they manage resources efficiently, mentioning the concept of resource contention with local AI applications.

The core idea of LLM wikis involves creating a structured folder of markdown clippings that an LLM can reason over to extract entities, concepts, and sources, building a searchable, graph-linked knowledge base over time. In addition to this, Scott talks about the integration of tools such as RSS feeds with Obsidian and Copilot Cowork, suggesting that it can serve as a personal knowledge management tool to make organizing information easier.

Scott emphasizes the importance of maintaining awareness of organizational data policies when pulling data into markdown files outside of IRM and sensitivity label protections. He shares practical insights on optimizing workflows, like using Python scripts to automate repetitive tasks, and reflects on the benefits of leveraging markdown-based systems for enhanced productivity.

Both hosts acknowledge the high token costs associated with these processes and suggest methods for reducing expenses while maximizing efficiency. They also discuss their personal experiences, elaborating on the importance of structure when managing various data sources and the potential growth of knowledge management practices using these innovative tools.