AI is transforming the way product teams approach customer research—but what should remain human, and what can be handed off to AI agents?
In this episode, Marc and Ben sit down with Aaron Cannon, co-founder of Outset, to explore the evolving role of AI in discovery and usability testing. Aaron unpacks how AI-moderated research enables unprecedented speed and scale while preserving depth, why intuition remains critical for building great products, and how research teams can shift from execution to framing the right questions and telling better stories. The conversation also dives into the future of PM and UXR roles, collective intuition at companies, and the career paths that might emerge as AI takes on more “entry-level” tasks.
Whether you’re a PM, designer, or researcher wondering how to integrate AI without losing the magic of human insight, this episode offers practical frameworks and a forward-looking perspective on what’s next.
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In this episode, we covered the following topics:
(02:05) Why Aaron started Outset—and the research tradeoff between speed, scale, and depth
(03:28) Two kinds of research: human-led improvisation vs. AI-led repeatable studies
(07:34) How Outset keeps AI on-track with guardrails while still enabling deep exploration
(12:14) The rise of iterative qualitative research—and how teams are testing and learning faster than ever
(15:30) Why faster tools don’t mean you should ship more—just that you need stronger product judgment
(19:13) How to structure product experiments as hypotheses to sharpen team intuition
(29:40) The emerging role of UXR: from execution to storytelling, diplomacy, and company-wide insight building
(42:46) What AI means for early-career UXR and PM roles—and how career ladders are being rewritten
And more!
Links:
Aaron Cannon: https://www.linkedin.com/in/a-a-ron-cannon/
Outset: https://outset.ai/
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