I remember testing different AI tools last year and noticing something strange.
Most people spent a lot of time comparing which model was smarter.
Almost nobody asked whether the output could actually be trusted.
At first, I thought that was normal.
After all, intelligence seemed like the thing that mattered most.
But the more I watch this industry evolve, the more I think we're overlooking something far more valuable.
Verification.
Right now, AI is getting cheaper, faster, and more accessible.
New models appear every month.
Capabilities spread quickly.
What was unique yesterday often becomes standard tomorrow.
That makes me wonder:
If intelligence keeps becoming easier to access, what actually stays scarce?
I keep coming back to trust.
Not trust as a feeling.
Trust as an economic resource.
The ability to verify where intelligence comes from, who produced it, whether it has been altered, and whether the activity around it is genuine.
That's one reason @OpenGradient caught my attention.
Not because of what it claims to build, but because it sits near a problem I think the market is still underestimating.
As AI networks grow, verification may become just as important as intelligence itself.
Of course, there are risks.
Verification systems can be manipulated.
Incentives can attract activity without creating real users.
Retention can weaken once rewards disappear.
So I'm not convinced anyone has solved this yet.
But I keep wondering:
When AI becomes abundant, will value come from creating intelligence or from proving that the intelligence can be trusted?
