The more I watch AI systems grow, the more I think the real scarcity won’t be compute.
It will be trusted memory.
Most AI models can absorb massive amounts of information now.
But over time, networks still need to decide what deserves attribution, what deserves preservation, and what keeps economic value inside the system.
That’s why @OpenLedger started making more sense to me recently.
Proof of Attribution, Datanets, and the wider $OPEN design feel less like simple reward mechanics and more like coordination infrastructure for useful intelligence.
If valuable datasets keep getting verified, reused, and connected back to contributors, the network creates repeat behavior instead of temporary speculation.
Of course the challenge is maintaining signal quality as activity scales.
But that’s also where transparent attribution and onchain tracking become an advantage layer instead of just another feature.
Narratives attract attention.
Systems that preserve trusted contribution usually keep the value longer.