Software Testing Unleashed - QA, DevEx & Quality Engineering

By Richard Seidl | Software Development & Testing ExpertBusiness Technology Education Management

Software Testing Unleashed - QA, DevEx & Quality Engineering episodes

October 01On-Site Testing Conferences: Why Networking Needs Presence - Okan Çakmak
How a risky one-time event in Istanbul grew into a conference that connects Europe and Asia
What does it take to turn a risky one-time event into a conference that testers travel across borders for? With Okan Çakmak I talk about how the Istanbul Software Testing Conference grew out of something missing: after the pandemic, the big Turkish testing events stayed online, and people lost the chance to meet, network and hug each other in person. He tells me how the team wondered whether 50 or 100 people would come, then welcomed 200, and how the "light in their eyes" of those first participants convinced them to keep going.
"Our main motivation is to see people with the light in their eyes when they leave here." - Okan Çakmak
Okan Çakmak is the founder and principal consultant of Padran Information Technologies and a co-founder of the Istanbul Software Testing Conference (ISTC). Based in Istanbul, he has more than 23 years of experience in software testing and quality engineering. He has helped organizations across Europe and the Middle East improve their test processes, test automation, performance testing, and service virtualization, particularly in telecommunications and financial services. As an ISTQB instructor, he enjoys sharing practical knowledge with testing professionals. Through ISTC, he helps connect the international testing community with practitioners in Türkiye. Outside work, he plays the clarinet.
Highlights:
The Istanbul Software Testing Conference started because Turkey's main testing events stayed online after the pandemic, leaving testers without a physical place to network and exchange ideas.
International participants made up 20 percent of the 2026 audience, and that share has grown with each edition since the first year drew 200 attendees.
Six program committee members reviewed every one of the more than 120 submissions for the third edition, a workload Okan Çakmak expects to outgrow as international submissions rise.
The conference will return from three parallel tracks to two, because participants reported that choosing between three sessions at once was too difficult.
Simultaneous translation runs in every track all day, so speakers can present in Turkish or English and no participant feels excluded by language.
More Links with Insights:
Padran Information Technologies
Istanbul Software Testing Conference (ISTC)
📘 Tool migration ahead? Teamscale playbook: migrate only 20% of tests, keep nearly all bug detection. Download for free
18 min
September 24You Need a Test Automation Strategy Before AI - Michaël Pilaeten
When AI removes your asserts and the pipeline stays green
What happens when AI ships poor quality faster, and nobody notices because the pipeline stays green? With Michaël Pilaeten I talk about why test automation without a clear strategy is a problem that AI only accelerates, not solves. We get into the question of what separates a tester from a test automation engineer, why those two roles need each other but are not interchangeable, and how chasing 100% coverage on millions of lines of legacy code can be a waste everyone agrees to quietly.
"An automated test rarely finds defects." - Michaël Pilaeten
Michaël Pilaeten is Head of Quality Engineering at SOFICO. He is an accredited trainer for various ISTQB and IREB courses, as well as an author, international keynote speaker and workshop facilitator.
Breaking the system, helping to rebuild it and giving advice on how to avoid problems in the first place: that sums up his work. With more than 20 years of experience in software consultancy across a wide range of environments, he has seen the best (and the worst) of software development. Today he guides consultants, partners and customers on their personal and professional path towards excellence.
Highlights:
Testers and test automation engineers are two distinct roles: testers explore and break products critically, while automation engineers translate requirements into automated cases, and conflating them weakens both.
AI-generated tests default to quantity over correctness, producing plausible-looking test cases with invented scenarios just to hit coverage targets, not because the scenarios are valid.
Automated tests rarely find defects; when a pipeline fails, teams blame the test rather than the code, which means real bugs hide behind green dashboards.
Replacing junior testers and developers with AI removes the learning path that produces senior engineers, creating a skills gap with no pipeline to fill it.
Convincing management to invest in test quality requires framing the argument around production incidents and customer risk, not coverage metrics they do not understand.
