#opg $OPG @OpenGradient

I opened a small $OPG position this week for a reason that has nothing to do with who has the smartest AI.

Everyone is obsessed with making models more powerful.

I'm becoming more interested in a different question:

How do we know an AI output can be trusted?

As AI starts handling capital allocation, automation, research, and critical decisions, raw intelligence becomes only part of the equation. The real challenge is accountability.

OpenGradient caught my attention because it's focused on something most people overlook: verification at the inference layer.

Think about it this way:

The more capable AI becomes, the less we're willing to accept "trust us" as an answer.

A model can be brilliant, but if nobody can independently verify how an output was produced, trust becomes the bottleneck.

Blockchain spent years solving this problem for transactions.

AI may eventually need a similar layer for intelligence.

I thought about adding more to my position last week, but I held off. There are still big questions around whether decentralized verification can scale efficiently enough to support real-world AI demand.

Even so, I can't shake the feeling that the biggest AI opportunity may not be creating smarter models.

It may be building the trust infrastructure that makes powerful AI usable at scale.

That's the part of the AI stack I'm watching most closely.