Systems | Development | Analytics | API | Testing

Can you trust AI agents to run your tests without losing control of your release process? In this video, you’ll learn how, with SmartBear BearQ’s agentic QA system, the answer is yes, because you decide exactly how much autonomy the agents get. This enables you to adapt QA to fast-moving AI codebases, all with human oversight.

When Spring Boot goes end of life, most teams assume their LTS coverage has them protected. It doesn't — at least not the way they think. The real risk isn't in the Spring Boot or Spring Framework version on the label. It's in the 40+ libraries the Bill of Materials has quietly pinned underneath it, frozen at EOL while CVE research keeps moving.

This session looks at how agentic automation can take over web and mobile regression. We start with the regression tax: the slow 3-day cycle, the manual triage, and the flaky reruns nobody trusts. We then cover why scripted suites hit a wall and make the case for handing regression to agents instead. The core of the talk is how it actually works, with Appium MCP driving mobile and Playwright MCP driving web, interpreting intent rather than hard-coded steps and adapting when the UI shifts.

AI is reshaping how software gets built and tested faster than most QA teams can keep pace, yet teams rarely get to influence what a vendor ships before the decision is made. That's why we created Tricentis Labs. Tricentis Labs is where agentic-AI ideas are built in public, giving quality engineering teams early access to experiments and a say in which ones become real products. In this announcement, Ryan Yackel and David Colwell walk through how Labs works and the first three experiments open to customers and partners today.