When we talk about AI today, the conversation tends to revolve around models — GPT-5 vs. Claude, Gemini vs. Mistral, proprietary vs. open-weights. But the real differentiator for user experience in the coming years isn’t model size, latency, or cost per token. It’s context portability — the ability for your context to follow you across systems, seamlessly. context portability As someone who has led programs focused on long-term and short-term memory for AI systems, I’ve seen firsthand how much friction is created when users have to “retrain” every new assistant on who they are, what they care about, and what they’ve done before. Right now, every LLM acts like an amnesiac genius: brilliant at answering a question, but forgetful about why you asked it. why Why Context Matters Every interaction we have — with humans or machines — is shaped by shared context.If you tell your assistant, “Book the same hotel as last time,” the assistant shouldknow what “last time” means. If you ask it to “reorder my usual groceries,” it shouldn’t require a fresh prompt history. know This is more than convenience; it’s the backbone of trust and efficiency. Context is what transforms an AI from a search engine into a genuine collaborator. The Problem: Context Lock-In The irony is that while AI is getting more open and accessible, our data context is becoming more siloed than ever. data context Each model or platform builds its own flavor of memory — a closed ecosystem that doesn’t interoperate with others.You can’t export your “profile” from one model to another without rebuilding it from scratch. Imagine switching smartphones and having to re-teach your contacts, playlists, and preferences — every time. That’s where we are with AI today. And it’s a massive friction point not just for users, but for enterprises running multi-model strategies. Companies experiment with OpenAI for reasoning, Anthropic for safety, Gemini for native Google integrations — but they can’t share user state or preference data between them. That fragmentation quietly kills productivity. Building the Bridge: Context as an API The long-term fix isn’t more proprietary memory. It’s context portability — a standardized, privacy-aware layer that lets your context travel across models the same way your identity travels across devices. context portability Think of it like OAuth for memory. You, the user, control which context gets shared, where, and for how long. The AI doesn’t own your history; it borrows it temporarily to make you more effective. own From a TPM’s lens, this isn’t a purely technical challenge — it’s a product and trust problem too.You’re balancing three competing priorities: Personalization depth — how much context to carry over,
Privacy and compliance — what not to share,
Interoperability — ensuring context schemas are consistent across ecosystems. Personalization depth — how much context to carry over, Personalization depth Privacy and compliance — what not to share, Privacy and compliance Interoperability — ensuring context schemas are consistent across ecosystems. Interoperability The architecture could involve a Context Profile Service that maintains structured embeddings of your preferences, entities, and goals. Models query this service via a secure token, retrieve what they need, and then drop it after session completion. That decoupling ensures the context belongs to you, not the model. Context Profile Service you The Real Challenge: Standards Before Scale No single company can solve this alone. Context portability will require the same kind of cross-industry collaboration that brought us HTML, USB, or OAuth. Without open standards, we’ll continue to see “AI silos” — each smart in isolation, collectively dumb. As a program leader, I’ve learned that interoperability always feels like overhead in the short term. But it’s the only way to make ecosystems sustainable. Context portability is the next great interoperability frontier for AI. Looking Ahead We’re entering an era where switching models will be as common as switching tabs. Users will expect their preferences, tone, and history to just work, wherever they go. The real competitive edge won’t come from who builds the smartest model — it’ll come from who builds the smartest memory architecture. just work And that means building for portability from day one.

Google

OpenAI

Context Portability: The Next Leap in AI Usability

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