Raelle Foil

I’ve noticed something interesting in QA job descriptions lately. More and more roles aren’t asking how well you test software anymore. They’re asking how well you test behavior. Specifically: ➡️ Does the AI hallucinate? ➡️ Does it leak sensitive data? ➡️ Does it behave differently with slight prompt changes? ➡️ Does it fail politely or catastrophically? What’s fascinating is that this isn’t a brand-new discipline. It’s still QA. The difference is: ↳ The bugs don’t reproduce the same way twice ↳ The “expected result” is probabilistic ↳ And the system can confidently lie to you 😅 Most QA engineers I talk to aren’t resistant to AI. They’re just unsure where they fit in this shift. My take? ↳ AI doesn’t remove QA—it raises the bar for what “quality” even means. The QAs who thrive next won’t be the ones who know the most tools. They’ll be the ones who know how to: ↳ Question outputs ↳ Define good vs dangerous behavior. ↳ And explain why something is risky in plain business terms Curious to hear from others: 👉 As a QA, what part of AI systems feels the most “untestable” to you right now? Hallucinations? Bias? Security? Something else?

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If you are vibe coding, you need to 2x or 3x your QA staff. Why? Because you are pumping out more code, more features, and getting them ready for review much faster. This coding is also lower quality and can cause a lot more issues. This means that there are going to be a lot more QA issues, more tickets, and more testing. So make sure you are budgeting for extra QA if you are expecting your engineers to vibe code.

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Good engineering starts with the truth. I once had a boss say, during a sales call: "if anyone asks, we're experts at socket programming in C#". We weren't; not by a longshot. And I wasn't comfortable lying about it, so I didn't. I still won't. The same goes for interviews. If I'm asked about a mistake I made, I won't downplay it; I'll lean in. I'll tell you about a *big* mistake I made - and the even bigger effort I put in to make it right. I don't want to land a job by pretending to be someone I'm not. And I certainly don't want to build systems on that kind of foundation. At this point in my life, success means feeling good when I wake up in the morning.

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Hey test automation QA community on LinkedIn Big news from Jason Huggins-he's the guy who created Selenium and Appium, right? Well, he just dropped a brand-new tool called #Vibium, and it's gonna make our lives way easier. Here's why it's a game-changer: ✓ Write tests in plain english: It making automation accessible beyond developers. Just say click the Sign Up button and boom-you're done. Even non-devs can use it! ✓ Self-healing locators: When the Ul changes (like a dev renaming a button), Vibium fixes itself. No more panic attacks when tests break! ✓ Fewer flaky tests: You know those annoying tests that fail for no reason? Vibium cuts that down big time. Less stress, more chill! ✓ Modern Architecture - Powered by WebDriver BiDi, the W3C's next-gen browser automation standard, for faster and more stable execution

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Most QA problems aren’t about tools or people, they’re about processes. If your testers are chasing bugs manually, your devs are guessing coverage, and your releases feel like fire drills, that’s not a resource issue. That’s a design flaw. Process is the real framework. Get that right, and everything else starts to click. #ProcessEngineering #SoftwareTesting #QualityOps #TestAutomation

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Client: "This feature is working as intended, it's all in the documentation." Me: "I know. I read it. Took us a while to figure it out." Client: "So what's the issue?" Me: ... If your QA needs to read the documentation over and over just to understand how a feature works, your player won't get it either. And your players won't have the documentation available, in front of them. Trust your QA. We're not here just to find bugs. We're your first real 'user', experiencing through your players' lenses. When a feature needs a deep explanation, that feature needs rethinking.

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Two things must ye know about devs who say "Leave me out of conversations! I just wanna write code!" 1. They're the first to complain when requirements aren't clear, or when the high-level architecture doesn't work, or when testers "break the code", or when their changes conflict with other people's. 2. They often write the worst code, too.

