#opg $OPG @OpenGradient
I think one of the easiest mistakes in AI infrastructure is treating every proof as if it proves the same thing.

With OpenGradient, the current trust model is good at proving the path a request took. The prompt can be hashed. The response can be signed. The gateway can show it ran inside an approved environment. That is useful because it makes fake receipts, altered outputs, and unverifiable settlement much harder.

But I keep coming back to a different question: did the exact model people expected actually produce the answer?

That is a much harder thing to prove. A trusted route tells us the request moved through the right system. It does not always tell us the full story behind the model, the weights, the version, or any extra tools used along the way.

For me, this is where verifiable AI gets interesting. TEEs may be the practical bridge today, while cryptographic proofs keep pushing the standard higher.

The next layer of trust won’t just prove that an answer arrived safely. It will prove what truly generated it.