~20ms overhead. Built on Cloudflare's edge, so it's fast globally. The value isn't speed—it's that you stop rebuilding context infrastructure and get versioning/debugging for free.
19 karma · joined November 27, 2023
Vector DBs are great for retrieval: "find relevant chunks to add to the prompt." But they're not designed for state management. When you update a message, there's no version history. When something breaks, you can't rewind to see exactly what the agent saw.
UltraContext manages the structured context (conversation history, tool calls, system prompts) with git semantics. Fork, rewind, merge. You can't git revert a vector embedding.
They're complementary. You'd use a vector DB to decide what goes in the context, and UltraContext to manage what's already there.
Quick backstory: every agent project I worked on, I spent more time on context infrastructure than the actual product. Same pattern—duct-tape a store, lose history, debug blind when things broke.
The "aha" was needing git semantics for a project where users wanted to edit messages while still being able to travel back. So that's what I built: immutable history, branch on change, rewind to any commit. But I didn't want to expose that complexity. So the API is just contexts and messages. Versioning happens automatically.
Still early. What context engineering problems are you hitting with your agents?