📘 Tool migration ahead? Teamscale playbook: migrate only 20% of tests, keep nearly all bug detection. Download for free
23 min
September 17Agentic Systems in Testing: Why Humans Stay in the Loop - Nishan Portoyan
Nishan Portoyan on why 8 to 12 agents replace your entire test workflow
What separates a handful of agents from a real agentic system? With Nishan Portoyan I talk about exactly that line, and why most teams are still on the wrong side of it. We walk through a full testing pipeline where eight to twelve agents handle everything from requirement review to performance test conversion, and I keep coming back to the question of where the human has to step in and why the AI simply cannot replace that judgment. Nishan is direct about what these systems cannot do: they do not think, they gather information and hand it back, and anyone expecting otherwise will run into trouble fast.
"There is no intelligence in there. It's just gathering information and handing it over to you." - Nishan Portoyan
Nishan Portoyan is a tester with a passion for his work. Whether it’s planning, coordination, automation, or execution, there’s no area of testing he doesn’t enjoy. Thanks to his solid training as a computer scientist and his degree in business administration, Nishan knows how to act professionally as a bridge between computer science and business.
True to his motto, “If you love what you do, do it all the way or not at all,” he is deeply committed to the testing community in addition to his projects.
Highlights:
An agentic system is not a collection of individual agents given tasks by humans, but a goal-based ecosystem where agents orchestrate other agents autonomously.
Between 8 and 12 specialized agents can cover the full testing process, from requirement review through test case creation, automation, and performance testing.
AI cannot apply business rules or judge coverage the way humans do, so human oversight is not optional but structurally required at defined checkpoints throughout the agentic system.
Performance test cases cannot be reused from functional automation because the scope differs fundamentally: functional tests control a GUI like a human, while performance tests examine back-and-forth system communication at scale.
In data-protection-strict environments such as Switzerland, cloud-based AI tools like ChatGPT, Claude, and Gemini are not viable, and teams must run models such as Mistral or DeepSeek locally, for example via Ollama, on GPU-capable servers.
📘 Tool migration ahead? Teamscale playbook: migrate only 20% of tests, keep nearly all bug detection. Download for free
29 min
September 10AI in Software Testing Raises the Value of Expert Testers - Olivier Denoo
Why expert testers will be needed more as AI writes more code
What happens to quality when anyone can generate code with a prompt but nobody checks whether it actually works? With Olivier Denoo I talk about why that question puts expert testers in a stronger position than many managers currently assume. We get into the real risk of AI that always sounds right, the edge cases a lost suitcase in Brussels reveals, and why the hardest unsolved problem in testing is still the same one Olivier ran into three decades ago: describing precisely what you want. The skills I keep coming back to in this conversation are business understanding, communication, and the ability to spot what the AI confidently got wrong.
"AI can do most of the parts of the testing process." - Olivier Denoo
Olivier Denoo has been, From May 2019 to April 2023, the president of the ISTQB and is now currently the Vice President of the ISTQB.
Olivier is also the President of the CFTL - the French ISTQB Board and official IREB, IQBBA and TMMi representative in France.
The CFTL is organizing the largest software testing conference in Europe (JFTL) with more than 1200 attendees.
He is also the Vice President of ps_testware SAS, the French subsidiary of the ps_testware group. His role is to develop business, recruit the local expert team, build sustainable partnerships, promote software testing and quality.
He is also involved in auditing test projects and organizations and provides high-level consultancy and support.
For nearly 30 years he is an international speaker who spoke at A4Q World Conference, Geekle QA, iSQE, Test-IT Africa; SQA-days; BA-days; JFIE; TestWarez; SEETEST; STF; Iqnite; JFTL; JMTL; JTTL; Analyst-days; Quality Week; Eurostar; Dasia…
He's also actively participating in the development of new certification schemes, like IQBBA (Business Analysis) or IREB (requirements engineering) and is co author of various books and articles on software testing
Highlights:
AI-generated output is correct often enough to look trustworthy, but the remaining faulty fraction, hallucinated references, invented requirements, fabricated test cases, causes real business damage if no human checks the result.
A tester who only runs pre-written scripts without understanding the underlying business is directly replaceable by AI; domain knowledge is what makes a tester hard to automate away.
Prompt engineering and requirements engineering are now core tester skills, because the fundamental problem of describing software behavior precisely and unambiguously has not changed in 30 years of the profession.
Communication skills are a critical gap in tester education: presenting data honestly, managing stakeholder expectations, and writing clear prompts all depend on abilities that engineering curricula do not teach.
