Risk-Based Product Design: Avoiding the Cost of Hidden Assumptions
Raelin Sawka Musuraca, Master of Human-Computer Interaction Program, Carnegie Mellon University
kHUB post date: July 14, 2026
Originally presented: July 2, 2026
Watch time: 60 minutes
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Most product teams follow the right process—and still build the wrong thing. The issue isn’t execution; it’s untested assumptions.
In this webcast, Raelin Sawka Musuraca introduces a risk-based approach to product design that helps teams identify and test the beliefs driving their decisions before committing time and resources. Centered on Assumption Artifacts, a lightweight tool for running fast, behavior-focused experiments, the session highlights how generative AI can be used to surface hidden assumptions, reveal overlooked product risks, and rapidly create and iterate on low-effort tests. Attendees will gain a practical lens for reducing hidden risk, improving prioritization, and making more confident product decisions.
Key Takeaways:
- How to identify hidden assumptions that drive product decisions—and why they are often the greatest source of risk
- A practical method for prioritizing product risk, shifting focus from features and process to what matters most to validate
- How to use Assumption Artifacts to design fast, low-effort experiments that test high-risk beliefs early
- How generative AI can accelerate discovery, helping teams surface blind spots and rapidly create testable artifacts
- A new lens for product development, reframing it as a process of reducing uncertainty rather than following prescribed steps
About the Presenter
Raelin Sawka Musuraca brings over 30 years of experience leading product, user experience, and strategy initiatives across financial services, retail, healthcare, and consumer products. She has held leadership roles at BNY Mellon and American Eagle Outfitters and founded her own consultancy, Sharp Creative, advising organizations on digital product strategy and innovation. She currently serves as Director of the Master of Human-Computer Interaction (MHCI) program at Carnegie Mellon University, where she partners with industry to develop future product leaders. Her work focuses on helping teams reduce risk, prioritize effectively, and translate user insight into measurable business value through frameworks such as the Uncertainty Model and Assumption Artifacts.