Recently active topics

🎓 Course Overview: Generative AI for TestersGenerative AI is revolutionizing software testing, transforming it from a futuristic concept into a present-day necessity. To equip testers with the skills needed to navigate this evolving landscape, Tricentis presents the Generative AI for Testers course. This interactive mini-course is designed to help testers understand, apply, and benefit from Generative AI in their testing processes.📁Structure of the course: Introduction to Generative AI for Testers Deep Dive Leveraging LLMs and Mastering Prompt Engineering Implementation Strategies and What Comes Next🧠 What You'll LearnBy the end of this course, you will be able to: Explain the fundamentals of Generative AI, how it differs from traditional AI, and its role in software testing. Identify and apply AI-powered testing techniques, including prompt engineering, in-context learning, and model selection. Evaluate the advantages, limitations, and biases of Generative AI models to make inf

Dinesh Gujarathi: Senior QA Engineer · Hands-on practitioner with Claude Code & GitHub CopilotAI in Software Testing · QA Engineering · AI Coding Agents5 tips covered in this articleGive the agent half the answer before it starts — clear context prevents hours of wrong output Learn enough code to question what you get — reading beats trusting blindly Build your instructions file from your own experience — CLAUDE.md and copilot-instructions.md done right Set guardrails before and during the session — hooks, pre-hooks, and real-time redirection Use plan mode and catch wrong directions early — correct the plan, not the outputYou will learnHow to write prompts that reduce agent guessing · Why one programming language changes how you use these tools · How to build CLAUDE.md and copilot-instructions.md from your own experience · How to use hooks and pre-hooks to protect sensitive files · Why git diff is your most underused safety net.You’re using Claude Code or GitHub Copilot. It asks pe

Certification course by Karthik K.K.  Course description:AI is no longer a future skill for QA engineers — it's the present one.In this course you'll learn what AI actually is, how large language models think, and why context and prompt engineering are the difference between mediocre and outstanding results.You will explore real AI models like Claude, ChatGPT, and Grok, build custom AI agents, and create reusable agent skills that automate entire testing workflows. You'll see live demos of AI generating complete test suites, writing production-ready code, navigating real browsers, and producing documentation — all without you writing a single line manually.By the end, you won't just understand AI — you'll know how to put it to work. Whether you're a manual tester looking to move faster, an automation engineer wanting smarter workflows, or a QA lead preparing your team for what's next, this course will transform the way you work and position you as an AI-powered QA engineer ready for th

Certification course by Japneet Sachdeva🆓 Free course · 36 lessons · Certificate included · Online · Beginner to IntermediateCourse description:This free certification course is built for manual testers and QA engineers who need to develop real coding ability from the ground up. Starting with Java fundamentals and progressing through arrays, strings, and essential data structures, each topic is approached at three levels — brute force, better, and optimal.The focus throughout is on pattern recognition: learning to identify and apply the Two-Pointer, Sliding Window, and other core algorithmic techniques that appear most frequently in SDET technical interviews. By the end, you will be able to visualize solutions clearly and implement them efficiently in Java.▶️ Start the Course📁 Structure of the course:Basics Understanding Divide and Modulo Operators Right Angle Pattern Print – Code Right Angle Pattern Print – Logic Pattern 2, 3 & 4 Explanations with Code Collections Overview – Lis

Author: Ujjwal Kumar Singh, Senior QA Engineer · 8+ years in enterprise QA  · beinghumantester.github.ioKey takeawaysAI will not replace testers — but it will make undocumented tester expertise visible and urgent to address There are two types of invisible testing work: genuine professional expertise, and organizational debt carried by people AI test generation tools cannot perform causal reasoning about system failures — this requires human mental models built over years The adaptive capacity testers exercise daily is the most undervalued competency in software engineering Organizations must document risk models and acceptance criteria before AI integration, not after Testers who make their judgment explicit become more valuable as AI capabilities increaseFor years, software teams believed their testing processes were robust. In reality, many were functioning only because testers were quietly compensating for everything the process failed to capture.When a requirement arrived without

For years, we have defined software quality through non-functional requirements. Performance told us how fast a system responds. Security told us how safe it is. Reliability told us whether it can be trusted over time. These were not features users directly interacted with, but they quietly determined whether a system deserved to exist in the real world.Today, something equally critical has entered this space:Ethics.Not as a philosophical idea, but as a practical requirement that directly influences how systems behave, decide, and impact people.The shift did not happen overnight. It crept in as systems started doing more than executing instructions. When software was rule-based, correctness was enough. If the logic was right, the outcome was right. Testing, therefore, focused on validating that logic.AI changed that foundation.AI systems do not follow explicit rules. They learn from data, infer patterns, and produce outcomes that are not always deterministic. Two similar inputs can pro

🎉 Announcing Our User of the Month for March 2026: ​@nbargaje 🎉We’re delighted to recognize ​@nbargaje  as our User of the Month for March 2026! 🏆He has consistently gone above and beyond within our community; sharing exceptional insights, offering thoughtful solutions, and providing unwavering support to fellow members. His commitment to excellence is evident in every interaction, making a lasting impact on our knowledge base and helping countless users overcome challenges.🎁 As a Token of Appreciation, ​@nbargaje  Will Receive:A special gift box filled with exclusive goodies A User of the Month badge to proudly display on his profile 500 points added to his account A shareable certificate celebrating his achievement🌟 Why ​@nbargaje Stands Out:📝 Exceptional Contributions: He has authored some of our most informative and practical posts, offering valuable tips and guidance that benefit users at every level. 🤝 Community Spirit: Always ready to help, his positive and collaborative

Mobile automation is the ultimate pain point. I say this from experience. Unlike web testing, mobile forces you to juggle device fragmentation, OS-specific behaviors, and a limited set of reliable frameworks.Traditional mobile test automation often failed under the weight of unstable scripts, constant app changes, and endless maintenance cycles, especially if we had to cover cross-device compatibility as well. We spend more time in maintenance cycles (fixing invalid selectors and tweaking platform-specific gestures) than we do on actual feature coverage. The dream of a truly autonomous suite that reasons and adapts like a human tester has always been just that: a dream.That has changed. Standard tools like Copilots and Claude Code are great for writing snippets, but they aren't enough to solve the fundamental fragility of mobile E2E tests.My team decided to move beyond basic AI assistance and experiment with Agentic AI. We decided to build an autonomous agent capable of learning and ad

It was my first interview.I had worked for a company for 7 years. Then I decided to explore opportunities.I successfully cleared 2 rounds of technical interviews.The hiring manager appreciated my testing skills. We discussed automation frameworks. I could tell he made the decision to hire me. Great feeling!The manager asked me to wait in a discussion room.After a few minutes, the HR executive walked in.She asked a few questions related to my previous experience. She talked about the current salary package.Then she asked for an expected package.I was clueless. I did not think about it. I said ‘As per industry standard’.She said “yes”. Immediately. I was very happy. I accepted the offer. Joined the company.Three months later, I had a discussion over tea with my teammate. Same role, similar experience. His package was way higher than mine. The difference? He negotiated. I didn't.That tea tasted bitter.What's actually happeningNow I have 20 years of experience. I am a Test Manager. I have

Jan TegzeTell us how AI powers your testing. Share your story in the comments for a chance to win a prize!🏆 About Jan:I am a Talent Acquisition Leader with 20+ years of experience in recruitment and the author of the bestselling "Full Stack Recruiter." I am passionate about helping recruiters and job seekers understand how hiring really works. Through my books, newsletter, and content, I empower thousands of professionals to navigate the modern job market with confidence. In my free time, I love exploring AI and building new tools and workflows.