Review an AI agent’s Android changes as a proposal—not proof of a working feature. Start with the requested behavior, inspect the complete diff, then run tests at the layer that matches the change. Google warns that generated code can be inaccurate and says to carefully test it for errors, bugs, and vulnerabilities before relying on it.
1. Re-establish what the change is supposed to do
Before reading implementation details, restate the request as observable behavior. Compare the prompt and acceptance criteria with the files and Android components the agent changed. Ask which user-visible states should change, which should remain unchanged, and what happens at boundaries or when an operation fails.
- Check loading, success, error, and empty states where relevant.
- Identify affected lifecycle events, permissions, data flows, and supported Android APIs.
- Compare the implementation with the project’s existing architecture and conventions.
Specific instructions, relevant project context, and smaller reviewable tasks make it easier to judge whether an implementation matches its intent. See Google’s Android Studio prompting guidance.
2. Review the diff before accepting it
Read every changed file, including build scripts and dependency changes, rather than relying on the agent’s summary. Android Studio Agent Mode asks developers to review and approve its proposed changes; that review is part of the workflow, not an optional formality.
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- Look for incorrect API or lifecycle assumptions, missing error handling, and changes that exceed the request.
- Check permission requests and how personal or sensitive data is accessed, stored, or transmitted.
- Verify that new dependencies and configuration changes are necessary and compatible with the project.
- Inspect generated tests separately: confirm their assertions would fail if the behavior were wrong and cover meaningful edge cases.
Agent Mode can help build and inspect an app on a connected device, including viewing screens, taking screenshots, checking Logcat, and interacting with the running app. These observations help surface problems, but they do not establish that the requested behavior is correct. See Android Studio Agent Mode documentation.
3. Choose tests that match the change
The key distinction is whether the behavior can be tested in isolation or depends on Android itself, integration, or real user interaction.
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| Test approach | Best fit | What it does not establish by itself |
|---|---|---|
| Local JVM tests | Isolated logic that has no Android framework dependency, or code that can use suitable test doubles. | Behavior that depends on Android APIs, device integration, or actual UI interaction. |
| Instrumented tests on an emulator or device | Android-dependent behavior, integration, and functional UI behavior that test doubles cannot represent adequately. | Coverage of every device, OS version, or build variant unless those are included in the test matrix. |
| Compose UI tests | Testing Compose interfaces with Compose’s dedicated test APIs. | Cross-app behavior outside the Compose UI under test. |
| UI Automator | Automating interactions that cross app boundaries. | Correctness of unasserted behavior or scenarios the test does not exercise. |
Android’s testing fundamentals and instrumented testing guidance explain the different roles of local and device-based tests. Choose the narrowest layer that can credibly verify the behavior, then add integration or UI coverage where the change crosses those boundaries.
4. Run tests for the affected module and variant
Use Android Studio’s test runner and result views for an IDE workflow, or use the command line when you need precise module and build-variant targeting or a repeatable CI job. Android also supports adb-based test execution for workflows that need its customization options.
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Do not treat a successful run of one target as a result for the whole app: first identify the changed module and the variant the change is meant to support, then run the relevant tests for that target. Android’s test-running documentation describes IDE, command-line, and adb workflows.
5. Verify on a device when device behavior matters
Use an emulator or connected hardware when the change depends on Android APIs, integration, permissions, or UI behavior that a local JVM test cannot represent. Inspect the resulting interaction and relevant Logcat output against the acceptance criteria; do not substitute a screenshot or a clean build for assertions about the behavior.
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A physical device is not mandatory for every workflow: Android supports emulator testing as well. The right choice depends on whether the feature’s behavior requires hardware or conditions that the emulator does not represent.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.6. Treat AI-generated tests as proposals too
Android Studio can generate Kotlin and Java unit tests, but generation does not guarantee useful coverage. Check whether each test states a meaningful outcome, exercises the relevant edge cases, and would fail if the implementation were incorrect. A test that merely runs the new code, or repeats its assumptions in its assertions, offers little protection.
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Google’s warning to validate generated code applies to generated tests as well. Use them as a starting point, then revise or add tests based on the behavior the feature actually requires.
7. Check what project context the assistant can receive
Before sharing source with an AI assistant, verify that the applicable data terms and project policy allow it. Android Studio documents context awareness as opt-in and provides .aiexclude restrictions. Its data-use terms differ depending on whether the user is on the free offering, uses a personal API key or Google One, or is covered by Enterprise terms.
Review the current settings and terms for your account and organization in Google’s Android Studio data and privacy documentation. Do not expose secrets or sensitive source unless sharing is approved under the policy that applies to your project.
When Android Studio Journeys may help
Journeys let teams describe UI flows in natural language and evaluate assertions based on what the AI sees on a device. Google documents the feature as Preview; project journeys require Android Gradle Plugin 9.0.0 or higher and run against configured build variants. Permissions are granted by default during a journey, so a flow that needs to verify permission-denial behavior should test that case separately.
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1Fix the driver behind crashes, sound loss and screen glitches2Repair Windows errors before they cause bigger problems3Scan for outdated or missing drivers - takes under a minuteThose constraints make Journeys a possible way to explore UI behavior, not a replacement for choosing and asserting the scenarios your feature requires. See Android Studio Journeys documentation.
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