We didn't build AI features because everyone else is. We built them because understanding test failures at scale was taking too long. Here's how we approached it, what we optimised for, and why Automation Intelligence extends DoesQA rather than replacing what already works.

Smelly tests are easy to recognize once you’ve been burned by them enough times. This article walks through the most common automation smells, from flaky “just rerun it” tests to over-mocked setups that don’t reflect real user behavior. If your test suite technically passes but still feels untrustworthy, this is a quick, relatable guide to spotting problems early and understanding what they usually say about your test design.

APM is not just for ops teams watching production dashboards. For testers, it is a practical source of truth. This article breaks down five ways APM data helps testers stop guessing, focus regression where it matters, strengthen exploratory testing, write clearer bug reports, and feel more confident in their decisions. If you want your testing to be guided by real usage instead of assumptions, this is a solid place to start.

Many of the world's largest economies have seen stunted growth for the last few years, and shareholders want profits. Companies that are struggling are looking to shred staffing costs, and the ones that aren't still want to maximize profits.

You're not trying to avoid all injuries, just the larger ones that would cause more significant damage or leave a permanent mark.

Since the global pandemic swept the globe a few years ago, one area that has yet to recover (and continues to decline) is the quality of shipped software.