QA testing in software is a fascinating topic to think about, with a number of paradoxical properties: despite testing’s entrenchment in the SDLC and the ubiquity of software testing workflows, we’ve never seen a breakout company hit venture scale in the QA testing space. The prevalence of open source (think Jenkins, TestMonitor, Selenium) combined with the brittle nature of these test automation tools have shaped the way a company treats testing: as a lot of manual and custom work, which hence begets lot headcount needed to do it well (3:1 SWE:QA Eng ratio needed to maintain high test coverage).
Does AI and this net new ingredient of LLMs to tackle QA testing change things? Instead of predefining test automation workflows (which tends to be rigid and static), can an LLM/agentic system that anchors towards the output goal of exploring the entirety of a piece of software be more effective? A number of interesting companies in the space with a panoply of interesting approaches - Bug0, Momentic, Skyramp, Meticulous, Synthetic Society (YC S25), and others. Excited to spend more time in this space, if anyone also shares this interest or is actively building here please reach out!
👋 I’m a Researcher at Work-Bench, a Seed stage enterprise-focused VC fund based in New York City. Our sweet spot for investment at Seed correlates with building out a startup’s early go-to-market motions.
