September 2026 Summaries

BrowserStack highlights João Proença, a Staff Quality Engineer, international speaker, and member of its Icons of Quality series, recognizing his contributions to software testing and community knowledge-sharing. Drawing on experience in quality engineering, development, support, and marketing, Proença applies systems thinking to solve software problems through technology, processes, or communication improvements. He identifies “Harness Engineering” as an emerging approach for establishing context and guardrails around generative AI in software development, while arguing that AI can generate test scenarios but cannot replace human risk-based judgment. Proença advises aspiring testers to understand risk before relying on tools, calls for universities to provide stronger testing and quality education, and stays informed through active participation in practitioner-focused testing conferences. Outside technology, he is also a singer-songwriter with an indie-rock project.

BrowserStack profiles Christine Pinto, a Berlin-based Staff Quality Assurance Engineer at EQS Group and experienced QA leader with more than 18 years in the field, highlighting her technical work, community leadership, and advocacy for a collaborative approach to quality. A former co-founder and CTPO of Epic Test Quest, where she helped develop the AI testing assistant Wizzo, Pinto also organizes the Ministry of Testing Berlin meetup, serves on the HUSTEF board, and participates in testing communities and events. She is particularly interested in agentic bug triage, which could analyze logs, compare prior incidents, and recommend severity levels to make initial assessments more consistent and free testers to focus on human-led investigation. Pinto argues that AI is unlikely to replace testers who exercise curiosity and judgment, but may displace repetitive checklist-based work. She advises early-career testers to become quality coaches who involve teams in asking better questions earlier rather than acting solely as final gatekeepers, and emphasizes that clear, empathetic communication is essential because identifying an issue is not enough unless others can engage with the feedback.

BrowserStack’s Icons of Quality profile highlights Huib Schoots, a Netherlands-based Sogeti consultant, coach, and one of four Rapid Software Testing instructors worldwide, whose work centers on improving software quality through connection, innovation, critical thinking, and candid communication. Schoots argues that testing is fundamentally a thinking activity rather than the execution of prescribed processes or test cases, with effective testers questioning assumptions, assessing risks, interpreting information, and helping teams make informed decisions. While he sees AI as a potentially useful accelerator for development and testing, he emphasizes that it cannot replace human judgment and advises practitioners to think and do initial work before seeking AI assistance. He encourages aspiring testers to prioritize curiosity, product and user understanding, mentorship, continuous learning, and engagement with the testing community through conferences, books, podcasts, and peer discussions. Outside technology, Schoots enjoys teaching, public speaking, brewing beer, board games, travel, photography, books, music, and singing in a band.

BrowserStack profiles Mark Hrynczak, Canva’s Head of Quality and QA Director, whose more than 20 years of experience in QA, SRE, and cloud operations includes scaling Canva’s quality function as its engineering organization grew from 300 to 3,000 employees and previously leading large AWS migrations at Atlassian. He describes Canva’s challenge of maintaining quality while serving over 200 million monthly users and deploying changes multiple times daily, emphasizing embedded, distributed ownership of quality that enables feature teams to ship confidently. Hrynczak sees AI-first and agentic testing as a major opportunity to delegate repetitive verification work to LLM-based tools, improve testing speed, support exploratory testing, and automate bug reproduction and analysis, while acknowledging risks associated with AI-generated code. He advises new testers to understand system design, the root causes of defects, and organizational ownership patterns rather than focusing solely on finding bugs, and stresses that automation is essential to modern engineering excellence. He stays informed through industry discussions, his team, community events, and Canva’s AI Discovery Week, while outside work he enjoys cooking under practical constraints.

BrowserStack highlights Pricilla Bilavendran as an Icon of Quality for her 15 years of QA expertise, leadership at Billennium, and contributions as a Postman Supernova, AWS Community Builder, WomenTech Network ambassador, mentor, speaker, and technical writer. Bilavendran describes quality engineering as understanding people, systems, and real-world technology behavior, and she is particularly interested in AI-assisted testing and Playwright. She argues that AI will not replace testers but can strengthen their ability to identify risks, challenge assumptions, and make quality decisions when combined with human curiosity, critical thinking, and appropriate governance. Her advice for new testers emphasizes learning how products and customers work, experimenting with tools, asking difficult questions, collaborating closely with developers, developing communication skills, and knowing when to say no. She maintains her expertise through hands-on experimentation, reading, writing, teaching, conferences, and community engagement, while valuing family time outside work.

BrowserStack’s Icons of Quality series recognizes Priyanka Halder, Associate Vice President of AI and Engineering at Deloitte, for her leadership in aligning technology strategy with major business outcomes and advancing AI, cloud-native modernization, and innovation across healthtech, fintech, and consumer technology. Halder emphasizes responsible AI as a promising way to address testing challenges and improve decision-making, while arguing that the greater challenge is not simply building AI solutions but ensuring they solve real business problems, scale effectively, and produce measurable returns. She advises new testing professionals to prioritize enduring, valuable skills over short-lived trends, learn from industry leaders and communities, and build their professional portfolios. Drawing on nearly two decades of experience, she highlights the often-overlooked importance of deciding when to buy existing tools versus build custom solutions, and she maintains her connection to Indian culture through semi-classical dance and cooking.

BrowserStack profiles Ash Winter, Senior Quality Engineer at the John Lewis Partnership, as a software-testing leader, coach, co-author of A Team Guide to Software Testability, and co-organiser of the Leeds Testing Atelier. Winter emphasizes that testing should remain a collaborative activity grounded in exploratory work, shared design discussions, and broad technical knowledge, while viewing AI and large language models as tools that can enhance rather than replace testers’ judgment. He advocates improving system testability so more team members can contribute, using coding assistants to rapidly prototype test environments and tooling, and applying AI specifically to surface information from logs, databases, queues, and system metrics. For new testers, he recommends learning API exploration, mocking, Git, and architecture review, while also consulting domain experts and avoiding isolated testing. He follows developments through testing communities and technology publications, and describes running as an important hobby that supports his wellbeing and time outdoors.

