In this Building Better Foundations episode, hosts Rob Broadhead and Michael Meloche continue their conversation with Greg Lind, founder of Buildly and OpenBuild. They explore how automating quality in software development changes the way teams build and test software. Greg explains that AI and automation can improve collaboration and prevent errors before they happen. As a result, teams can deliver code faster, maintain consistency, and build stronger foundations for long-term success.
Greg’s experience across startups and open-source projects has shown him one simple truth: quality can’t be bolted on at the end—it must be built into the process from the start.
“QA often gets left until the end. But it has to start from the developer.” — Greg Lind
About the Guest — Greg Lind
Gregory Lind is an American software developer, author, and entrepreneur with over 20 years of experience in open-source innovation, software efficiency, and team transparency. He’s the founder of Buildly in Brooklyn and co-founder of Humanitec in Berlin, helping organizations modernize systems through collaboration and automation. A frequent speaker at Open Gov and Open Source conferences, Greg advocates for open, scalable solutions and smarter software processes. His upcoming book, “Radical Therapy for Software Teams” (Apress, 2024), explores how transparency and AI can transform how teams build software.
Automating Quality Starts with Developers
Greg explains that every developer should think like a QA engineer. Testing isn’t something done after code is written—it’s something built into how code is written.
He stresses that developers should write unit tests early and often, focusing on verifying object-level functionality rather than simply checking UI forms or user flows. QA should then expand from there, building additional layers of testing as complexity grows.
“I learned that I need to think like a QA person from the very beginning.” — Greg Lind
By shifting QA upstream, teams reduce rework, accelerate release cycles, and improve code confidence.
Automating Quality in Software Development Across the Pipeline
At Buildly, Greg and his team integrate testing automation into every stage of the development pipeline. Tools like Robot Framework and Selenium handle both front-end and API-level testing, while Git pre-commit hooks ensure tests are written before code even reaches the repository.
“You have to make sure those tests have already been written. If there isn’t a test, it pulls it back and says, ‘make sure that you have your test in before you check it in.’” — Greg Lind
This system ensures that developers can’t skip testing—and that QA has visibility into every build. It’s a workflow that blends accountability with automation, reinforcing a culture where quality is everyone’s job.
AI’s Role in Continuous Improvement
Greg sees AI as a critical ally in maintaining software quality at scale. Rather than replacing QA engineers, AI helps automate the tedious parts of the process—like generating basic test cases, reviewing commits, or spotting missing standards in pull requests.
“I don’t mean to put that out there as a replacement for QA in any way. Developers need to be in the process, and QA are developers as well.” — Greg Lind
AI’s ability to analyze large volumes of commit history and testing data helps teams identify trends, recurring issues, and areas for improvement. This frees human testers to focus on strategic validation, exploratory testing, and creative problem-solving.
Transparency, Collaboration, and Learning
Another major theme Greg highlights is transparency. Buildly’s AI-driven summaries and automated reports make quality metrics visible to everyone on the team—developers, product managers, and QA alike.
“It’s not about who wrote the bad test—it’s a learning process. Every pull request is an opportunity to make the code better.” — Greg Lind
This openness removes blame from the process and instead encourages collaboration and improvement. Code reviews become opportunities to mentor, learn, and evolve—not just check boxes.
Evolving Agile for the AI Era
As Rob and Michael point out, Agile principles still apply—but the implementation must evolve. Traditional sprint structures don’t always fit AI-accelerated environments. Greg agrees, noting that the key is flexibility: adapt the process, automate what you can, and always look for ways to improve.
“You don’t have to be a slave to what you think the process is. Agile literally tells you—adjust it as your team and your project evolve.” — Rob Broadhead
Automation and AI are simply the latest tools in that evolution—helping teams move faster, collaborate better, and keep quality at the core of every release.
Final Thoughts on Automating Quality in Software Development
Greg Lind’s insights in this episode reinforce a powerful truth: automating quality isn’t about replacing people—it’s about empowering them.
When developers, QA, and AI systems work together, software development becomes a continuous cycle of improvement, learning, and trust. As teams embrace automation and transparency, they don’t just ship faster—they build stronger, smarter, and more sustainable software foundations.
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