Blog (Resources Center)

Watch an AI agent run a regression test sometime. Really watch it.

It lands on a login page. It reads the entire page structure: every element, every attribute, every nested div someone added in 2019 that nobody has dared to remove since. Then it reasons. It weighs its options. It explains to itself, at some length, that the button labeled "Sign in" is probably the on...

Your manual test library is more than documentation. It contains years of decisions about what your product should do, and how to tell when it doesn't. That knowledge is a valuable starting point for automation, not something you should have to recreate from scratch.

The clearest example came up in a customer conversation. The head of quality at a fast-growing fintech...

Your team has more changes to test, more environments to cover and less time to maintain regression suites. AI can help produce tests, but that introduces another workload: deciding whether those tests check the right behavior, whether a repair hides a defect and whether the evidence is enough to support a release.

Agentic QA tools aim to take on more of that work, fr...

In a release test I published in July, Katalon’s AI runner reported seven cases passed and four failed. I could open the steps, inspect their screenshots, and watch the browser session. The failed rows showed which expectations broke. The passed r...

“Customers can apply a discount code” looks ready for testing. Give that sentence to an AI model and it can produce cases for valid, invalid, expired, and reused codes in seconds. The trouble starts when someone asks what a valid code should do. Which basket is eligible? Does the discount change the displayed total before or after tax? Should the saved order carry the same am...