Make Memory work for you.

As conversational AIs get more capable, our expectations grow with them. We don’t just want faster answers, we want tools that remember, adapt, and fit the way we work. That’s where Memories (beta) come in. And with it, new questions: What should an AI remember? How should it recall? And what does it take for you to trust it?

When we talked to users across personal and professional settings, three consistent needs stood out: transparency, control, and focus. People want the ability to ask, “What do you know about me?” and get a clear answer. They also want memory to stay on-task. As one Le Chat user put it: “I need a hammer, not a friend.”

For some, that means citations: show me exactly which conversation or file a response is pulling from. For others, it means scoped recall, project-specific details, not casual asides from months ago. Whatever the preference, one thing is clear: memory should stay visible, editable, and under your control.

Under the hood, we’ve built a graph-based architecture that balances performance with context-awareness, so memory doesn’t just get longer, it gets smarter. AI is still early. Models will change, and fast. Memories are what keep your assistant anchored in your context, even as everything else shifts. Not a feature. Not a friend. A system you can trust and one that grows with you.

Many AI tools today store information automatically. Some resurface it without warning; others only recall when you explicitly ask.

Le Chat takes a hybrid approach. It saves useful information automatically, like jotting down a note while you talk. But recall is designed to be smart, timely, and visible. You’ll always see what memory is in play, with links to the source.

That design comes from a simple philosophy: An AI assistant should help you think better, not guess what it’s doing. Here’s how we put that into practice.