Part 7 - The Memory Does Not Care Which AI Is on Sale

Pick the best model today and you have picked the wrong model for next quarter. That is not a criticism of anyone's model. It is the pace of the field, and it is the thing every AI workflow quietly pretends is not happening.

My situation was that I used more than one. Claude for some work, ChatGPT for other work, and my own scripts for the boring parts. Each one had its own idea of what my project was, and none of them shared it. Switching models meant starting over. So in practice I did not switch, even when the other model was better, because the re-briefing cost more than the upgrade was worth. The memory had become a lock-in mechanism against my own interests.

The rabbit hole was the memory features the labs ship. Each is good, each is proprietary, and each makes the problem worse by design. A memory that lives inside one model is a reason never to leave that model. That is not a bug from the vendor's point of view.

So the architectural decision was that the memory must not care which AI is on sale this month. Any client that speaks the open tool protocol and holds a workspace key gets the identical tool surface: Claude, ChatGPT, or an agent you wrote yourself. The load path is the same query for every one of them, which is not a policy but a property of how the system was built: the model is never the orchestrator, only a bounded callee, so it cannot be special-cased even if I wanted to. Today the one-click sign-in is Claude-only, the other clients use an API key. The tool surface is the same.

The daily version of that looks like this. You lock a project brief into one immutable preset code: your profile, the working rules, the memory, the mistakes, one file or topic. Paste load preset and that code into any AI session and the whole brief loads in one call, with a live token count on every slot. When the session is done, it can save its conclusions back to the same file or topic, and those atoms flow through the same engine as forwarded email, stamped as AI-session content so they never masquerade as verified facts. Stop in one model. Resume in another. Nothing lost, nothing re-explained.

No credential ever enters the model's context on the way. Tool access is derived from one registry, bound to the session, and never hand-edited.

Here is the bet. The large labs will not build this layer. A memory that works identically across every model commoditizes the model, and no lab can be expected to build the thing that makes its product interchangeable. The layer has to come from outside, from someone with no model to protect. That is the whole reason an independent company is the right shape for this product, and it is the reason I am comfortable being small.

Context Windows Close. AI Forgets Everything. Your Work Should Never Start From Zero.

MrAgentˣ is in private beta. Limited to the first 1,000 until launch.