A home for personal context

Every agent I use is building a model of me. Claude has learned how I like my prose. ChatGPT remembers what I’m working on. I don’t mind this, but if I switch products, I have to start over. If I use three agents, each rebuilds from scratch what the others already know. Everything an agent learns lives with its vendor.

It doesn’t need to be this way. What if every person had a canonical, user-controlled repository of context that any agent could request permission to use?

Last month I wrote about what a personal website becomes in the age of AI: canonical, public context for how the network understands you. This is the flip side of that thought. A website is where you teach the world who you are. But the richer context — your preferences, your projects, your history — is private, and right now it has no home of its own. It lives in fragments inside whichever agent you happen to have been using.

Plenty of people have started down this road by pointing agents at a pile of Markdown files; the best-known recent example is probably Karpathy’s LLM Wiki, elegant not just as a design but as a document. I’ve spent the past year working in a similar way, and it taught me five things a personal context system has to get right. It also led me to a bigger question: where should that context live? Not on which disk, but inside which trust boundary?

I’ve written about both in A Home for Personal Context, published on O’Reilly Radar. If we get the pattern right, changing agents won’t mean changing homes.