I spent eleven months building something inside ChatGPT that I didn't know I could lose.

Not a document. A way of working. Specific prompts refined over dozens of iterations. A system for how I structured research, how I framed problems, how I trained the model to respond in ways that were actually useful to me. The kind of thing that takes weeks to develop and becomes invisible once it works — until it doesn't.

In early 2025, a ChatGPT outage erased months of conversation history for thousands of users. Most of it was never recovered. The same year, a federal judge ordered OpenAI to preserve 20 million user conversations for litigation — including ones people had already deleted. Opting out of training did not exempt them.

I call this the evaporated context problem. Every hour you invest making an AI tool actually work for you is stored on infrastructure you don't own, under policies that can change without notice, subject to legal holds you'll never be informed about. The value you built doesn't belong to you. It belongs to whoever controls the server.

That's the distinction I keep returning to when I look at what @OpenGradient Chat is actually built on at chat.opengradient.ai. The architecture that prevents the operator from reading your prompts is the same architecture that changes who controls what gets preserved. When the system is designed so that plaintext never exists outside your device and the enclave, there's nothing for a court order to compel, nothing for a platform policy change to reach, nothing for an outage to wipe in a way that was yours to begin with.

Eleven months of context. The prompts I won't be rebuilding from scratch.

That's what I've started thinking of as the real cost of working on infrastructure that was never yours. Not the privacy risk. The ownership risk.
@OpenGradient $OPG #OPG #opg

Have you ever lost AI work you couldn't recover?