Knowledge Management

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. ...