I’ve been thinking about something that’s easy to miss with test automation: can a test be completely reliable and still be outdated?
Tools like mabl focus on keeping coverage current as applications change, Testim uses AI-powered locators to make tests more resilient, Functionize looks at AI-driven maintenance and test realignment, and Applitools takes a different angle with visual and functional validation. I like that each approach is solving a different part of the same maintenance problem.
While exploring X360 AI Tech, this made me look at test maintenance a little differently. A test can keep passing every day and still be less useful if the requirement, user flow, or expected behavior has changed. In that case, there’s no failure telling us that something needs attention.
That’s what I find interesting about AI-assisted testing. Maybe AI shouldn’t only help us fix tests when they break. It could also help us notice tests that have been passing for a long time but may no longer represent what we actually want to validate.
I’m starting to think that a healthy test suite isn’t just one with fewer failures. It’s one where we still understand why each important test exists and whether it matches the current product.
How do you usually spot tests that are still passing but have slowly become outdated?