BrowserStack profiles Gaurav Singh, a Senior Software Engineer at Microsoft Teams Engineering Systems with more than 15 years of experience at organizations including Meta, CRED, and Gojek, recognizing his contributions to scalable test automation, developer productivity, and the testing community through his blog, videos, mentorship, and open-source courses. Singh describes his work supporting Teams application development for more than 300 million customers and emphasizes that effective quality engineering combines testing with infrastructure, engineering practices, and people-focused solutions. He is particularly focused on detecting and addressing flaky tests through scalable feedback systems, while also identifying predictive test selection, isolated test environments, performance testing, and security testing as important areas for innovation. Singh argues that AI should primarily help create smarter deterministic tests and infrastructure rather than replace reliable automated testing with nondeterministic agents, though he sees potential for AI in exploratory testing when paired with human evaluation. For early-career engineers, he recommends curiosity, continuous learning, broad technical exploration, automation and programming skills, and avoiding rigid role identities, while his own learning approach centers on solving meaningful problems, consuming diverse technical content, hands-on experimentation, teaching others, and maintaining personal notes.

BrowserStack profiles Jesper Ottosen, a test strategy advisor and Principal Cybersecurity Consultant at NNIT with more than 20 years of experience leading testing in large IT transformation, regulatory compliance, and security-focused programs. A longstanding Ministry of Testing contributor, author of three books, and prolific blogger, he emphasizes designing testing strategies around stakeholder needs, delivery cadence, and the underlying business “why” rather than applying every available test type or pursuing tools for their own sake. Ottosen highlights GRC engineering as a promising DevSecOps practice that automates verification of security and government-mandated requirements, and argues that AI will increase the need for critical thinking, validation, and evaluation even as it reduces manual test-case creation. He views testing primarily as a people-centered discipline shaped by stakeholder risk perceptions, collaboration, mentorship, and careful engagement with participants, while continuing to support emerging quality professionals through writing, speaking, and mentoring.

BrowserStack’s 11th AI x QA Leadership Summit will be held virtually and free of charge on September 23, 2026, from 8:30 to 11:30 PM IST, focusing on how quality engineering teams can adopt AI responsibly and effectively. Under the theme “Building the AI-Native QA Engine,” the event will offer separate tracks for QA leaders addressing AI strategy, governance, metrics, and oversight, and for practitioners developing AI-assisted testing skills through demonstrations and workshops. The summit will bring together QA leaders, engineers, AI specialists, and enterprise practitioners to discuss decisions around automation, human supervision, measuring AI’s impact, and changing QA roles, with the full speaker agenda to be announced.

BrowserStack’s Icons of Quality series recognizes Debbie O’Brien for her contributions to web development, testing, artificial intelligence, and developer education, including her advocacy for Playwright, Playwright MCP, and AI agents. A Google Developer Expert with experience in frontend architecture and technical program management at Microsoft, O’Brien emphasizes that AI is becoming essential to testing, particularly for helping verify work, generate effective tests, and improve testing agents over time. She advises new testers to develop broad AI proficiency alongside traditional testing skills, including learning how to direct agents and assess the quality of their output. O’Brien also uses AI bots to identify, summarize, and prioritize learning resources amid rapid technological change, while reflecting that AI reduces barriers for newcomers even though her own early career benefited from learning through difficult challenges. Outside technology, she values sports and cycling, describing time outdoors in Mallorca as beneficial for creativity and reflection.

BrowserStack profiles Keith Klain, Director of Quality Engineering at KPMG UK, as a software-quality leader specializing in AI assurance, quality engineering, and operational risk, with experience leading major testing transformations for organizations including Barclays and Citigroup. Klain describes his work on strategic enterprise, infrastructure, and merger-integration programs as centered on identifying risk and delivering timely, useful information, while emphasizing the value of collaboration with the global testing community. He argues that systems thinking, critical thinking, risk management, and the ability to translate technology risk into business terms are increasingly important, particularly as organizations assess AI-enabled systems for safety, reliability, fitness for purpose, and trustworthy evidence. Although skeptical of much of the current “AI in testing” activity, he expects the field to change rapidly and advises new testers to study the profession’s history and diverse approaches rather than rely solely on certifications or vendor promises. Klain also characterizes software quality and risk as fundamentally people problems requiring effective management and communication alongside technical skill, and notes his interest in learning French, spending time with his family, hiking, traveling, and attending concerts.

BrowserStack profiles Richard Bradshaw, known as FriendlyTester, a Senior Architect in Quality Engineering at Slalom Build and former CEO of the Ministry of Testing, recognizing his influence on software testing through community leadership, thought leadership, and advocacy for human-centered automation. Bradshaw views complex problem-solving as the core of engineering and considers AI agents both promising and challenging because their probabilistic behavior requires broader quality practices such as evaluations, telemetry, human review, statistical measures, and production feedback. He argues that AI will automate much routine testing work, but critical thinking, risk assessment, experimentation, and judgment will remain essential skills in increasingly hybrid engineering and quality roles. He advises newcomers to develop programming, architecture, observability, monitoring, and AI literacy while retaining curiosity and the ability to ask valuable questions. Bradshaw also emphasizes learning through hands-on experimentation and professional communities, describing testing primarily as gathering and validating information to support informed business decisions rather than simply finding bugs or accumulating automated checks.