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Friday, May 30, 2025

Memory Is the Real Moat—But It Should Belong to Us


Memory Is the Real Moat—But It Should Belong to Us

In the AI age, the most valuable resource isn’t data—it’s your memory. Not biological memory, of course, but the contextual breadcrumbs you've left behind across a growing constellation of LLM-powered apps. Every prompt, every reply, every fine-tuning of tone, style, and preference—this is the memory that makes an AI assistant yours. And this is becoming the most powerful moat large AI platforms have.

But herein lies the dilemma: this memory is locked inside walled gardens. ChatGPT knows your writing style. Claude remembers your schedule. Perplexity learns your research interests. But none of them talk to each other. And none of them give you full control.

A Moat for Them, a Trap for Us?

From a platform perspective, memory is a dream. It deepens engagement, raises switching costs, and feeds into a virtuous loop: the more you use the app, the better it gets, the harder it becomes to leave. But for users—especially professionals relying on AI across tasks, tools, and devices—this creates real friction.

Imagine writing part of a novel in ChatGPT, managing your tasks with an AI assistant, and analyzing documents with a third app. Each has a different slice of your memory, with no unified context. You end up re-teaching, re-uploading, and re-reminding each app what the others already know. It’s like having a dozen brilliant interns who don’t speak to each other.

The Case for Memory Portability

This is why the idea of “Plaid for memory” is so compelling. In fintech, Plaid unlocked financial data portability, enabling users to control how and where their information is used. Why can’t we do the same with AI memory?

Imagine a permissioned memory layer that sits above the AI apps—a personal data vault you control. Apps would need your consent to read from or write to your memory. You could revoke access anytime. Want to switch from ChatGPT to Claude? Your memory comes with you. Want your task app to learn from your writing habits? Grant it access. Want to share your professional context with a new assistant agent? One click.

This idea turns memory from a moat into a market. And in doing so, empowers users rather than platforms.

What Would It Take?

  • Standards for contextual data: Just like there are APIs for calendars or contacts, we’ll need standards for memory—conversations, task histories, preferences, tone, etc.

  • Encryption and privacy controls: Memory portability must be secure by default. Encryption, consent logs, and clear revocation mechanisms are a must.

  • An open protocol or foundation: Ideally, this layer should be governed by a nonprofit or consortium—not a single company—so it doesn’t become just another silo.

  • Developer incentives: AI startups should be incentivized to support memory portability. This could become a competitive differentiator.

Why This Matters

As AI becomes more ambient—woven into every device, browser, and workflow—fragmented memory will become unbearable. Users will demand interoperability. And the companies that embrace memory portability may not just win trust—they may unlock a new layer of innovation.

Today, we’re still in the early “memory hoarding” phase of LLM platforms. But history favors openness. The companies that gave users ownership—over code, identity, or data—sparked ecosystems, not silos.

Whoever builds the “Plaid for memory” will unlock a better AI future. One where the most valuable thing—the story of you—is finally yours to own.


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