Obsidian is usually placed in the same category as Notion, Apple Notes, Roam, or any other app where people collect thoughts. That comparison is useful at the interface level, but it hides the more important design choice. Obsidian’s central object is not a workspace hosted inside the product. It is a folder of Markdown files on your own machine. The app sits on top of that folder and gives you ways to inspect, connect, search, visualize, and extend those files. That is a very different architecture from the productivity tools most people are used to. In many modern tools, the database is the source of truth and the interface is the only practical way to reach it. In Obsidian, the file remains the source of truth. A note can be read outside the app. A vault can be backed up like any other folder. Links are written into the text. Metadata can live inside the file. The useful thing is not that Obsidian has a graph view or a plugin marketplace. The useful thing is that it keeps the durable layer simple enough to survive the interface. This also explains why Obsidian becomes more interesting in the AI era. LLMs work best when the material they operate on is explicit, inspectable, and easy to transform. A folder of Markdown notes is a much better substrate for that than an opaque productivity database. A model can summarize notes, extract metadata, suggest links, generate index pages, or turn raw research into a more coherent local wiki. But the human still needs to audit the result, because a knowledge base that looks organized can still be wrong. The point is not to automate thinking. The point is to make the maintenance of knowledge less fragile.