What cross-AI memory actually means.

Every AI assistant available today keeps its own memory, if it keeps one at all — and that memory stays inside that one assistant. Say something useful to one, and it’s genuinely useful only there. Open a different one, a different app, or even just a different device, and you’re starting from close to nothing. The manual fix people reach for first is obvious: keep a document with the important parts, and carry it with you — paste it in, attach it, whatever the assistant of the moment allows. It works, for a while, for anything short-lived.

The document only knows what you remembered to put in it, and only as of the last time you updated it. Something changes — a plan, a number, a decision — and unless you go update every copy, whichever assistant you open next is working from a version that’s quietly gone stale. It won’t tell you it’s stale. It’ll just answer as if it’s still current, because as far as it knows, it is.

Cross-AI memory, properly done, isn’t a bigger memory inside any one assistant, and it isn’t a document you’re responsible for carrying between them either. It’s a project that exists on its own, outside every AI you use — and each assistant you connect to it can read the current state and add to it, in whichever conversation you happen to be having. Which assistant you’re talking to stops being the thing that decides what it knows.

Making the same facts reachable everywhere is the easy half. What actually matters is what happens when something changes — and it will, because the whole reason you’re using more than one AI is that your thinking keeps moving. Before it adds something new, whichever assistant you’re in checks what the project already says. A fact that’s changed updates in place, the old version kept as history. A decision that gets reversed stays visible instead of vanishing, marked reversed, with the reason attached. None of that depends on which specific assistant you’re using in the moment — it’s a property of the project, not a feature of any one AI.

Say you’re weighing a couple of job offers. On your phone, over lunch, using whichever assistant you’ve got open: “save the decision — going with the smaller company, the flexibility matters more than the base salary difference, at least for now.” A few days later, at your desk, after a second conversation with the smaller company changes the picture: “reverse that decision — going with the larger one instead, they matched the flexibility and the difference in comp is too big to leave on the table now.” The first decision doesn’t disappear — it stays exactly where it was, marked reversed, with the reason attached, not quietly deleted the moment you changed your mind. That evening, back on your phone, you ask whichever assistant’s open to check the project before you draft a reply to the smaller company. It reads the larger-company decision as current, not because your phone remembers what you said at your desk, but because you told it exactly where to look.

Open the project on its own and it isn’t a log of which AI said what, when — it’s just the decision, in plain language, with the reasoning behind it. That’s the Simple view. Structured view shows the same project broken into its labeled parts. Neither one cares which assistant you happened to be using when any of it was said.

The longer you do this, the less it’s about any single project and the more it’s about all of them at once — a few hundred conclusions, across everything you’ve ever asked an AI to help you think through. Cross-AI memory that only solves “today, on whichever assistant” isn’t enough by itself. It has to still work when you’re trying to find the one decision you made eight months ago, in some AI you don’t even use anymore, about a job offer you can barely remember the details of. Search across every project you have, and it isn’t hunting through old conversations hoping you’ll recognize a sentence — it’s looking at what you actually kept: the facts, the decisions, the questions, wherever they came from.