AI Tokens Decentralized Platform

Resolve the meaning of token

In an AI project, a token may refer to a piece of model input or output, a service credit, or a transferable digital instrument. Make the meaning explicit wherever you describe usage, pricing, or resource access. A reader should not have to infer the unit from context.

Start with the entitlement. Does a credit authorize a request, reserve capacity, or settle a completed task? Define its limits and the handling of cancellations before adding governance or reward functions.

Connect settlement to accepted work

For a hypothetical compute marketplace, document how a customer’s request becomes an operator’s accepted obligation. State the success condition, who checks it, and how a disagreement is resolved. Keep model-quality evaluation separate from the fact that a payment transaction completed.

ERC-20 provides a common interface for fungible token operations. A service still needs its own rules for capacity, usage, and disputes. An interoperable balance does not independently establish that an AI task can be delivered.

Review the surrounding incentives

Ask whether operators are rewarded for useful completed work or merely reported activity. Test how the measurement could be manipulated in the proposed design. Separate temporary participation rewards from the costs and payments associated with ongoing customer demand.

Avoid descriptions that turn a compute entitlement into an implied promise of investment returns. Keep the workload evaluation and token-design review as distinct documents, and require each to make sense on its own.

Reference pointEthereum: fungible token interface. The checks here are a proposed review framework; verify your own operating environment.