The way we build agents today is dumb with Vaibhav Gupta

Juan and Tim are back for a LIVE episode with Nachiket Mehta, an experienced data leader who has lived and breathed the “shift left”. In this episode we unpack how ontology, events and culture unlock enterprise AI.  We discuss the gap between what your systems think is happening and what's actually happening on the ground and dive into real world examples: a trailer with expensive merchandise sat forgotten in a yard for weeks. $35M in delayed orders. The math added up, but nobody saw it coming. Why? Because we're obsessed with cleaning data and building dashboards, but nobody mapped the happy path vs. the exceptions actually happening on the ground.  What is delivery when the customer isn't home? What's "lost in transit" versus "sitting in our own yard"? The solution? Send your ontologist to the fulfillment center. Build tiger teams. Shift your data teams left to act like software product teams. And most importantly: connect the five why's back to your OKRs, or you're just building features nobody needs.See omnystudio.com/listener for privacy information.

This is the takeaway episode with Nachiket Mehta, an experienced data leader who has lived and breathed the “shift left”. In this episode we will unpack how ontology, events and culture unlock enterprise AI. We discuss why your ontologist needs to visit the fulfillment center, how to shift data teams from afterthought to proactive partner, and why the five why's matter more than your tech stack.See omnystudio.com/listener for privacy information.

Tim and Juan unpack why Vaibhav Gupta, co-creator of BAML, states that most agentic AI code out there is dumb. It's ugly, fragile, and built by people who've never had to wrestle with probabilistic systems before. But here's the thing: we've seen this movie before. Remember when building websites was painful? Then jQuery showed up... then React... then Tailwind. Abstraction always wins. It just takes time (and about 50 bad frameworks for every good one). The gaming industry also figured out about unreliable systems decades ago. The takeaway is that the real bottleneck isn't abstracting the AI, instead it's abstracting the failure. Oh, and this episode has a live demo (first time we ever do this!). See omnystudio.com/listener for privacy information.

This is the takeaway episode with Vaibhav Gupta, co-creator of BAML, where we unpack why most agentic AI code out there is dumb. If you like what you hear, you should listen to the full episode. See omnystudio.com/listener for privacy information.

Juan and Tim grab a beer and rant about decision intelligence and context graphs, MCP vs Skills, and how companies really have a work problem (not a data/AI problem) and what is the maturity model to get that work doneSee omnystudio.com/listener for privacy information.

Tired of executives breathlessly asking "what's our AI strategy?" while your data team drowns in 1,000 dashboards that nobody uses? In this episode, Juan and Tim cut through the noise with Juan Gorricho a data and analytics executive with more than 25 years of experience delivering business value at TD Bank, Visa, The Walt Disney Company We cover: Why do data leaders keep building vanity metrics instead of business value? How do you go from being an "order-taking reporting team" to a trusted decision intelligence partner? And why does every data governance initiative feel like building policies nobody wants to follow? The secret? Do it by slice. Not top-down. Not bottom-up. By slice—connecting each data product to real business outcomes while building reusable foundations underneath. If you're ready to turn your data team's NPS around and build trust that actually sticks, this one's for you. Spoiler: It starts with being brave enough to tell executives the truth. And btw, "I bet 40 columns drive 90% of your business."See omnystudio.com/listener for privacy information.

This is the takeaway episode of our chat with Juan Gorricho, a data and analytics executive with more than 25 years of experience delivering business value at TD Bank, Visa, The Walt Disney Company. We cover: Why do data leaders keep building vanity metrics instead of business value? How do you go from being an "order-taking reporting team" to a trusted decision intelligence partner? And why does every data governance initiative feel like building policies nobody wants to follow? And so much more. If you liked these takeaways, listen to the full episode!See omnystudio.com/listener for privacy information.

Juan and Tim got together for a beer to rant about what's on their mind, the latest in the data world and share Data Day Texas takeawaysSee omnystudio.com/listener for privacy information.

Dr. Irina Steenbeek is a data practitioner, and author of multiple books including Data Lineage from a Business Perspective. In this episode, Juan and Tim discuss with Irina the practical realities of implementing data lineage and its relationship to Data and AI governance. For example, do you really need to have a comprehensive technical lineage? A lot of honest no-bs nuggets in this episode!See omnystudio.com/listener for privacy information.

This is the takeaway episode with Dr. Irina Steenbeek, a data practitioner, and author of multiple books including Data Lineage from a Business Perspective. In this episode, Juan and Tim discuss with Irina the practical realities of implementing data lineage and its relationship to Data and AI governance. See omnystudio.com/listener for privacy information.