technology & computing

AI API launch checklist: eight checks before production

A practical launch checklist from the HiAPI team for developers integrating image, video or text generation. Use each item as a release gate and keep evidence that it works in your application. These checks apply across providers; consult the specific model documentation before choosing parameters or retry behavior. HiAPI: https://www.hiapi.ai/en/

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1

Validate model inputs: test one minimal documented request and reject missing or unsupported fields before sending it.

2

Keep credentials server-side: confirm browser code, error messages and logs contain no API keys.

3

Set limits before launch: cap spend, concurrency and request size; show users when a limit is reached.

4

Persist job state: save an internal job ID and provider task ID so a generation can survive a closed browser tab.

5

Treat timeouts as uncertain: check the existing task before retrying; use idempotency only where documented.

6

Handle callbacks carefully: verify the documented signature, deduplicate events and test delayed or repeated delivery.

7

Verify the output: check that the returned asset is accessible and store it according to the provider retention policy.

8

Test recovery end to end: simulate network loss, rate limits and failed jobs; confirm users see accurate status and next steps.