I built a bot trained on my own X bookmarks and likes. Around 50,000 of them, accumulated over years of lurking, arguing, and clicking the save button on things that made me stop scrolling.
The technical part isn't complicated in principle. You pull your export, embed the text, build a RAG pipeline, add a style prompt derived from your own writing patterns, and you get something that responds to prompts by retrieving your most relevant saved content and riffing from there. I called it Bookmark Brain, which is either clever or embarrassing — I haven't decided.
What I didn't expect was how much it would clarify my thinking about what generative AI actually is.
The bot works too well. That's the problem.
When I ask it about API design opinions or takes on the current AI hype cycle, it returns something that sounds like me — specific, slightly annoyed, grounded in a particular set of concerns — better than most general-purpose LLMs do when I prompt them with "write in my voice." The difference isn't the model. It's the retrieval layer. The model in both cases is doing the same approximate thing. What changes is what it retrieves before it starts generating.
