Systems | Development | Analytics | API | Testing

Testers are great at finding flaws in systems. But what happens when the system under test is the tester themselves? In today’s world of constant change, rising stress, and growing uncertainty, resilience has become just as critical as technical skill. From handling pushback and tight timelines to navigating burnout and self-doubt, testers face pressures that often go unseen.

AI promises speed, but testers are often the first to notice where it quietly breaks down. Beneath the impressive outputs lie hidden issues like hallucinations, false confidence, and blind spots that can easily go unnoticed yet cause real damage if left unchecked. This atomic talk explores the subtle ways AI can fail, why speed without reliability is risky, and how testers play a critical role in supervising and strengthening AI systems. It highlights practical strategies for working alongside AI to make its outputs more trustworthy, reliable, and genuinely useful.

Learn more: https://speedscale.com/

Business logic sits at the core of every system, yet it often becomes the hardest part to change. Rules get buried in complex code, feedback arrives too late, and even small updates turn into slow, risky efforts. This session explores why teams struggle with something that should be simple and how to bring clarity back into the process.

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?