Knowledge Management

You already have the research repo. Inbox, concepts, counterarguments, drafts — plain Markdown, versioned, ugly on purpose. Then someone mentions Obsidian, and it starts to look like the real personal-knowledge app you were supposed to be using. It is not. The repository is the system. Obsidian is one optional way to look at it. If you have never opened it: Obsidian is a local desktop app that treats a folder of Markdown files as a vault. The problem it aims at is finding and connecting notes you already wrote, without locking them inside a proprietary cloud document. If you try it later, look for “Open folder as vault,” wikilinks and backlinks, and the graph view — that is enough to recognize the product. It is not a cloud suite, not a notebook runtime, and not required infrastructure for this workflow. ...

I was deep in a research thread that was not going to become a weekend post. The topic started small: juniors asking an AI to format code that Prettier already owns, or to invent a debounce helper the repo already has. It got larger fast. Sometimes the person is not a developer at all — they have an idea, they paste a warning into ChatGPT, the “build” goes green, and they never learn that the message was ESLint. The software can become more sophisticated than the operator’s mental model. That is a different problem than “juniors are lazy,” and it is too big to finish in one sitting. ...

We’ve all used ChatGPT to write a function or debug a regex. But that’s just the tip of the iceberg. The real power of Large Language Models (LLMs) isn’t in the “chat”; it’s in the integration. As I explored in my 2025 series on Jupyter and AI, the real value of these tools comes when they are part of a structured thinking process. By combining the interactive execution of Jupyter Notebooks with the reasoning power of Local LLMs, we can build something much more powerful: a Personal Knowledge Engine. ...