Our beautiful Berlin QA community gathered again in early October, and even with autumn in full swing, around 70 people showed up for another great evening of ideas, demos, and honest conversations about quality. I’m so damn happy to see how this community has grown: familiar faces who’ve

Q3 was special. We took the feedback, ideas, and friction points from our community and channeled them into a focused push on three core fronts: simplifying your workflow, making our AI an indispensable partner, and giving you enterprise-grade control. The result? Some of our most impactful updates to date. Here's

Test automation is often treated as a checklist item: if you have it, great; if not, build it. But too many teams automate without knowing what value they expect, or how to measure whether the investment is paying off. That’s a problem. Because automation is an investment. Like any

Vitaly Sharovatov and Anupam Krishnamurthy investigate the Myth of Laziness in a new research paper, available for download now from Zenodo. Laziness as a Construct, Not a Trait Research across psychology, neuroscience, and organizational behavior shows that “laziness” is rarely an inherent trait. Instead, behaviors that look like disengagement usually

It’s 6:47 PM. The go-live is tomorrow. Your PM, Julia, leans over your desk:  “We’re sure the MFA flow was fully tested after that UI change, right?” A simple question but your mind races. That was ticket JIRA-4815. The original requirements are in a Confluence doc titled

Consistency in testing shouldn't be a constant struggle. It should be the default. We believe the key isn't to work harder, but to remove the friction that makes the work difficult in the first place. This month, we took a hard look at those time-consuming, repetitive tasks that get in

In the first article of this series, I focused on where AI is already proving useful in test automation: generating test cases and assisting with automation. In the second, I explored what’s still emerging: promising ideas like defect prediction and visual testing that work in some places but aren’

In the previous article, I looked at how AI is already improving test automation: from test case generation to self-healing locators and assisted test conversions. These tools are in production today, delivering real value for many teams. But not all AI applications in testing are ready for prime time. Some

In 2024, a product called Devin AI, was introduced by Cognition Labs as the “world’s first fully autonomous AI software engineer”. The authors claimed that Devin could independently plan, code, debug, and deploy entire applications based on natural language prompts — essentially, perform typical developer tasks. This announcement gained significant