Systems | Development | Analytics | API | Testing

Testers weren’t nervous about AI replacing their work, the challenges were actually logistical. Teams struggled with unpredictable pre-production environment changes, global coordination, and unclear deployment windows, which caused confusion during monitoring and adoption. — Mush Honda, Chief Quality Architect at Katalon Follow Katalon for more insights in our series!

As AI agents take on critical roles in testing and automation, their weaknesses can become hidden risks waiting to surface. This session explores how applying red teaming techniques, borrowed from cybersecurity, can help uncover vulnerabilities in AI agents before they cause real-world failures.

Overburdened clouds rack up notable costs — in terms of storage, productivity, and finances. It’s time to make a change. This webinar makes it clear: You don’t have to struggle with your cloud storage and issues any longer. Ephemeral data will help free up space in your cloud, make data more accessible, and save you money. Our demo highlights the Perforce Delphix DevOps Data Platform for Kubernetes and its impact in numbers.

Learn more at: speedscale.com.

AI has transformed how software is built and tested, yet many teams still rely on traditional metrics like pass rates, coverage, and defect counts. While these numbers look good on dashboards, they often fail to answer the most important question in the AI era. Can we actually trust what the system is doing?