I’ve been thinking a lot about where the AI economy is actually heading, and I keep coming back to one question.
What happens when AI becomes so widely integrated that computation itself turns into a global marketplace?
Right now most discussions still revolve around model performance. Faster outputs. Bigger models. Better reasoning.
But I think the next challenge looks very different.
The real bottleneck may become who provides the compute, how that compute gets verified, and how value moves between machines without relying on centralized infrastructure.
That perspective is exactly why @OpenGradient caught my attention recently.
What stands out to me is its approach toward building a decentralized network where AI inference doesn’t simply execute somewhere behind closed systems, but can operate through verifiable infrastructure while enabling programmable payments directly at the protocol layer.
And that feels important.
Because if AI eventually becomes part of everyday digital activity, the systems powering computation may need economic coordination as much as technical performance.
I’m starting to think future AI networks won’t compete only on intelligence.
They may compete on who builds the strongest economic layer underneath intelligence itself.
