Avoid importing model-layer token pricing to the application layer
Pricing application-layer work in tokens imports the model provider’s cost structure into the customer relationship and anchors product value to a unit whose cost keeps falling. Carrying model-layer pricing logic into the application layer is often a mistake.
When an application prices that work in tokens, it imports the model provider’s cost structure into the relationship with the customer and anchors the product’s value to a unit whose cost keeps falling. Based on our work, it’s often a mistake to carry the model layer’s pricing logic into the application layer.
Package variable work in credits; move toward outcomes customers can recognize and trust
Turn variable work into units customers can understand. Use credits to package those units when flexibility matters. Move toward outcomes as soon as customers can recognize and trust them.
The better path is to price at the highest layer of value you can reliably measure, attribute, and defend. Translate variable work into understandable units. Use credits to package those units when flexibility matters. Move toward outcomes as soon as customers can recognize and trust them.
Tokens tie an application’s price to model consumption; credits can package different units, so what triggers a charge matters. Tugce Erten and Sarah Wang recommend pricing the highest value layer that can be measured, attributed and defended. Mintlify kept credits but moved from token-variable charges to fixed prices for answers and document updates, with specified no-result cases free. These sources do not establish one model for every AI product.