Generative AI has made major leaps since we last explored its use in game QA, and this episode dives into how that progress is reshaping the field. Host Devin Becker is joined again by
Christoffer Holmgård and
Julian Togelius, co-founders of modl.ai, to unpack how recent advances in computer vision and agent behavior are enabling fully no-code QA testing workflows. We discuss the shift from traditional code-integrated systems to screen-seeing, input-driving AI agents, and the technical breakthroughs that finally made this approach viable. The conversation also explores the types of bugs and edge cases this new method catches, and the surprising ways it differs from prior tools.
The conversion also goes deeper into what this shift means for studios. Julian and Christoffer highlight how QA roles are evolving when testers can direct powerful AI agents without needing engineering resources. They also examine the line between automation and augmentation, arguing for the enduring value of human testers while outlining where AI can dramatically improve speed, coverage, and reporting. From auto-generating reproduction steps to fitting into broader ecosystems of AI coworkers, this episode offers a grounded, forward-looking take on how AI is transforming QA from the inside out.
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