How to Test an AI-Generated Mobile App Before Launch
Use a practical testing strategy for vibe-coded apps, from unit checks and device testing to release candidates and real-user feedback.
Test the core journey first
Write one end-to-end scenario for the first release. Start with a clean install, create an account, complete the primary action, close the app, reopen it, and confirm the result is still available. This catches more launch-blocking issues than a large collection of shallow screenshots.
Use four layers of testing
- Unit tests: validation, formatting, calculations, and business rules
- Component tests: loading, empty, success, and error states
- Integration tests: authentication, API, database, and navigation boundaries
- Device tests: keyboard, permissions, network changes, deep links, and performance
Ask your AI agent to add the smallest useful test at the same time as the feature. Tests written after a large generated change are harder to align with the intended behavior.
Try the bad paths on purpose
Turn off the network. Submit a form twice. Use an expired session. Enter long text. Deny a permission. Rotate the device. Delete the last item. These cases reveal whether the app helps users recover or simply leaves them stuck.
Create a release candidate
Build a production-like version with real configuration and test data. Install it on at least one iPhone and one Android device if you support both. Do not assume simulator behavior represents a slow, older phone.
Ask for a test report
Codex or another agent can summarize changed files, test commands, uncovered risks, and manual checks still needed. Keep that report with the release notes so future sessions know what was verified.