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Wendy Erdheim-Poch

Wendy Erdheim-Poch

Wendy Erdheim-Poch is a QA Automation Engineer at Elementor with over nine years of experience in JavaScript testing and automation. She helps development teams build confidence in their code by making quality a natural part of the workflow. She’s passionate about pushing buttons, breaking things, and making sure everything works the way it should. Outside of tech, she’s a swim teacher, mom of two, and enjoys camping and creative projects.
Elementor, Israelsubstack.com/@wendyqaqueenWendyQAQueenwendy-erdheim-poch-b887888
Think Like a Tester: What to Look For in AI-Generated Code
JSNation 2026JSNation 2026
Upcoming
Think Like a Tester: What to Look For in AI-Generated Code
AI is writing code faster than ever. But there's a gap: the gap between "it works" and "it works correctly."As a QA Automation Engineer with 9 years of experience, I've developed the instinct to see what breaks before it breaks. AI generates clean code that hides catastrophic bugs in plain sight. This talk teaches you "the tester's eye" – the ability to spot edge cases, boundary conditions, state issues, and silent failures that AI confidently creates.You're reviewing AI code with developer eyes trained to see "does this solve the problem?" Testers see something different: "what are all the ways this could fail?" I'm teaching you to see both.
artificial intelligencetesting
Think Like a Tester: What to Look For in AI-Generated Code
Web Engineering Summit 2026Web Engineering Summit 2026
Upcoming
Think Like a Tester: What to Look For in AI-Generated Code
AI is writing code faster than ever. But there's a gap: the gap between "it works" and "it works correctly."As a QA Automation Engineer with 9 years of experience, I've developed the instinct to see what breaks before it breaks. AI generates clean code that hides catastrophic bugs in plain sight. This talk teaches you "the tester's eye" – the ability to spot edge cases, boundary conditions, state issues, and silent failures that AI confidently creates.You're reviewing AI code with developer eyes trained to see "does this solve the problem?" Testers see something different: "what are all the ways this could fail?" I'm teaching you to see both.
testing