AI API for UGC Platforms: Stop Generating Content You Can't Safely Publish

AI APIs for user-generated-content platforms should be treated not simply as media-generation tools but as governed workflow systems that manage approved inputs, asynchronous jobs, asset lineage, moderation, publishing permissions, disclosure, and billing for images, video, metadata, and 3D assets. The recommended approach is to define a specific creator job before selecting a model, use traceable stateful jobs with idempotency keys and authenticated webhooks to prevent duplicate spending and lost outputs, and retain records of source rights, prompts, model settings, review decisions, costs, and destinations. The text emphasizes separating input rights, output safety, advertising truthfulness, and AI or paid-content disclosure, particularly to prevent AI avatars from being misrepresented as real customers or testimonials. It proposes reviewing a still image before generating video to control identity drift and cost, measuring cost per approved publishable asset rather than per generation attempt, and beginning with a tightly scoped pilot such as converting approved product photos into creator-style draft images. Success should be evaluated through completion, acceptance, review, repeat-use, publication, and cost metrics, while broader commercial claims require controlled experiments.

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