We are entering an era of unprecedented change in software quality practices. The continued rise of agile and DevOps are accelerating the pace of software delivery, driving the automation imperative and an increased need to focus on quality throughout the development lifecycle. Fortunately, we are an adaptable community, and our approaches to software practices are evolving quickly to respond to these challenges. We are building new skills. We are shifting left. And we are taking advantage of innovations in AI, low-code automation, and cloud computing to make testing automatic. In this session, we’ll use specific examples to illustrate how you can embrace innovation to respond to the disruptive forces in the software quality landscape. After that, with an eye toward the future, we’ll discuss how we can all prepare ourselves and our teams for the disruptions to come.
Quality Engineering Resources
The Scaling Crisis: How mabl's Agentic Testing Solves Open Source Shortfalls
Open Source is a great way to get your developers in on testing, but it has its limits at scale. Playwright test automation layered with mabl makes it easy.
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Rebuilding an AI Agent the Right Way: Measurement, Not Guesswork
Doing a ground-up rewrite nine months after a release isn't always a bad thing, especially when it's rooted in real-world data, as we discovered.
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When AI Writes the Code, Who Is Accountable for Quality?
AI tools like Claude Code + Playwright speed up testing, but are you building quality debt? The three risks engineering leaders need to understand now.
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