If all AIs can be replaced at any time, is the model itself still valuable?

What is truly scarce is no longer the model but the scheduling rights. @dgrid_ai breaks this down very clearly.
It’s not about building more powerful models but about making models interchangeable execution units, with a unified interface connecting to different models for supply.
The system automatically matches the optimal path based on the task—considering price, performance, and latency—all factored into the calculation. This essentially pushes AI toward commoditization.
Whoever is cheaper, faster, and more stable gets called upon. The supply side begins to compete, and the demand side gains freedom.
Looking at the verification layer, DGrid uses PoQ to confirm inference quality. The result isn’t trust-based but verified.
This step transforms AI from a probabilistic tool into a settled asset.
$DGAI ’s role here is to turn all calls into value streams—each request redistributes the revenue.
It’s not about who has the model wins, but who controls the scheduling and defines the market.
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