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What are the best AI tools for writing and improving tests?

The useful ones start from a failure or a behaviour, not from a coverage percentage. Prefer tools that reproduce a real bug as a failing test first, then verify the fix makes it pass.

Surveyed 17 September 2026

Generate and improve tests

Open in Tools →
No.Tool
  1. 01
    Expect

    Reads your git diff, generates AI test plans, and runs them in real browsers using your existing login sessions.

    Developer Tools
  2. 02
    qa-use

    Automates QA by handing test flows to browser agents that exercise web apps end to end.

    Developer Tools
  3. 03
    Trailblaze

    AI-driven Android UI testing framework where plain-language test descriptions let an agent drive the app.

    Developer Tools
  4. 04
    OpenAI Testing Agent Demo

    Demo UI testing agent on OpenAI's Computer Use model that drives a browser to test apps end to end.

    AI Agents

A curated selection in editorial order. Use the fit and evidence to judge it for your task. Something missing?

What to look for

  • 01Does it write tests that can fail? Generated tests that assert whatever the code currently does lock in bugs instead of catching them.
  • 02Does it run the suite, or only write files? A tool that never executes what it wrote cannot tell you it works.
  • 03Does it fit your existing framework and fixtures, or import a second test runner alongside the one you have?

Common questions

Does AI-generated test coverage actually catch bugs?
Only when the test was written to reproduce a specific failure. Coverage generated to hit a percentage target mostly asserts current behaviour, which passes forever and catches nothing.
What is the most reliable way to use an agent for testing?
Red-green: have it write a test that fails for the right reason, confirm the failure, then fix the code until it passes. The failing run is the proof the test is real.

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