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You don't need to hire a software farm for anything anymore. You need one developer who sits next to you for 6 weeks and learns how your business runs. Not how it looks in a deck. How it actually runs. The messy inbox system. The Notion doc nobody follows. The 4-step process your EA does manually every morning. A good AI developer, someone who works in n8n, Claude, and modern automation tools, turns that into systems that run without you. We placed one with a 12-person e-commerce brand. In 8 weeks he'd automated their order exception workflow, their influencer outreach follow-up, and their weekly reporting. The admin team is being trained in AI. Those that don’t adopt are gone. 3 tasks. Each one was eating 6-8 hours a week from someone on the team. That’s money in your pocket. 416h per year. That’s almost a full quarter's worth of work. A dev shop's savings don't matter if they can't ship. Ours do. I wrote more on this on more detail in the blog linked below: https://lnkd.in/gVpWJGZw DM me if you have been seeing AI happening in front of you and want to know how you can avoid missing out.

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Think QA is just about squashing bugs?   Think again.   There's a bigger picture... Quality assurance isn't just bug-hunting. It's so much more. It's about alignment. Understanding how things affect the business, engaging the right people, and making sure testing meets user needs. It's not just about finding problems. It's about stopping them before they even start. Bugs? Just symptoms. The real issue? Poor quality strategy. Want to avoid common QA pitfalls? Here’s what to watch for: - Lack of clear communication - Ignoring user feedback - Rushing the testing phase - Not involving stakeholders - Overlooking long-term impact Quality can't be an afterthought. So, what's the biggest QA mistake you see every day? Let's talk!  #QualityAssurance #SoftwareTesting #TechIndustry

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Scrolling LinkedIn this morning and saw multiple posts from QA folks saying some version of: “AI is great at generating test scaffolding and boilerplate… but the thinking hasn’t changed.” I get why these posts exist. They’re trying to defend the value of QA. They’re trying to say: “You still need us.” And they’re right, you absolutely still need strong QA thinkers. But saying the thinking hasn't changed is naive. The thinking has changed. Substantially. AI isn’t just good at scaffolding anymore. It’s increasingly good at: Suggesting what to test Mapping how pieces fit together Generating unit, integration, and API tests Surfacing edge cases you didn’t initially consider So the job is no longer: “What are the test cases for this feature?” It’s: What level should this be tested at, unit, integration, contract, E2E? How was this system actually built? What context does the AI need to reason correctly? How do I evaluate whether the AI did a good job? How do I prompt it to go deeper when it’s wrong? What documentation must exist so AI can operate effectively? Where are the architectural risks? That’s not less thinking. That’s bigger thinking. Yes, you still need a deep understanding of the product. But so do developers. So does product. That alone isn’t what makes QA special. The value now is thinking like a director of the full stack. Understanding: System design Test strategy across layers Risk modeling AI strengths and failure modes Feedback loops It’s no longer about writing test cases. It’s about orchestrating intelligence. If you’re in QA and acting like nothing has changed, you’re going to get left behind. If you lean into the shift? You become exponentially more valuable. The tools changed. The surface work changed. And yes, the thinking changed too. And pretending it didn’t is the most dangerous move of all.

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Most dev teams think Swagger UI is documentation. I think it's the reason 60% of API integrations fail. Here's what's actually killing your partnerships… Swagger UI is not documentation. It is a tester. It is not a guide to first success. I’ve watched teams ship an API with a shiny Swagger UI and zero context. An integrator then spends hours clicking endpoints to guess the sequence. Launch stalls. Support explodes later. A working API is not an easy to use product. What was missing: • Plain language descriptions for each endpoint. What it does. When to use it. • Authentication path. How to get a key or token. Where it goes in the request. • First call guide. One page that gets a response in Postman in under five minutes. • Sequence map for core flows. Call A, then B, then C. What you pass from one to the next. • Try it for real. In-doc auth or a Postman collection so people can run the flow end to end. How I fix it in week one: 1. Write the First call page. Key, header, sample request, expected response. 2. Add an Auth guide with the exact steps and a copy-paste snippet. 3. Document the sequence for the top two jobs to be done. Show the order and the hand-off values. 4. Add plain language descriptions to every endpoint in Swagger. No jargon. 5. Publish a Postman collection and link it inside the docs. If a partner has to reverse engineer your API, you are burning time and goodwill. Fix the guides before the next sprint and your next launch will move. Which of these pages would have saved your team hours this month?

