Facilitation Lab Podcast

In this episode of the New Friction series from the Facilitation Lab podcast, host Douglas Ferguson interviews Daniel Elizalde, VP of Product and Technology at ReUp Education, about why faster AI-powered building doesn't automatically produce business results. Daniel describes the "speed fallacy" in B2B, where long sales cycles, security reviews, and limited customer attention cap how fast products can be adopted. He explains how he now treats product and engineering as a portfolio, pausing roadmaps and moving teams to wherever the real bottleneck sits, anchored by a shared company vision that his team communicated through an AI-generated video. The conversation covers misaligned incentives in sales and marketing, the risk of everyone vibe coding their own tools without a shared data layer, and the standardized agents and skills his engineers use with Claude. Daniel closes with the F1 analogy that a faster engine means little if the rest of the car and the track can't keep up.

In this episode of the New Friction podcast, host Douglas Ferguson interviews Bryon Jacob, a technology advisor and AI strategist who previously co-founded data.world as CTO and spent a decade at HomeAway. Jacob argues that the teams succeeding with AI-assisted software development share one thing in common: rigorous governance — including near-100% automated test coverage, strictly enforced architectural standards, and code bases deliberately organized for agentic development. He explains why zero tech debt has shifted from aspirational to economically necessary, since AI amplifies good patterns and railroads bad ones, making clean, well-documented, thoroughly tested code the prerequisite for real productivity gains. The conversation examines how leaders are rethinking code review, prototyping, and the entire software development lifecycle, including why a CEO drafting a pull request in Claude Code is a fundamentally better spec than any design brief. Jacob closes by drawing the arc from assembly language to compilers to natural language programming, framing today's moment as the natural next step in a decades-long evolution — and a preview of the governance-driven transformation already coming for legal and every other structured profession.

In this episode of the Facilitation Lab podcast, host Douglas Ferguson interviews Yvette Cronje, Head of UX Design for HP's unified consumer app experience, about how design leadership is shifting as AI compresses production time. Cronje argues that AI hasn't removed the hard part of design so much as relocated it: craft is shifting from executing pixels to judgment, taste, and critique, and teams need shared principles and decision frameworks in place before they diverge into AI-generated options, or misalignment simply accelerates alongside execution. She and Ferguson trace how this plays out in practice, from workshops that align teams on principles before production, to using AI as a critique partner and coaching tool rather than a production shortcut, to the delegation and communication skills leaders increasingly need as ICs manage AI collaborators. They also discuss trust, both customers' trust in AI-driven product features and organizational trust in people through constant change, as a central design and leadership problem. The conversation closes on reframing AI anxiety as an opportunity for curiosity and growth rather than a threat to craft or job security.

In this episode of the Facilitation Lab podcast, host Douglas Ferguson interviews Alyssa Coughlin, Director and Chief of Staff for Autodesk's Data, AI, and ML Platform organization, about what it actually takes to move a large engineering company from AI-enabled to AI-native. Coughlin describes how bottlenecks have shifted away from writing code toward code review, deployment permissions, and design decisions now that AI has made execution fast and cheap. She walks through concrete changes her org has made, including abandoning two-week Scrum sprints for Kanban flow, moving from PRDs to spec-driven development consumable by both humans and AI, and building shared "knowledge graph" brains to catch duplicated work before it ships. Throughout, she frames change management as a balance of carrot and stick, arguing that engineers aren't losing their jobs so much as shifting from author to orchestrator, and that managers themselves must stay hands-on with the tools to coach effectively. She closes by describing AI as an amplifier that exposes organizational seams rather than a fix, so the real work is continuously finding and addressing the friction it reveals.

In this episode of the Facilitation Lab podcast, host Douglas Ferguson interviews Jeff Chow, Chief Product and Technology Officer at Miro, about where friction is showing up inside product teams as AI reshapes how work gets done. Jeff describes how PMs prototyping in high fidelity, designers coding, and engineers orchestrating agents are collapsing old role boundaries, and argues the underlying tensions — who owns a decision, who gets paged at 2am, how a designer receives feedback — aren't new, just amplified. Much of the conversation centers on decision-making as the real bottleneck: Jeff makes the case that 10x individual output doesn't translate into 10x business results unless organizations can also accelerate cross-functional alignment and cascade decisions with their underlying context, not just their conclusions. He and Douglas dig into Miro's bet that a shared visual canvas — carrying both artifacts and a decision log of why choices were made — is the connective layer that keeps AI-assisted work and human teams moving together instead of fragmenting into isolated single-player sessions. The two also trade observations on viral AI adoption patterns inside organizations, the psychology of design crits applied to AI-generated work, and the early signs of "ephemeral UI" and custom, vibe-coded widgets reshaping what software teams expect to build for themselves.