While this isn’t hard to understand, in practice it makes costs harder to predict, especially for small teams moving from experiments to early production. This feels less like a technical problem and more like a budgeting and planning problem.
I’m curious about alternative pricing abstractions, for example a subscription with unlimited tokens but a capped number of requests, aimed at making monthly spend easier to reason about while building.
For people running AI in production today, does token based billing give you enough predictability, or would a model like this actually reduce friction? What tradeoffs would matter most to you?