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Unreal requirements are getting out of hand. Just saw a job posting asking for: 5+ years experience Expert-level certifications Established client relationships Proven track record of results For an "entry-level" position. Make it make sense. Dear companies: How does someone get 5 years of experience without getting their first opportunity? You're asking for unicorns and wondering why you can't fill positions. Meanwhile, you're missing out on: The hungry recent grad who'll outwork everyone. The career changer with transferable skills. The coachable candidate who'll become your top performer. Here's what entry-level should actually mean: Willingness to learn Strong work ethic Good communication skills Professional attitude That's it. Stop creating impossible barriers. Every skill you listed can be taught in 90 days. Character and drive can't be taught at all. Hire for potential. Train for performance.

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If you're preparing for an SDET or QA Automation interview, just knowing Selenium or Playwright commands isn't enough. Top companies will test your ability to design robust, scalable, and maintainable testing solutions. I remember early in my career, the real challenge wasn't just writing scripts but building systems that last. That's what separates a good tester from a great one. Here are 8 must-practice automation challenges that frequently show up in coding rounds: 🔹 Design a Test Framework from Scratch (using Page Object Model) 🔹 Handle Advanced Synchronization Issues (Fluent Waits and custom wait conditions) 🔹 Automate REST API Scenarios (including auth, assertions, and schema validation) 🔹 Implement Data-Driven Testing (reading from Excel, CSV, or JSON files) 🔹 Integrate Tests into a CI/CD Pipeline (like Jenkins or GitLab CI) 🔹 Configure Parallel Test Execution (using TestNG/JUnit and Selenium Grid) 🔹 Automate Complex UI Interactions (like drag-and-drop, iframes, and dynamic tables) 🔹 Generate Comprehensive Test Reports (with tools like Allure or ExtentReports) ✅ These problems test how you think about architecture, solve real-world flakiness, manage test data, and integrate with the DevOps lifecycle. #automationtesting #testautomation #sdet #qa #softwaretesting #selenium #playwright #interviewprep #codingchallenge #apitesting #cicd #qualityassurance #qacommunity

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Helping someone break into QA automation this week reminded me You do not need the perfect job title to start building momentum. We went over a roadmap together. He is working in QA but has not been able to get real automation experience yet. So we built a game plan anyway. 𝗦𝘁𝗮𝗿𝘁 𝘄𝗶𝘁𝗵 𝘄𝗵𝗮𝘁 𝘆𝗼𝘂 𝗰𝗮𝗻 𝗰𝗼𝗻𝘁𝗿𝗼𝗹 Build a Playwright or Selenium project, even a small one Add it to your resume and GitHub Write a short README explaining what it tests and how 𝗧𝗮𝗿𝗴𝗲𝘁 𝘁𝗵𝗲 𝗿𝗶𝗴𝗵𝘁 𝗿𝗼𝗹𝗲𝘀 Look for QA automation or hybrid roles that mention Python or Selenium Focus on junior-level positions that ask for 0 to 2 years of experience Use sites like BuiltIn, Google Jobs, and LinkedIn to search and filter 𝗟𝗲𝘃𝗲𝗹 𝘂𝗽 𝘆𝗼𝘂𝗿 𝘀𝗸𝗶𝗹𝗹𝘀 𝘄𝗵𝗶𝗹𝗲 𝘆𝗼𝘂 𝗮𝗽𝗽𝗹𝘆 Learn GitHub Actions to show a basic CI/CD experience Add API testing with Postman to your project Read through public test automation repos to study how others write tests 𝗔𝗻𝗱 𝘄𝗵𝗲𝗻 𝗶𝘁 𝗰𝗼𝗺𝗲𝘀 𝘁𝗼 𝗶𝗻𝘁𝗲𝗿𝘃𝗶𝗲𝘄𝘀 Do more than study. Practice speaking out loud Use the STAR format to organize your answers Keep a list of 10 examples from internships or personal projects that you can use in interviews If you are trying to grow into QA automation without official experience, it is possible. You just need structure and consistency. I also put together a few digital products that might help if you want a shortcut: https://lnkd.in/epWTmucn

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