Erin May talks with Jared Forney, Research Operations Principal at Okta, about how the role of research and research operations is shifting as AI accelerates product development. Jared explains why scale and rigor do not have to be opposing forces and why teams need to return to their core goals before adding new tools.

Jared dives into how he builds trust across legal, product, and design teams and why that trust becomes the capital you spend when driving big change. He shares why automating more work actually concentrates human attention rather than removing it, how he approaches knowledge management and orchestration across many data sources, and why written communication and technical skills now matter more than ever. Jared also answers audience questions on governance, getting buy in for research ops, working faster under compressed timelines, AI guard rails, and breaking into the field.

Highlights

• 02:13 Upskilling for scale and rigor
• 04:33 Balancing speed with research quality
• 14:50 Where humans fit in AI workflows
• 25:00 Rethinking knowledge management and MCP
• 32:00 Best tactic for getting governance buy-in
• 41:35 Enabling faster research under pressure

About Our Guest
Jared is a Research Operations Principal based in the San Francisco Bay Area with 8+ years building research infrastructure from the ground up. His work sits at the intersection of governance, tooling, and enablement: building systems that help research teams move faster while keeping data practices sound. He's led repository migrations, developed AI governance frameworks, consolidated tooling ecosystems, and spoken at industry conferences about how operations can amplify — not constrain — great research. Connect with Jared on LinkedIn!

Resources

• The Blueprint for Evaluating AI Across the Research Pipeline
• The State of Research Operation 2026
• State of Synthetic Users Report
• AI in Research Risk Cascade

This week we're revisiting one of Awkward Silences' most memorable episodes.

Much of the conversation around AI in UX involves how it will shape and change researchers' work. This episodes's guest, Jess Holbrook, who leads UX research for Microsoft AI, thinks a lot about how this technology can be improved with design and UX best practices. Jess has spent over a decade working on the UX of AI at companies like Meta and Google. He's also helped develop foundational principles for the ethical use of LLMs.

Jess joined Erin and Ben to reframe the AI conversation, focusing on how UXRs can and should adapt, what working on these systems has taught him about the UX discipline, and his philosophy for building teams that are ready to take on the innovative challenges of tomorrow.

Jess's recommendations: Matt Webb, Maggie Appleton, and the Pessimists Archive Newsletter.

Highlights

• 07:15 Human-Centered AI Evolution
• 17:53 Evolving AI Forecast Strategies
• 24:04 Diverse AI Team Building
• 33:27 Navigating Responsible AI Challenges
• 37:01 Qualitative Analysis with AI Tools
• 40:15 Optimism and Concerns About AI

About Jess
Senior Director of Research specializing in human-centered AI. Early stage investor in AI, AI hardware ecosystems, climate, and anything that seems like the world would be better with it in it. Currently leading UX research for Microsoft AI. Previously led the Generative AI team and supported all UX functions for the Responsible AI and data transparency teams at Meta. I also served on the Board of Forging Youth Resilience, a nonprofit that empowers young people to build physical and mental strength for life by providing access to a national network of community-based fitness programs and mentorship.

Resources

• The AI in UX Research Report
• 20+ Tools for Every Research Phase
• Using AI in UX: A Day-in-the-Life

Erin May sits down with Alec Levin, CEO and Co-Founder of Learners, to explore how researchers can navigate the rapid changes reshaping their field. Alec shares his vision for how AI and automation are creating unprecedented opportunities for research teams willing to step up and lead.

Alec argues that while AI can handle routine tasks like usability testing and surveys, researchers have a chance to focus on higher-value discovery work that includes prototyping and coding. He emphasizes that this is a critical moment for researchers to define their own future rather than letting executives decide their role. The conversation covers practical examples of AI-powered research workflows, the importance of cross-functional collaboration, and why researchers need to be more proactive in pitching their vision internally.

Highlights

• 03:40 Balance sheeting thinking for change
• 06:15 Connecting researchers through community
• 13:11 Discovery research importance
• 15:02 Vision needed for researcher evolution
• 24:08 Automated research workflows emerging
• 31:16 Human elements AI can't replace

Resources

• AI for User Research 101 Workshop
• What is the New AI in Research Risk Cascade?
• Assessing the ROI of AI in UX Research Webinar
• AI Context Engineering for Research Course