How do you test code your AI coding agent wrote?

Claude Code, Cursor and Copilot can now write a whole feature while you get a coffee. That part of the job got fast. The part after it, checking that the code actually works, did not.

Most developers have already made the switch. In the Stack Overflow Developer Survey 2025, 84% of developers said they use or plan to use AI tools in their work. But trust went the other way: 46% said they actively distrust the accuracy of what those tools produce.

So teams end up in an awkward place. They write code faster than ever, then either slow down to check it by hand, or ship it and hope.

Why AI-written code needs a different kind of checking

AI-written code is not worse than human code by default. It fails in different ways:

• It looks right. The code is tidy and confident, so reviewers skim it.
• It passes its own tests. If the agent wrote the code and the tests together, the tests often check what the code does, not what it should do.
• It handles the happy path. Empty lists, slow networks, expired sessions and two users at once are where it tends to break.
• There is a lot of it. A reviewer who could read 200 lines a day now gets 2,000.

The answer is not to read every line more carefully. It is to make checking as fast as writing.

A simple routine for every AI-written change

1. Write the test cases before the code

Ask the agent for the test cases first, in plain language: what the feature must do, and what must never happen. Read that list yourself. It is ten lines instead of five hundred, and it is where your judgement matters most.

2. Run the tests somewhere real

Tests that only pass on the developer's laptop prove little. Run them on real browsers and devices, against a running build, the way a user would meet the feature.

3. Keep a record of every run

When a test fails next week, you want to know whether it ever passed, on which build, and what changed. A test case and its run history should live in one place, not in a chat log.

4. Check what tests don't cover

Functional tests don't tell you whether an API leaks data or falls over when fifty people use it at once. Add a security scan and a short load test before anything important ships.

5. Send failures back to the agent

This is the step most teams skip. When a test fails, the agent that wrote the code should get the failure, the logs and a recording, and fix it itself. A person approves the result instead of doing the triage.

Where ProvaLab fits

We built ProvaLab so a coding agent can do this whole routine on its own. Through the Claude Code plugin or MCP, the agent runs your tests on cloud browsers and devices, records every result in test management, scans for security issues, runs load tests, and gets the failures back so it can fix them.

You can see it working in the two-minute product tour, or book a 30-minute demo and we will run it against your own app.

AI made writing code fast. Checking it should be just as fast.