Three experts break down AI-native QA in production.
Turning delivery over to autonomous agents and AI-native architectures introduces a major engineering dilemma: how do you maintain accountable quality when humans step back? Without proper architecture and guardrails, AI-native workflows lead to context rot, unmitigated risk, and false confidence at scale.
In this session, a QA strategist, a systems architect, and a front-line engineering lead come together to unpack the real-world friction of agentic testing.
Key takeaways:
Turning delivery over to autonomous agents and AI-native architectures introduces a major engineering dilemma: how do you maintain accountable quality when humans step back? Without proper architecture and guardrails, AI-native workflows lead to context rot, unmitigated risk, and false confidence at scale.
In this session, a QA strategist, a systems architect, and a front-line engineering lead come together to unpack the real-world friction of agentic testing.
Key takeaways:
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AI QE Specialist
Beth Marshall is an experienced and pragmatic Quality Engineer fascinated by all things AI and what it means for our industry, both now and in the future. Currently working as a specialist AI QE team at Lloyds Banking Group, she supports thousands of engineers with AI-assisted test automation frameworks.
Founder of ArchQA
Ivan Davidov is an Agentic Quality Engineer and the founder of ArchQA. He designs agentic testing systems and has trained more than 4,000+ engineers through global agentic Playwright automation workshops and courses.
QE Strategist
Paul Grizzaffi is a QE strategist, practitioner, and international keynote speaker who creates high-impact test automation solutions. A writer and a guest lecturer at the University of Texas at Dallas, he frequently shares insights on technology and architecture across the global testing community.
