Systems | Development | Analytics | API | Testing

In this fireside chat with Jaydeep, we’ll dive into how AI is changing the way we measure success in both QA processes and live generative AI bots. On the QA side, we’ll look at cycle time reduction—the “time goalie” metric that shows how quickly we move from discovering a bug to fixing it. We’ll also talk about predictive quality accuracy, which shifts QA from being reactive to proactive by predicting which code changes are most likely to introduce bugs. And of course, we’ll touch on test creation velocity—how much faster teams are able to create meaningful automation with AI’s support.

In this session, Andrew will trace Vibe Coding's journey—from emergence to current impact—exploring how it has got us into re-thinking development and testing. He'll examine today's tools, real-world use cases, and the cultural shifts teams need to embrace this AI-driven approach. Andrew will share hot takes on myths versus reality and deliver practical advice for getting started. This video is of one of the sessions presented at - World’s Leading Virtual Software Testing Conference.

Leon Taiman, Global Practice Lead at Dell Technologies, discusses the strategic partnership between Dell, Cloudera, and NVIDIA to accelerate the adoption of Private AI on-premises for customers.

The AI Forecast welcomes back John Santaferraro, host of The Digital Analyst Podcast and CEO of Ferraro Consulting, for a candid look at what’s really coming next for AI in 2026.

The AI ecosystem is exploding with tools that promise to accelerate delivery, improve quality, and transform the way we work. Yet for many teams, evaluating these tools is overwhelming - flashy demos and marketing claims rarely answer the real questions: Will this work in our context? Can it scale? Is it sustainable?

AI is reshaping software testing, but real quality does not come from hype alone. This session explores where AI truly adds value in automation and where human testers remain essential. It focuses on building a practical partnership between AI and testers, where speed and scale are balanced with judgment, context, and responsibility.

AI is leveling the field across organizations. Everyone, from leaders to individual contributors, is approaching work with a beginner’s mindset, questioning what AI can do, what it cannot, and how it affects business, customers, and roles. This shared uncertainty challenges traditional leadership models and raises a fundamental question. How does leadership evolve when no one has all the answers?