"Great companies, you're never deciding between a great idea and a bad idea. You're looking at 20 great ideas that all have merit and you…
New Friction
AI has made eliminating workflow friction easier than ever, but removing every obstacle can create hidden organizational risk. This article introduces the concept of friction discernment; the leadership skill of distinguishing between draining friction that wastes time and developmental friction that builds judgment, expertise, and resilience. Learn why optimizing solely for speed creates capability debt, how AI can unintentionally erode critical thinking, and how leaders can intentionally design the right friction back into work to strengthen decision-making, learning, and long-term organizational performance in the age of AI.
In this episode of the Facilitation Lab podcast, host Douglas Ferguson interviews Sarah B. Nelson, Distinguished Designer at Kyndryl and co-founder of Kyndryl Vital, about why AI's promise to remove friction is actually surfacing the human dynamics organizations have always avoided facing. They unpack how a single word like trust splinters into distinct concerns — model accuracy, data use, organizational credibility — and why treating human in the loop as a rubber-stamp step risks disengagement and stripped-out meaning. Nelson draws on the NeuroLeadership Institute's SCARF model to explain why AI rollouts stall on status, certainty, autonomy, relatedness, and fairness rather than on the technology itself, and shares stories spanning cybersecurity burnout, Holacracy at Zappos, and the extraction economics behind AI training data. The conversation keeps returning to her insistence on designing with people rather than at or for them, and on imagination as the resource most at risk of being engineered out of enterprises chasing speed. She closes with a Buckminster Fuller line she keeps returning to: that people are called to be architects of the future, not victims of it.
In this episode of the New Friction podcast, host Douglas Ferguson speaks with Peter Bell, founder of Gather.dev and author of the forthcoming O’Reilly book Scaling AI Adoption in Engineering. Bell draws on his work running invite-only peer communities for senior engineering leaders to diagnose why most organizations stall out in AI pilot mode rather than achieving meaningful transformation. The conversation maps three distinct patterns of engineer resistance—skeptics burned by early models, craft-focused developers who resist the shift toward managing agents, and those with principled objections to AI—and offers concrete tactics for reaching each group. Bell and Ferguson explore how AI amplifies existing organizational health: strong DevOps practices compound upward while process debt scales its dysfunction. They examine the mandate trap, measurement via token usage as a diagnostic rather than a performance metric, and the non-negotiable role of psychological safety in any serious adoption effort. The episode closes with Bell’s call for engineering leaders to build hands-on with current models, arguing that firsthand intuition—not secondhand reports from a VP of AI—is what this transition demands.
In this episode of the New Friction podcast, host Douglas Ferguson speaks with Jeff Grabill, Dean of the College of Arts and Sciences at the University at Buffalo, recorded in the immediate aftermath of the IHE US AI Summit 2026, which both men attended. Grabill recounts what emerged from that two-day working convening: the foundation of the Buffalo Statement, a collective public agenda for AI in higher education, and reflects on why the room's patience, grounded confidence, and willingness to question prior assumptions exceeded his expectations. The conversation explores why universities, often criticized for moving slowly, may possess exactly the right instincts for AI transformation: designing conversations intentionally, engineering productive friction, and moving fast and slow at the same time. Ferguson and Grabill dig into how AI has relocated rather than eliminated friction, particularly in learning environments, where effortless output now threatens the productive struggle that actually builds expertise and ideas. They close on a librarian's insight from the summit — "I don't care if AI created it, I care if it's true" — and Grabill's call for businesses and universities to actively seek one another out as partners in working through this moment.
In the inaugural episode of New Friction, host Douglas Ferguson and Erik Skogsberg explore how AI has shifted organizational friction from execution to decision-making and alignment. While AI accelerates production, it magnifies existing dysfunctions when teams lack collaborative habits. They introduce the concept of "multiplayer AI"—moving beyond individual productivity gains toward team-level collaboration. The conversation emphasizes that facilitation, judgment, and organizational health are now the critical differentiators. Practical takeaways include assessing whether your organization operates in "single player" or "multiplayer" AI mode and intentionally slowing down at key decision points to maximize human impact.
New Friction is a podcast from Douglas Ferguson on the real organizational challenges of AI transformation. AI made execution almost free but most organizations are still stuck. Not because the technology doesn't work, but because the people problems got harder: decision-making, governance, and trust friction. Each episode features practitioners navigating AI change at ambitious organizations — what broke, what they tried, and what actually worked. We explore the shift from building to deciding, the 4x perception gap between leaders and the workforce, multiplayer AI organizations, and how the next generation learns judgment. Episode 1 drops May 26, 2026.
