QA Engineer

Speech: Enhancing QA Work with AI: A Phase-by-Phase Guide

This talk presents a phase-by-phase approach to using AI meaningfully in software testing. It explores how AI can support key QA activities such as test planning, case design, exploratory testing, defect reporting, and regression analysis—without replacing human judgment.

Rather than promoting AI as a one-size-fits-all solution, the session focuses on practical applications that improve speed, coverage, and clarity in testing workflows. It highlights how AI can reduce repetitive effort while reinforcing the tester’s role in critical thinking and product quality.

I’m a QA engineer and educator with a passion for purposeful testing. I’ve spent the last four years building quality into fast-moving products, especially in e-commerce. I believe in meaningful automation, sharp analysis, and being hands-on from start to finish. My focus is always on real impact—not noise.

I see QA as more than just a gatekeeper role. It’s a mindset that shapes product direction. I believe testers should ask the uncomfortable questions early, challenge assumptions, and prevent failure—not just report it. To me, testing means owning quality, not just measuring it.

With a degree in Management Information Systems, I’ve worked across web, mobile, and desktop QA projects using tools like Selenium, Postman, and Python. I hold certifications in Test Automation, Docker, and DevOps, which support my effort to stay technically current and adaptable.

Outside of my engineering role, I write on topics like human-centered automation and tester roles in agile teams. You can find my articles in LinkedIn. Outside of QA, I work closely with high school and university students, helping them think through questions of purpose, identity, and values.