Designing an Honest “Unlimited” Generative AI Product: Credits, Queues, and Fair Use

Building a Generative AI product that offers an "unlimited" experience requires careful consideration of several key design principles. First, access should be separated from execution priority. Access determines whether an account can submit a valid job, while priority determines when the job should run relative to other jobs. Concurrency answers how many jobs an account can run simultaneously, and throughput answers how quickly new jobs can enter the system.

By treating access and priority as distinct concepts, the product can maintain access during heavy load without forcing users into a quota-exhausted error state.

Credits serve as a common accounting unit across various media types, such as image, video, music, and voice generation. The estimated cost of a job can be calculated based on factors like model cost, duration, resolution, and retry risk. When credits are reserved before dispatch, and the provider reports actual usage after completion, the balance is reconciled. If the balance matches the estimate, the job is reserved and enqueued with normal priority. If not, it is enqueued in a lower-priority continuity queue.

Partner inventory varies widely based on factors such as country, device, profile, time of day, and partner demand. Designing the system as if inventory were constant can lead to geographical dead ends. Monitoring key metrics, such as the percentage of eligible sessions with zero activities, median credits earned per user, completion-to-credit success rate, and queue wait times by priority class, is essential. The goal is to detect when the normal path is missing and ensure that a usable fallback remains available.

The continuity queue should be treated as a real product path, not a fake button that never completes. A scheduler can determine the priority score of a job based on factors like job age, expected cost, and account trust. This approach prevents small jobs from waiting indefinitely behind expensive jobs while still allowing older work to advance.

Useful safeguards include limiting the number of active continuity jobs per account, deduplicating identical submissions, cancelling jobs before provider dispatch, using idempotency keys for retries, implementing provider-specific circuit breakers, and providing transparent status messages and estimated wait bands.

Fair use must be behavior-based rather than arbitrary. Controls should respond to actions that threaten other users or the service. Signals can include automated bursts exceeding human interaction patterns, repeated duplicate submissions, multiple accounts sharing one identity, attempts to bypass concurrency controls, and confirmed rights violations.

Starting with reversible actions, such as reducing concurrency, adding cooldowns, requiring re-authentication, or requesting verification, is crucial. Permanent blocks should only be used with strong evidence, and an appeal path should be provided. It's essential to recognize that a genuine power user should be allowed to maintain their unlimited access privileges.

Finally, distinguishing between platform permission for commercial use and input rights for the user's original content is vital. The platform can grant commercial permission for output produced by its current routes, but it cannot create rights for input that the user did not own. The product should clearly distinguish between platform permissions and input rights, ensuring that legal protectability of the output is considered based on the user's specific content.