Published on: October 7, 2024
In a recent interview with SafetyDetectives, Brad Tudor, Managing Director of BetterQA, shared insights into his 15+ years of experience in the QA industry and the founding of BetterQA. The conversation delved into the importance of long-term, dedicated QA teams, a principle that guides BetterQA’s mission to provide unbiased testing solutions. Tudor also highlighted the challenges of balancing rapid software development with thorough testing and discussed how AI and machine learning are reshaping the QA landscape. His emphasis on integrating QA early in the development lifecycle reflects BetterQA’s commitment to preventing costly errors and ensuring consistent software quality.
Can you tell us a little about your background and how you came to lead BetterQA?
I’ve been working in the QA industry for over 15 years now, starting my career with a large client in the U.S., and eventually leading a department of 20 QA engineers. BetterQA was born out of a need I identified during my previous roles: companies often overlooked the value of retaining long-term QA teams. Each project is unique, and having a consistent team throughout ensures the quality isn’t sacrificed due to shifting knowledge bases. It’s that philosophy that now drives BetterQA—offering dedicated, long-term QA solutions to our clients.
What inspired the creation of BetterQA, and what do you think sets it apart from other QA companies?
BetterQA was inspired by the desire to offer independent and unbiased testing services. We don’t offer development services on purpose—it allows us to remain objective when evaluating software quality. We don’t “shove bugs under the rug,” as you might say. Our team focuses on integrating deeply into our clients’ processes, ensuring we act as the crucial bridge between developers, product managers, and stakeholders to deliver a holistic approach to quality.
What do you believe is the biggest challenge companies face when it comes to software testing today?
One of the biggest challenges companies face today is balancing the speed of development with the need for thorough testing. The pressure to release new features quickly often leads to cutting corners on QA, which can result in costly post-release defects. It’s about striking that balance and ensuring QA remains a priority even when time is tight.
With the increasing speed of software development cycles, how can businesses balance the need for quick releases with thorough QA processes?
It’s all about embedding QA early in the development lifecycle. By getting involved from the start—during requirements analysis and initial design phases—we can help prevent defects before they occur. This proactive approach not only saves time in the long run but also ensures that testing isn’t seen as a last-minute hurdle, but as an ongoing process that supports faster, more reliable releases.
Can you speak to the role of AI and machine learning in the future of QA testing?
AI and machine learning are making waves in the QA industry. At BetterQA, we’re starting to integrate AI-driven tools to optimize test case generation and test data management. These technologies are especially helpful in regression testing and can reduce the amount of manual work required, freeing up our team to focus on more complex and exploratory testing activities.
What are some common mistakes companies make in their QA processes that lead to costly errors down the line?
One of the most common mistakes we see is companies delaying QA until the final stages of development. This leads to defects being found late in the process when they are most expensive to fix. Another issue is not having a solid process in place for continuous testing. Testing should be integrated throughout the development lifecycle, not just at the end. Companies also underestimate the value of thorough requirements reviews and early defect prevention.