Most people watching AI still think the model is the product.
What I keep noticing inside OpenLedger is that the real leverage sits lower. The contributor layer decides which human signals get validated, attributed, and routed into training demand.
The loop is simple but brutal: submit data, pass validation, earn allocation. But once rewards appear, low-quality farms start imitating useful contributors faster than most people expect.
That changes the economics completely. Real operators optimize reputation and consistency. Sybils optimize extraction speed before reward weights adjust.
The interesting part is that models can be replaced. Coordinated attribution history cannot.
Five years from now, the most valuable AI infrastructure may not be the model itself but the system quietly organizing who contributed intelligence in the first place.
