How to embed quality across the agentic SDLC

AI has accelerated software development and raised the bar for quality engineering. Code is generated and released at a pace most teams were not built to support, introducing new forms of quality risk across large, complex environments. As a result, test coverage is no longer just about finding defects. It is also about understanding what has been built, what has been validated, and where risk remains.

When development moves faster than quality teams can keep up, a gap forms between speed and trust. To close that gap, teams need an approach that supports rapid development while maintaining visibility, control, and governance. In this webinar, we will show how to modernize quality engineering with a scalable, intelligence-driven model that keeps humans in control.

You will also see how Tricentis AI Workspace helps embed quality across the SDLC while enabling AI-powered workflows that scale with faster release cycles.

• How to build confidence in AI-assisted systems in a practical, repeatable way
• What it takes to support rapid development while maintaining visibility and control
• How to apply AI-enabled quality engineering strategies across the SDLC

Speakers:

• Ryan Yackel, SVP Product Marketing
• Michal Hrncirik, Product Manager, AI Workspace