More Links with Insights:
Oliviers Website
📘 Tool migration ahead? Teamscale playbook: migrate only 20% of tests, keep nearly all bug detection. Download for free
22 min
September 03Lean Management: Why Problem Analysis Beats Quick Fixes - Nirmala Saneechur
How spending more time on a problem means solving it fewer times
Why do we rush to fix problems before we actually understand them? With Nirmala Saneechur I talk about Lean management, what it means to deliver quality at the right time rather than just on time, and why spending a full day understanding a problem is not wasted time. We get into what waste really means in a software project, including the story of 15 features a client never used, and how working in silos creates the kind of back-and-forth that slows everything down.
"Waste is anything that does not bring value to the customer." - Nirmala Saneechur
Nirmala Saneechur is an experienced Test Manager based in Mauritius, with a strong background in software quality assurance and delivery. She specializes in defining testing strategies, leading high-performing teams, and ensuring quality across complex IT projects. Nirmala is the Secretary of the Mauritian Software Testing Qualifications Board (MSTQB), where she actively contributes to advancing the testing profession. She is also an engaged community member, playing a key role in organizing TestCon. A recognized local and international speaker, Nirmala has presented at DevCon, TestCon, and the A4Q Testing Summit, delivering sessions in both English and French. She holds a Green Belt in Lean Management, reflecting her commitment to efficiency and continuous improvement. Known for her collaborative leadership style and passion for quality, Nirmala is dedicated to strengthening testing practices and supporting the growth of the software testing community.
Highlights:
Rushing to a solution before understanding a problem means the same problem returns: time spent on root cause analysis eliminates recurrence, which spending time on a quick fix never does.
Waste in software projects is anything that delivers no value to the customer, including features built on time but never used by the people they were built for.
Lean is not a methodology layered onto agile, it is a mentality that runs underneath any working method, applicable to processes, tools, and daily habits alike.
Management buy-in is a prerequisite for sustained lean adoption: without it, the time required to understand problems gets cut before the mindset has a chance to take hold.
More Links with Insights:
Facebook
📘 Tool migration ahead? Teamscale playbook: migrate only 20% of tests, keep nearly all bug detection. Download for free
22 min
August 27Performance Monitoring: Set a 70% CPU Alert Before Failure - Rao Dhaligadoo
Slow systems bleed money before they ever crash
Slow systems don't just annoy users, they cost companies real money, and most teams only find out when the phone starts ringing. With Rao Dhaligadoo I talk about what it actually takes to catch performance problems before customers do. We get into how a 70 percent CPU threshold can trigger an automated chain of monitoring, ticket creation, and root cause analysis, and why that matters more than it sounds. Rao also shares what it feels like to spend 45 hours in a war room at a bank, watching a CIO walk in at 1 a.m. while the whole team sits in silence, and how that experience shaped the way he thinks about proactive testing.
"In a perfect world, they never see the loading spinner or the 404." - Rao Dhaligadoo
Vasudev Rao Dhaligadoo is a Quality Engineering Lead with over 10 years of experience driving test management, automation strategy, and QA capability across enterprise systems in banking, payroll, and large-scale platforms. He has led end-to-end testing initiatives, built scalable automation frameworks, and integrated quality practices into CI/CD pipelines to improve release confidence and delivery speed.
He is also a QA and Test Automation trainer, regularly mentoring engineers and delivering hands-on training on modern testing tools and practices. Passionate about advancing quality engineering, he focuses on combining test management, observability, automation, and AI-assisted insights to diagnose complex system issues and strengthen software reliability.
Highlights:
A 70% CPU or resource threshold triggers automated alerts before systems degrade to failure, keeping end users away from slowdowns and 404 errors entirely.
Slow systems cost real money even without full outages: a combined YouTube and Azure slowdown incident cost more than 70 million US dollars.
AI-powered monitoring tools like Datadog's Bits AI pinpoint the exact database query or API endpoint causing a performance issue, cutting analysis time from hours to minutes.
Database query optimization and load balancer configuration under high traffic are the most common root causes of production performance problems, based on Rao Dhaligadoo's field experience.
Reactive incident response without proactive monitoring forces teams into war-room situations, with one real case stretching to 45 hours before production was restored.
