đź’¨Building with AI7 min readUpdated: Nov 11, 2026

Smoke Testing and UAT for Your AI-Built App

Smoke testing is a quick check that your app works. Here's how to build a smoke test checklist and have users test your AI-built app (UAT).

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Roman
AboutTheApp

Overview & context

A smoke test is a short check you run after creating a new version to quickly verify that the app works: for example, you start the app, log in and check the basics, such as the database connection. User acceptance testing (UAT), by contrast, verifies in detail that the app does what its users require. An AI-built app needs both, because if your spec isn't thorough enough, the AI can change another feature while editing one. This article shows how to set up both kinds of testing without a test framework and where to keep the checklist and links for your testers.

1. What is smoke testing

Smoke testing is a short set of checks that confirms that a new build works and is worth testing in more detail. The name comes from electronics development: you power the device on, and if no smoke comes out, you move on to real measurements.

A smoke test doesn't cover every feature. It checks only what the app can't be used without, like loading the home page, logging in, saving a record or sending an email. The whole run should take a few minutes at most, but you can often finish it in a few seconds.

2. Smoke testing vs. sanity testing vs. UAT

Smoke testing checks the whole app after a deployment, sanity testing checks one specific fix or change and UAT checks whether the app meets its users' requirements. They differ in who runs them and how long they take.

Smoke testingSanity testingUAT
What it checksThe app works at a basic levelA specific fix or change worksThe app does what users need
WhenAfter every deploymentAfter a bug fixBefore a release or a handover to the client
Who testsYou or an automated scriptYouUsers or the client
How longA few minutesA few minutesHours to days

3. Smoke test checklist

Build your smoke test checklist from the main scenario you've described for the AI. If you wrote the spec with a PRD template, use the Main scenarios and Done when sections. Then run through the list after every change from the AI and after every deployment.

Here's an example for a web app with a login and a database. Adjust it to what matters for your app.

Task listClick to toggle

4. Smoke testing an AI-built app

Run a smoke test on an AI-built app after every larger change, not just before a release. While editing one screen, Lovable, Bolt or Cursor can change a shared component, the database schema or the login flow. The bug then shows up somewhere else in the app.

If a smoke test fails, tell the AI, or go back to the last working version and give the assistant the change again in a smaller scope, pointing out the problem the original solution caused. For that you need your code in Git and changes committed in small steps. You can also use the checklist to have the AI write automated tests from it, for example in Playwright. Even with automated tests, walk through the main scenario by hand now and then, because the AI may ignore situations that would bother you in the app.

5. User acceptance testing: how to let users test your app

User acceptance testing (UAT) is testing where real users or the client confirm that the app does what they need and approve the release. It runs in a test environment such as staging, not in production with real data.

  1. 1

    Set up a test environment

    Deploy the version you want to verify to a dedicated environment. Switch payments to test mode and send emails only to test addresses or a dummy mailbox.

  2. 2

    Create test accounts

    Prepare test accounts for testers with the roles they'll have in the live app. Test data should resemble production in volume, and you can anonymize sensitive data.

  3. 3

    Write UAT test scenarios

    Tell testers what to go through. Don't describe click-by-click steps; give real scenarios, for example “book a meeting room for next Tuesday, then cancel the booking”. If something changed in the new version, let them know.

  4. 4

    Agree on how to report bugs

    Pick one place for bug reports, such as a form or a task or bug tracker. For each bug, the tester should write the app version and the steps that led to it, and attach a screenshot or a short video.

  5. 5

    Record the UAT sign-off

    When testing is done, write down which version users approved and which bugs need fixing before the release. Then deploy the approved version to production unchanged.

Frequently asked questions

What is smoke testing?

Smoke testing is a short set of checks run after a deployment to confirm the app works: it starts, you can log in and the main scenario runs to the end. Only then does more detailed testing make sense.

What's the difference between smoke testing and sanity testing?

Smoke testing checks the basic functions of the whole app after a deployment. Sanity testing checks one specific fix or change and that it didn't break anything right next to it.

What is UAT testing?

UAT (user acceptance testing) is testing where real users or the client confirm the app meets their requirements and approve it for release. It runs in a test environment, not in production.

Who performs user acceptance testing?

Future users of the app or the client's representatives, not the developer or a tester.

How often should I smoke test an AI-built app?

After every larger change the AI makes and after every deployment. The AI can change another part of the app while editing one feature. A smoke test catches that within minutes.

Can smoke testing be automated?

Yes. You can give your checklist to an AI assistant and have it write automated tests, for example in Playwright, that run after every deployment. It's still worth checking some steps by hand.

Where should I keep the test checklist and links for testers?

In AboutTheApp you add them to the app as links under Monitoring & Quality and Issue Tracking and mark the internal ones as private. Testers then get one About page link with the environment, version and list of changes.

In short

A smoke test after every AI change catches a broken app within seconds, and UAT before a release confirms the app does what users need.

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