Token Economics: Pricing Intelligence as a Service
For two decades software pricing evolved along per-seat and usage-based paths — both assuming people are the final consumers of value. Agents are quietly removing that assumption.
For two decades software pricing evolved along per-seat and usage-based paths — both assuming people are the final consumers of value. Agents are quietly removing that assumption.
For two decades, software pricing evolved along two paths: per-seat, which hangs the price on “the person using it,” and usage-based, which hangs it on “calls or resources consumed.” Both assume one thing — people are the final consumers of value.
Agents are quietly removing that assumption.
When the main consumer of tokens shifts from people to machines, the anchor of pricing must move from “human time” to “value created by machines.”
Picture an accounting Agent that clears ten thousand invoices overnight. Charge per seat and it counts as one user — wildly underpricing the value. Charge per token and you price the cost, not the result. The sensible anchor is what it saves or earns for the customer.
Human markets are capped by population and attention — a day has 24 hours. Machine consumers have no such cap. So the ceiling of the token economy is no longer “how many people,” but how much value the whole economy can create.
Three questions matter more than “price per thousand tokens”: who is the value created for, how is it metered, and how does metering become a settlement both sides accept. That is the infrastructure problem we work on at ZhiyuHui.