What if your AI could say "I'm not sure, but I can guess if you want"?

Most AI memory systems have the same problem: they always answer, even when they have nothing useful to say. Ask about something that was never mentioned and instead of "I don't know," you get a confident wrong answer built from the closest random match in the vector. I've been thinking about this a lot while working on a memory layer for LLM agents. The core issue is that vector similarity search always returns results. There's no "nothing found" state. So the AI treats whatever comes back as real context and builds a confident sounding answer on top of garbage.