📘 Tool migration ahead? Teamscale playbook: migrate only 20% of tests, keep nearly all bug detection. Download for free
18 min
August 20End-to-End Test Automation Without the Maintenance Trap - Lilia Gargouri
Why 15 test cases can cover more ground than 500 ever will
Forty percent of automation time lost to flakiness and maintenance: that is the reality Lilia Gargouri describes. I talked with Lilia about end-to-end test automation at scale, and what struck me most was how far back the real solutions reach: a single HTML attribute added in 2017 still pays dividends today, simply because the team decided to use it consistently and never change it. We get into the full picture, from how to accurately identify every UI element without XPath gymnastics, to why fifteen well-chosen test cases can outperform five hundred noisy ones, to naming conventions and layered library architecture that keep maintenance from spiraling. And for anyone sitting on an old, flaky test suite right now, Lilia has a concrete answer for where to start.
"Test automation is software development. It's a software project within the big one." - Lilia Gargouri
Lilia Gargouri is known for sustainable, scalable, and efficient quality assurance in complex e-government projects. She is committed to accessibility, trains career changers, and is a passionate advocate for greater visibility and equal opportunities for women in IT. As the inventor of a model-based low-code tool for test automation, she has significantly simplified and accelerated quality assurance in critical e-government projects. As a member of the German Testing Board, she actively drives the further development of quality standards in the industry.
Highlights:
A custom HTML attribute added solely for end to end test automation, introduced in 2017, still delivers stable, flakiness-resistant element identification years later across a large government application portfolio.
Scoping the DOM so that only the relevant section exists for the test tool removes ambiguity when identical elements appear in multiple sections, making precise targeting possible without complex selectors.
Fifteen well-chosen test cases covering the most critical scenarios deliver more sustainable value than five hundred loosely defined ones dragging down execution time and maintenance capacity.
Sleep-time workarounds accumulate silently: one analyzed project lost two hours per test run to individually small hardcoded waits, a cost eliminated only by building a proper application-busy detector.
Naming every automation procedure as action plus business label (for example, "enter name") means a new team member can read the test code and navigate the application logic without separate documentation.
📘 Tool migration ahead? Teamscale playbook: migrate only 20% of tests, keep nearly all bug detection. Download for free
34 min
August 13API Testing: Agent-Optimized Design Cuts Token Costs - Sebastian Małyska
When end-to-end automation is the answer and when it is the wrong question
With Sebastian Malyska I talk about what sits behind the APIs testers often take for granted. We get into why REST is still on top but not the whole story, how GraphQL and webhooks fit into the picture, and what actually happens when an AI agent talks to a real system through MCP. There is a practical argument running through all of it: if you understand the protocol layer, you can make smarter decisions about where to test, how to structure automation, and how to avoid burning unnecessary tokens and budget. Sebastian also makes the case that front-end testers are already closer to this world than they think, and that the next step in the career is simply to look one layer down.
"Improving is not like giving you know golden card to AWS, give me more resources. But this is the hard way, this is engineering way." - Sebastian Małyska
Sebastian Małyska is a software quality enthusiast with over 20 years of experience proving that “it works on my machine” is not a testing strategy. Has worked as a manual tester, automation engineer, QA Lead, and QA Manager, basically wherever quality (or patience) was missing. Speaker at national and international conferences and a program committee member who enjoys talking about QA almost as much as reporting other people’s bugs. Codes mainly in Python, because life is too short for bad code and even worse languages. President of the Polish Quality Board, Secretary of the ISTQB® Board, member of the IREB® community, and co-founder of ŁuczniczQA in Bydgoszcz. On a daily basis, fights for better quality, fewer critical defects, and more common sense in IT projects.
Highlights:
APIs optimized for agent use require fewer requests to retrieve the same data, which directly reduces token consumption and lowers operational costs.
REST is a set of recommendations, not a strict protocol, so teams can and do deviate from its conventions without violating a formal standard.
MCP works by having the MCP server send a description of its available tools and resources to the LLM at the start of a session, which is how the model learns what actions it can call.
API-level tests offer greater stability and faster execution than end-to-end browser tests, and the right testing strategy names the layer where each scenario is best covered rather than defaulting to front-end automation.
Starting API test design from documentation such as a Swagger spec, before the front end exists, removes the wait time at the end of the development cycle and eliminates idle waste.
