The Joe Reis Show

The 2026 Practical Data Community State of Data Engineering dropped this week. It's full of some obvious and very counterintuitive information about the state of data engineers around the globe, in all sizes and types of organizations. Check it out!
Also, I talk about the book writing process, where I messed up on this latest book, it's progress toward publication, and more.

Survey: https://joereis.github.io/practical_data_data_eng_survey

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I sat down with Paul Dudley (CEO) and Ricky Thomas (CTO) from StreamKap to catch up on where the world of streaming data is heading—and things have changed fast since we last spoke.

We dive into the concept of "vibe coding" and how AI is radically accelerating how we build software (I even share a story about building a data analysis tool in an hour). But the real meat of this conversation is about the intersection of streaming data and AI agents. Everyone is building agents, but without real-time context, they’re flying blind. We discuss why streaming is a missing link for agentic workflows, the shift from dashboards to automated decision-making, and why SaaS companies are racing to build walled gardens around their data.

We also get into the nitty-gritty of the UK vs. US tech markets, the resurgence of PR in the AI era, and StreamKap’s upcoming move into the Snowflake native app ecosystem.

Streamkap: https://streamkap.com/

This week was a doozy with new AI releases, the stock market, and more. It really feels like this was the first tremor in AI's impact on the SaaS market. What's do I think is next? Listen and find out.

In this episode, I sit down with Mike Driscoll, founder of Rill Data, to discuss the evolving landscape of business intelligence and data engineering. We explore why the industry keeps "rediscovering" old concepts like the semantic layer and how the rise of AI agents is forcing us to rethink how we structure data.
Mike shares his insights on the "shape" of analytics, debating whether conversational interfaces will replace dashboards or simply complement them. We also dig into the growing demand for data engineering, the importance of watermarks and temporal semantics, and why data visualization remains a critical tool for "trust but verify" in an AI world.

Rill Data

Mike’s Podcast: Data Talks on the Rocks

As I use AI, I'm finding that I create MORE work for myself, not less. One task completed means five more to do. This is the paradox of today - AI might actually mean more work, not less.

I talk about this, the Data Day Texas final episode, and more.

Check out the review I did of Cube's new analytics agent: https://www.youtube.com/watch?v=p3frGJOUl1E
(Thanks to Cube for partnering on the review)