You've heard of UX. You've heard of developer experience. Now meet AX — Agent Experience — and it's about to reshape how enterprises think about their entire tech stack. Lee Harper talks with Vihan Patel of Australia's Mantel Group about what happens when AI agents start bumping up against APIs that were never designed for them, why e-commerce is ground zero for the agentic shift, and the uncomfortable truth that enabling Cursor for your whole dev team doesn't automatically make you faster. They also tackle the governance nightmare of scaling from two agents to twenty, and whether we're heading toward a world where we get paid for decisions, not deliverables.

Most data programs don't fail because of bad technology, they fail because nobody wants to talk about the hard stuff. John Ladley has spent decades proving that behavior change is what separates the programs that stick from the ones that quietly die. In this episode, he's not holding back. From walking away from clients who weren't serious to telling a CIO to admit he didn't know what he was doing, John shares the unfiltered lessons that most consultants won't say out loud. If you work in data and you're tired of watching good ideas go nowhere, this one's for you.

Data governance is often seen as restrictive—but what if it’s actually the key to making data work?

Bob Seiner joins Sid Atkinson to challenge how organizations think about governance, accountability, and behavior change. Drawing from decades of experience, Bob explains why governance efforts stall, what shifts when organizations focus on outcomes instead of activity, and how ownership, not tooling, drives real adoption.

He also introduces the concept of data fluency, exploring why the ability to communicate with data is becoming just as important as understanding it.

Hosts Sid Atkinson and Lee Harper engage with guests Gary Griffin and David Holcomb, authors of "Building a Data Culture: The Usage and Flow Data Culture Model", to explore the concept of data culture. They challenge the notion that culture is unmanageable, presenting frameworks and models that make culture visible and actionable. The discussion covers the three R's of data culture, the usage and flow model, the significance of microcultures, and the differences between public and private sector dynamics. The conversation culminates in the introduction of the Data Culture Institute, aimed at equipping leaders to build and sustain a data-driven culture.

Data management purity and pragmatism built opposed camps starting in the 1990s, and echoes of those tenants present themselves today in Generative AI. Ontology purists and vector-based engineers appear at opposite ends, but how might we reframe so everyone's in the same picture? Tracy Talbot is a consummate data practitioner and has seen it all—from mainframes to machine learning. In this episode, she sits down with Sid Atkinson to reveal how the age-old Kimball vs. Inman debates mirror today’s AI struggles—and why her concept of “semantic patches” could be the key to keeping generative AI grounded in reality.

Building a data program isn't all about the tech—it's about getting people to actually work together. Carlos Rivero shares what it was really like starting as Virginia's first Chief Data Officer with no team, no budget, and a lot of skeptical agencies. He talks about how he learned to be more of a "people wrangler" than a data expert, turning critics into allies and figuring out that most of the job was just getting everyone on the same page.

Ever wonder why so many promising tech pilots never make it past the starting line? In this episode, Sid chats with Jonathan Alexander about breaking free from “pilot purgatory” and actually scaling innovation. From cavemen pushing carts with square wheels to global rollouts of cutting-edge solutions, Jonathan brings stories, strategy, and wisdom about how to get things done in a giant enterprise. They dive into building business cases that don’t flop, why change management beats the perfect tech stack, and how to avoid getting stuck with great ideas that go nowhere.

Leading complex IT systems in a major city demands more than technical know-how—it requires a shift from individual success to team achievement. Summer Xiao, Deputy CIO of Houston, shares her journey from "I" to "we," discussing the crucial transition from "doer" to "facilitator," the importance of shared ownership in large projects, and how team performance reflects directly on leadership.