📘 Tool migration ahead? Teamscale playbook: migrate only 20% of tests, keep nearly all bug detection. Download for free
35 min
August 06LLMs in Software Testing: Start with Small, Bounded Tasks - Klaudia Dussa-Zieger
Not every testing problem needs AI, and knowing the difference matters
With Klaudia Dussa Zieger I talk about where language models actually deliver in testing and where they fall flat. We get into the concrete details: why a small function like generating keyword documentation works so well with a standard chat model, why reviews only started working once they switched to a reasoning model, and why one engineer working on embedded legacy code said no to AI help without hesitation. Klaudia also shares the translation use case I found most vivid, turning a cryptic technical defect message into something a domain tester can actually read.
"The more autonomy you give to an AI agent, the better it has to be." - Klaudia Dussa Zieger
Klaudia Dussa Zieger has been working in the field of software testing and quality assurance for more than 25 years. She is the team leader responsible for consulting at imbus AG. She is particularly interested in test management, the continuous improvement of the test process and the professional training and further education of testers and has been a trainer for the ISTQB Certified Tester Foundation and Advanced Level as well as a lecturer for software testing at the University of Erlangen-Nuremberg for more than 20 years. Since March 2009, Klaudia has been chairwoman of the DIN working committee on systems and software engineering and is actively involved in the development of standards at international level.
Highlights:
Reasoning models outperform standard chat models for code review tasks: switching from GPT-4o to O1 was what made automated keyword review produce usable results.
Small, tightly scoped AI functions deliver faster adoption than large end-to-end automation, because testers can verify the output and stay in control of the process.
Self-healing test automation that uses embeddings to repair broken locators risks masking real defects, because the system cannot distinguish an accidental change from an intentional one.
As AI agents gain autonomy and operate without a human between each step, the quality requirements for their output rise sharply, which closes the gap between using AI and testing AI.
📘 Tool migration ahead? Teamscale playbook: migrate only 20% of tests, keep nearly all bug detection. Download for free
27 min
July 30Testing Complex Systems: Ship Small and Learn Fast - Jean Francois Riverin
A tester on why predicting production failures is impossible
With Jean-Francois Riverin I get into a question that bothered him for over 20 years: why are there still bugs in production even when you tested as well as you possibly could? His answer is that software stopped being a complicated problem, like building a bridge, a long time ago. It is now complex, more like medicine or meteorology, and that means the whole idea of finding the right answer through testing is the wrong goal. We talk about what it looks like to switch that mindset, what "safe to fail" means in practice, and how to make that argument to a manager who still expects predictable budgets and zero surprises on Friday afternoons.
"Testing is not about preventing errors anymore in the complex world is to learn about what is working and what is not working." - Jean-Francois Riverin
Jean-François Riverin is the Co-Founder and CEO of Zentelia, a Canadian consulting and training firm specializing in software quality, testing, quality engineering, and continuous improvement.
With more than 25 years of experience in information technology, he helps organizations improve the way they build, test, and deliver software in complex and rapidly evolving environments. His work focuses on aligning quality practices with business objectives, enabling teams to make better decisions through meaningful metrics, pragmatic processes, and collaboration.
Jean-François is an active contributor to the international software testing community. He serves on the Board of Directors of the Canadian Software Testing Board (CSTB), where he leads initiatives related to volunteering and technical excellence. He also contributes to the evolution of software testing certifications and is currently involved in the working group developing the next generation of the ISTQB® Certified Tester Foundation Level syllabus.
A frequent speaker, trainer, and facilitator, Jean-François regularly shares practical insights on software quality, testing, metrics, DevOps, and organizational transformation. He is passionate about helping organizations move beyond compliance and control toward a vision of quality as a strategic capability that supports innovation, informed decision-making, and sustainable business performance.
Highlights:
Software is not a complicated system like a bridge; it is a complex one, meaning outcomes are unpredictable and only observable after the fact, not calculated in advance.
Blaming testers for production failures misunderstands the nature of complex systems, where exhaustive pre-release prediction is structurally impossible, not a skill gap.
Testing in a complex environment is a learning activity: deploying small changes frequently generates knowledge about what works, rather than confirming a known correct answer.
Safe-to-fail experiments, feedback loops, and monitoring metrics replace the engineering goal of finding one right solution with continuous adaptation based on real production data.
📘 Tool migration ahead? Teamscale playbook: migrate only 20% of tests, keep nearly all bug detection. Download for free
21 min

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Software Testing Unleashed - QA, DevEx & Quality Engineering

Software Testing Unleashed - QA, DevEx & Quality Engineering episodes

About Software Testing Unleashed - QA, DevEx & Quality Engineering