Test Every Iteration Before Expanding

AI-generated applications should be tested after every meaningful change.

Not eventually. Not before launch. After every iteration.

This is one of the simplest and most important habits in the entire process.

Why Testing Matters So Early

Small issues compound quickly in AI-generated systems.

A feature that looks correct may still have:

• broken buttons

• failed persistence

• missing validation

• layout issues on mobile

• partial edge-case handling

• hidden workflow regressions

If you stack more features on top before testing, you bury the root problem.

What to Test

At a minimum, test:

• all buttons, links, and actions

• all primary workflows

• data save and reload behavior

• mobile and desktop layouts

• basic empty and error states

• any AI-generated output path

Testing Checklist

Functional

Can users complete the intended workflow?

Interaction

Do all controls behave correctly?

Persistence

Does the data remain after refresh or navigation.

Responsiveness

Does the UI hold up across screen sizes?

Error Handling

What happens when something fails?

Permission or Role Behavior

If applicable, do restricted actions stay restricted?

Real-World Example

For ParkEasy, a real-time parking reservation app, a build may appear functional until you test:

• reserve spot

• confirm payment

• refresh app

• return to reservation screen

If the reservation disappears after refresh, the workflow is not done

For SignalHub, testing should include:

• CRM enrichment source availability

• failed enrichment edge cases

• duplicate record handling

• dashboard state after refresh

Callout

If you do not test after each iteration, you are building on assumptions.

Tips and Tricks

• Keep a simple test script for each app

• Test the primary workflow first, then edge cases

• Test on one small screen and one large screen every time

• If data matters, refresh the app before declaring success

• Test before asking for the next feature

Gotchas

• Trusting the preview without actually using it

• Clicking only the happy path

• Skipping mobile

• Forgetting state persistence

• Expanding the app while a known issue still exists

Practical Example

For TaskMate, a stable iteration means:

• create a task

• edit the task

• move the task

• refresh the app

• confirm state persists

• confirm layout still works on mobile

Only then should reminders or AI prioritization be added.

Next Step

Once testing is part of the workflow, the next thing to avoid is the prompt mistakes that waste the most time. That’s next.