Software Testing Unleashed - QA, DevEx & Quality Engineering

This time I talk to Mitko Mitev, about how AI is reshaping our work as testers, without replacing us. Mitko shows exactly where AI tools save real time across test planning, test case generation, and exploratory testing, and why human expertise remains non-negotiable for context, business logic, and validation. We go into the shift from writing scripts to instructing agents in plain language, how ISTQB's new AI syllabi prepare testers for what's coming, and why waiting another year to explore AI might already be too late.

In this episode, I talk with Marta Firlej about a topic most testers avoid: money. Marta explains why understanding how your company actually makes money is crucial for QA professionals, and walks through the real costs behind salaries, automation projects, and test activities that stakeholders care about. She shares a practical calculation method to assess whether test automation is worth the investment, and challenges us to translate testing value into business numbers.

In this episode, I talk with Simon Stewart, professional software developer and former lead of the Selenium project for over 10 years, about one of the most frustrating problems in software testing: flaky tests. Simon reveals why a flaky test isn't always a bad test – sometimes it's actually exposing real production risks that your team needs to address. We dive into practical strategies for handling flakiness in CI pipelines, from gatekeeping techniques used at Meta to knowing when it's actually okay to delete tests. You'll learn why assigning ownership to individuals (not teams) is crucial, and how to use test flakiness as valuable signal rather than just noise.

In this episode, I talk with Line Ebdrup Thomsen, quality engineering manager, about why software testing attracts more women than other tech roles – and why that's still not enough. Line shares how she coaches testers to be assertive but kind, especially when they're the only woman or the only tester in a team of developers. We discuss what prevents women from speaking up, how curiosity and communication skills matter more than your degree, and why the next generation of leaders might still need a wake-up call.

In this episode, I talk with Natalia Romanska about why our biggest professional disasters often teach us more than our polished success stories. She shares how a 70,000 złoty accounting mistake early in her career forced her to develop the self-awareness that now guides her QA work—and why that painful learning stuck harder than any training ever could. We dig into the uncomfortable truth that testers rarely talk about: the gap between knowing we should learn from failures and actually sitting down to extract those lessons. Natalia offers concrete practices for turning blame into growth, from the "magic five whys" to building feedback loops that don't just stroke our egos.

In this episode, I talk with Callum Akehurst-Ryan, a quality coach with nearly 20 years of experience, about why exploratory testing is far more than random button-pushing—and how teams waste it by using it in all the wrong places. Callum walks us through practical exploratory testing techniques that help uncover risks in non-functional requirements like performance and security, especially when no one has bothered to document what "good" should look like. We discuss how to structure exploration with timeboxes and risk-based scopes, when to turn findings into automated tests, and why retrofitting quality into existing systems demands a different software testing strategy than most teams realize.

In this episode, I talk with Maryia Tuleika about stepping on stage in tech and testing. We explore why people speak: joy of sharing, stage energy, and community. The hard part is fear and stress. If you fear the stage, you will hear simple moves that help. Maryia shows how to switch stress to excitement: prep well, record dry runs, collect feedback, use box breathing, slow down, and stand tall.

In this episode, I talk with Linda Van De Vooren about impostor syndrome, mental health, and growth in testing. Linda shares stories, from eating disorders to the inner critic she named Hannibal Lecter. We look at how doubt hits our work, like writing a test plan that feels too easy. Her tactics: Share openly. Check basic needs. Treat your comfort zone like a rainbow and pick a color you can handle today. Build an honest feedback circle.

In this episode, I talk with Jani Grönman about KPIs for quality. We ask what to measure, and why. Jani shares pairs that keep teams honest. Test pass rate with escaped defects or flaky tests. Mean time to recovery with reopen rate. Lead time to production with customer impact. One team, one number. Keep it to three or four KPIs, own them, and act. We talk about agency at work and product sense. Your tests are not a scoreboard. They are a feedback loop. Bring product and engineering together, do root cause analysis. I left inspired to pick fewer numbers, tell stories, and ship with care.

In this episode, I talk with Pekka Klärck about Robot Framework. We start with 2004, his thesis roots, and Nokia Networks turning a prototype into an open source project in 2008. He explains the core idea: a generic engine with reusable libraries, human readable tests, and one set of reports. Best fit in mixed tech stacks. We revisit milestones like the move to plain text, a new parser, and a thriving ecosystem. Pekka previews secret variables in 7.4, a modern user guide, markdown docs, and a cleaner namespace with backward compatibility. He even tests Robot Framework with Robot Framework.

In this episode, I talk with Florian Fieber about what 2025 taught testers and how to get ready for 2026. AI boosts productivity, it does not replace us. The sweet spot is generation of artifacts like test ideas, cases, scripts, and data. Accessibility grew due to the EU AI act, yet many underestimate the work. A plugin is not enough. You need manual checks and early design. For 2026 we expect agentic AI and a pilot role for testers. AI literacy becomes company wide.

In this episode, I talk with Tibor Csöndes about how testing grew up and where it goes next. We recorded live at HUSTEF in Budapest, a conference he helped shape. Tibor shares telco roots where automation was normal. Tools change, thinking stays. He sees AI as a third wave after CATG and model based testing. Helpful, not a job thief. Use it, or the testers who do will take your seat. ISTQB gave us a common language across industries. Learn the basics, automation, AI, and the human stuff like clear messages and critical thinking.

In this episode, I talk with Péter Földházi about test automation that solves real problems, not shiny tools. Péter brings two decades in quality and helped write the ISTQB automation syllabi. We ask why to automate, where it fits, and how the test pyramid guides choices across unit, API, and UI. I like how the simple pyramid makes choices visible. He shares a gaming case with 5,000 defects and a velocity drop. Strategy first, then tools, six month steps, and clear value.