Stay ConnectedI’m Joe Reis, co-author of Fundamentals of Data Engineering, creator of Mixed Model Arts, international speaker, and long-time observer of the tech industry’s favorite recurring mistakes.
Weekly broadcasts from somewhere on the road. Expect raw solo rants and long-form conversations with the engineers and leaders actually building things. I dive into data, AI, architecture, and career survival.
This podcast is invitation-only. Unsolicited guest pitches and PR outreach are not considered.
Copyright: © Joe Reis
Sanjay Agrawal, CEO of Revefi and co-founder of ThoughtSpot, joins me to talk about how AI agents are quietly driving unpredictable spikes in cloud data spend, and why most FinOps practices are built for a world that no longer exists.
Zach Wilson and I happen to be in Stockholm on the same night, so we sat down to talk about what it actually takes to be a data engineer in 2026.
Josh Wills has spent 25 years writing data pipelines. He uses coding agents daily and keeps hitting the same wall: they jump to conclusions and ship pipelines nobody understands. We get into the $200K vibe-coded pipeline problem, and why politics is the last job LLMs will ever touch.
Everyone says if you're not maxing out AI every second, you're getting left behind. I disagree. I talk about minimizing AI use for deep cognitive work, my new minimalist travel setup, and the skills that will actually get you left behind.
Shinji Kim, founder of SelectStar (acquired by Snowflake), joins me to talk about the deal, and why in a few years we may stop calling these things "data catalogs" at all as the category evolves into a living AI context layer.
Recovering from jet lag and hiking the hills of Salt Lake City, I break down a conversation with a VC friend about what's actually defensible in the age of coding agents, and what isn't.
George Fraser, CEO of Fivetran, breaks down why the "modern data stack" has evolved into "open data infrastructure," and why data gravity is the most overrated concept in data management.
From Shibuya Crossing in Tokyo, I make the case that the 40-year adoption curve of the electric grid is a better analogy for the AI boom than the dot-com bubble, and why most AI failures come down to the organization, not the technology.
Bob Seiner has worked in data governance since before it had a name. We dig into his Non-Invasive Data Governance approach, why he pushes back on the term "data enablement," and the state of data security in the age of autonomous AI agents.
From the hillsides of Phuket, Thailand, I push back on the idea that teams "don't have time" for fundamentals anymore, and make the case that AI actually makes data engineering more critical, not less.
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