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I’ve been in QA for a few years now. I know how testing works. You write a test case. You define the expected result. You run it. It either passes or fails. Simple. So when our team started working on an AI-powered feature, I thought, okay, same process. Different kind of input, but same idea. […]
The way we test software is changing — and it’s changing fast. Over the past couple of years, AI has moved from a buzzword in QA discussions to something teams are actively building into their workflows. If you’re working in software quality or engineering, understanding these shifts isn’t optional anymore. It’s part of staying effective.
If you’ve spent any time working in test automation, you know the drill: We start every project with the best intentions — promising ourselves we’ll write clean, maintainable code But fast forward a few months, and we’re spending half our week fixing flaky tests, hunting down brittle locators, and dealing with “duplicate email” errors in
Why I’ll Never Manually Write Test Scripts Again (And You Shouldn’t Either) Read More »
Artificial Intelligence is no longer a futuristic concept or an experimental capability. In 2026, AI has firmly embedded itself into core business operations—powering decisions in hiring, finance, healthcare, customer experience, and beyond. This shift brings a fundamental change: AI risk is now business risk. For Quality Engineering teams, especially QA leaders, this marks a turning
AI Risk & Compliance in 2026: Why QA Teams Must Lead the Shift Read More »
Many of you may already be familiar with Physical AI — the evolution of artificial intelligence from purely digital intelligence to systems that understand and interact with the real world. Physical AI enables machines to: Understand physical environments Adapt to real-world conditions Make autonomous decisions Execute actions in dynamic systems This shift — from information
From Physical AI to AI-Augmented QA: The Next Evolution of Testing Read More »
