Interview with Mike Urbanovich, Head of Testing Department - a1qa

Mike Urbanovich  

Head of Testing Department, a1qa

Can you share your journey with a1qa and what inspired you to specialize in software testing and quality assurance?

I embarked on my QA journey when I was 20 years old, while studying in my third year at university. At that point, I was eager to work on real projects and grow by learning from professionals. I was actively studying programming, but a friend of mine had already been working at a1qa for over a year and recommended me to the company. That’s how my long journey began, filled with the excitement of training, the challenges of my first project, and the experience of my first serious client interview.

Over the following five years, I built expertise across multiple engineering roles — functional, penetration, performance, and test automation expert. Later, I had the amazing opportunity to lead a performance testing team. As it grew, we expanded into test automation as well.

For the past five years, I’ve been working as the head of a large and truly remarkable team of 200+ QA professionals, where we focus on the technical service areas of a1qa.

Looking back, which project or achievement has been the most defining moment for a1qa’s growth in the QA industry, and why?

I see two key aspects here. The first is the growth of our clients: we started working with some of them when they were still small companies, and over time we progressed together, building long-lasting and trusted partnerships. The second is that we began launching new projects on a much larger scale, with dozens of engineers involved right from the start.

At the heart of it all lies one principle: the client’s interests always come first. As professionals, we are ready to adapt with flexibility while consistently maintaining the highest standards of expertise.

What is your approach to structuring software testing strategies that balance speed, cost-efficiency, and uncompromised product quality?

Based on my experience, the key is first to define the priorities, because the focus and trade-offs will always align with what matters most to the client. For example: how much faster do we truly need to become in terms of time to market? After a certain threshold, achieving additional speed often requires significant budget investments.
At the same time, we aim to deliver cost-efficient services, such as designing highly stable, custom-built test automation frameworks that are carefully tailored to the client’s products. This approach enables rapid execution with broad coverage and strong reliability, though it naturally requires investment in both development and maintenance.
Finally, before shaping a testing strategy, it’s critical to agree on clear and measurable indicators of success, such as regression execution speed, test automation ROI, test coverage, stability of automated tests, and defect escape rate.

How do you help clients select the right testing tools, frameworks, and methodologies to match their unique business and technical needs?

We are highly flexible in our approach. On the one hand, we can work with our own established technology stacks.For example, in test automation we cover all major programming languages and the top five frameworks. On the other hand, when it comes to recommending a solution for a specific client, we consider the technology stack already leveraged by their engineering teams. This way, they can easily navigate and adopt the solution should the need arise.

When it comes to test tracking utilities, we have a broad toolkit at our disposal and can work seamlessly with both our own tools and those provided by the client. We also have extensive experience leveraging open-source solutions, which bring clear advantages: transparency, freedom from vendor lock-in, and significant cost savings.

In your experience, what are the most critical factors for businesses to achieve sustainable growth through strong QA practices?

I think sustainable growth through strong QA practices relies on several critical factors. First, there must be stable processes and a professional strategy that channels the team’s energy toward achieving business objectives. A clear pre-release quality gateway is essential, consisting at minimum of thorough new feature testing and solid regression coverage.

It’s also crucial that QA specialists are fully integrated into the broader goals of the project or product. QA teams should have the authority to influence release decisions and be embedded into the core logic of how the business and product operate. They should also be empowered to share their hypotheses and insights.
Ultimately, testers are the very first users of a product. Yes, they approach it with a bias toward breaking things and uncovering flaws, but at the same time, they are uniquely positioned to answer a fundamental question: how intuitive and convenient is the product for end users?

From Agile to DevOps to Continuous Testing — which methodology do you find most effective in delivering consistent, reliable results, and why?

To my mind, the best results are achieved through a DevOps approach combined with continuous testing. Agile methodology provides rhythm and flexibility, but without end-to-end automation, quality remains inconsistent. DevOps bridges development and operations, automating builds, deployments, and infrastructure, while continuous testing ensures early risk assessment with every change.

This approach accelerates feedback, increases coverage, reduces manual errors, and shortens rollback time. Practices such as shift-left testing, treating tests as code, CI/CD pipelines, containerization, and observability create repeatable and verifiable software delivery processes. Regular metrics, experiments, and post-mortems help embed continuous improvement.

This methodology scales effectively, reduces technical debt, enhances transparency, and lowers the cost of defects in the production environment as teams grow.

Could you share examples of how a1qa’s QA services have helped clients reduce risks, cut costs, or accelerate time-to-market?

We absolutely have plenty of examples where a1qa’s QA services have helped clients reduce risks, cut costs, and accelerate time-to-market. Just off the top of my head, I can recall a case where a large eCommerce product we worked on had a time-to-market of 1.5 months from the product owner’s request to implementation and A/B testing. A detailed analysis revealed that approximately 45% of this time was consumed by testing. The QA process relied on an extensive test model that had grown arbitrarily over the years, duplicating functionality and significantly reducing testing efficiency. Additionally, the build process depended heavily on developers, often delaying delivery to the test environment.

We were able to restructure this workflow by implementing CI/CD practices and redesigning the test model. This allowed us to reduce the number of tests and steps while increasing coverage by filling gaps that had previously been overlooked. As a result, regression testing time dropped to 0–10%, depending on the scale of changes and timing of updates to the test environment.

This improvement not only accelerated testing but also sped up development itself, as builds no longer required manual effort from developers. The cycle “update → retest → update” became much shorter, ultimately allowing the product to reach the market 2.5 times faster.

I also make it a point to share such experiences with my colleagues, and I gain valuable insights from them in return. It’s truly rewarding to see how, thanks to our internal Centers of Excellence and strong knowledge-sharing culture, these successful outcomes are consistently replicated across projects. That kind of continuity speaks volumes about the professionalism and maturity of our QA practice.

Which emerging testing technologies (e.g., AI-driven testing, automation, performance engineering) do you see as the most transformative for the QA industry?

Spec-driven development for test automation seems to me to be one of the most promising areas. In this approach, AI coding agents such as Code Claude or Warp handle the actual writing of test code, while the automation engineer focuses on setting up environments, developing specifications, defining rules for test creation, and managing the overall process. The AI agents generate code across multiple streams at incredible speed and can even maintain the automated tests continuously. 
This model has the potential to accelerate test development, improve consistency, and free human engineers to focus on higher-level design and strategic work rather than repetitive coding tasks.

How do you foresee AI shaping the future of software testing, and which industries do you think will benefit the most from AI-powered QA?

The real advantage will be achieved by those who adopt AI in testing processes early, following a strategy  that combines strong oversight with targeted use of AI in areas where the current technology delivers the highest value, namely code development. Beyond automated tests, this also enables broader coverage through unit testing, as well as more active use of modular and integration testing (not only end-to-end). This leads to earlier detection of issues and, consequently, lower fixing costs.

This becomes especially impactful when the development process itself also leverages spec-driven practices, where every code increment is automatically tested by an AI agent through the use and continuous improvement of tests.

What key goals and initiatives does a1qa have for the coming year to further strengthen its position as a global QA leader?

Our primary focus is on distributing talent worldwide to meet client needs with teams operating within the same time zones. We also invest heavily in developing internal technologies and practices that keep us at the forefront of modern testing approaches, with a particular emphasis on leveraging LLMs.