Catalog & Cocktails: The Honest, No-BS Data Podcast

It's Friday: Juan and Tim rant about AI, Agents, and the Uncomfortable Truth About Data's New Center of Gravity

Catalog & Cocktails: The Honest, No-BS Data Podcast

Show Notes

Juan and Tim's Friday rant covers a lot of ground, from Juan's TED takeaways on AI's unprecedented speed and what it means for humanity, to the uncomfortable shift data teams need to make: work and decisions are the point, not pipelines and gold layers. They dig into what Medallion Architecture 2.0 looks like (feedback loops, insights to action, agent governance), why organizational design theory applies directly to agent swarms, and what library science can teach us about the future data stack. The thread running through all of it: the humans who thrive in this moment won't be the ones who build the most, but the ones with taste. See omnystudio.com/listener for privacy information.

More from Catalog & Cocktails: The Honest, No-BS Data Podcast

Oct 23, 2026

Nick Zervoudis, data product manager, trainer, and consultant at Value from Data & AI, joins Juan and Time to talk about why many data teams end up working like a service desk and what to do about it. The answer is: DO DISCOVERY! In this conversation, we cover how a service desk model breaks down when a request can’t be described in a few words, why dashboards get opened once and then forgotten, and how product thinking differs from project management in data work. We also discuss how to start doing discovery without a full transformation, and what AI does and doesn’t change about that work. See omnystudio.com/listener for privacy information.

Oct 23, 2026

This is the takeaway episode with Nick Zervoudis, data product manager, trainer, and consultant at Value from Data & AI, joins Juan and Time to talk about why many data teams end up working like a service desk and what to do about it. The answer is: DO DISCOVERY! See omnystudio.com/listener for privacy information.

Oct 16, 2026

Mohammed Aaser, former chief data officer at McKinsey and former chief data strategy officer at Domo, recently visited Juan and shared his framework on talent in the AI era. It was incredibly insightful and we asked if he could come back to the podcast (after 5 years!) His argument is that the potential of AI will be unlocked by humans because humans understand the problems, and are driven/motivated to solve the problems. In this episode, Mohammed lays out a framework for talent in the AI era. Automation is already taking over the known, repeatable work. What remains is the unknown, and that takes people who keep learning and who take initiative. The framework plots people on two dimensions, learning and drive. You have Doers, Philosophers, Commanders, Hackers, Strategist, Innovators, Game changers and more. Topics discussed Automation and the innovation engine The known versus the unknown Two dimensions of talent The talent quadrants The multiplier effect Commanders and scaling Environments that don’t build initiative Rarity of high-potential people Investing in human potential The human mind as the limit Critical thinking through discomfort See omnystudio.com/listener for privacy information.

Oct 16, 2026

This is the takeaway episode with Mohammed Aaser, former chief data officer at McKinsey and former chief data strategy officer at Domo. He recently visited Juan and shared his framework on talent in the AI era. It was incredibly insightful and we asked if he could come back to the podcast (after 5 years!) His argument is that the potential of AI will be unlocked by humans because humans understand the problems, and are driven/motivated to solve the problems. See omnystudio.com/listener for privacy information.

Oct 9, 2026

How do leaders preserve executive trust and credibility? Dora Boussias, executive advisor and former data executive returns to the podcast to unpack this question. Her answer: protect your judgement. In this episode, Dora presents the trust equation that most leaders grew up with: expertise + track record + judgment. Dora’s point is that the equation still holds, but each part now means something different. Nobody will out-know AI, so expertise is less about what you know and more about asking the right questions and challenging assumptions. A track record is harder to read when you can’t tell whether a good result came from you or from the model. Judgment carries the most weight now, and it’s the part leaders are most likely to hand off without noticing. Topics discussed: Trust equation under AI Expertise is changing Track record is harder to read Judgment carries the most weight Decision fog Speed isn’t everything Ford’s rehiring of experienced engineers Business fundamentals matter more Alignment and accountability are cross-functional Real value is “so what” See omnystudio.com/listener for privacy information.

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