Developers don't write most of their code from scratch anymore, they generate it. That's already changed the pace of software delivery, and it's now landing directly on QA: more changes, more code, more required coverage, without bigger teams.This session looks at what that means for testing in practice. We'll walk through a workflow where AI does real work: turning a requirement into a starting point instead of a blank page, deciding what's worth automating, and scoping regression to what actually changed.
Yuval Gal
Marketing Manager
Panaya
Yuval Gal is a Product Marketing Manager at Panaya, where she works on how enterprise QA and IT teams handle constant change across their business-critical systems. With a strong background in B2B SaaS, Yuval focuses on the practical side of AI in testing: what to test, what to skip, and what is worth automating. Her work centers on turning platform capability into workflows teams can actually run.