What I Found While Exploring AI-Powered Test Automation

<p>Last month I asked a senior candidate the same question I ask everyone. "Tell me about a flaky test you fixed and how you fixed it."</p> <p>She paused and said, "I just added a

<h2> The Asymmetry of Change: Why Your Tests Are Looking the Wrong Way </h2> <p>A passing build is often treated as a certificate of correctness. In reality, it's a narrow

<p><em>This is a submission for the <a href="https://dev.to/challenges/google-gemma-2026-05-06">Gemma 4 Challenge: Write About Gemma 4</a></em></p> <h3> Why I Wrote This </h3>

<p>An AI coding agent implements a feature, generates tests, runs them, and opens a pull request with a green build.</p> <p>That looks like independent verification. It often is

<p>AI test automation architecture is the system that tells AI what to test.</p> <p>It also defines how to run tests and prove the result.</p> <p>I split it into three layers:

<p>Here’s what actually happens in most QA teams: a sprint ends, features ship, and someone still has to figure out which test cases cover the new flows and which existing ones