Design around async generation
AI video generation should be treated as a long-running workflow, not a synchronous API call. Your application should create a task, store the returned identifier, and let a queue or scheduled worker handle status checks.
Persist every task
Store the prompt, model, status, user ID, task ID, and any provider response. This gives support teams enough context to debug failures and lets users refresh a page without losing progress.
Handle retries carefully
- Retry network failures with exponential backoff.
- Do not retry a successful task creation without checking whether the first task ID was saved.
- Separate provider errors from user input validation errors.
Expose clear states
Users should see whether a video is queued, generating, complete, or failed. Reliable status labels make the product feel stable even when generation takes time.