Data Contracts Are For Software Engineers, Not Just Data Teams w/ Mark Freeman and Chad Sanderson
In this episode, I sit down with Mark Freeman and Chad Sanderson (Gable.ai) to discuss the release of their new O’Reilly book, Data Contracts: Developing Production-Grade Pipelines at Scale. They dive deep into the chaotic journey of writing a 350-page book while simultaneously building a venture-backed startup.The conversation takes a sharp turn into the evolution of Data Contracts. While the concept started with data engineers, Mark and Chad explain why they pivoted their focus to software engineers. They argue that software engineers are facing a "Data Lake Moment, "prioritizing speed over craftsmanship, resulting in massive technical debt and integration failures.Gable: https://www.gable.ai/
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Freestyle Fridays - To Succeed in 2026, Use December Wisely!
I meet a lot of people who want to accomplish major goals next year. Then the year comes and goes and most people are still waiting to get started.It's almost December. Rather than wait until the New Year to get going, use December to plan how you'll execute on "that thing" you're itching to accomplish. Time waits for nobody, so get going.
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Why AI Agents Need a New Lakehouse. Ciro Greco (Bauplan) on “Git for Data”
In this episode, Ciro Greco (Co-founder & CEO, Bauplan) joins me to discuss why the future of data infrastructure must be "Code-First" and how this philosophy accidentally created the perfect environment for AI Agents.We explore why the "Modern Data Stack" isn't ready for autonomous agents and why a programmable lakehouse is the solution. Ciro explains that while we trust agents to write code (because we can roll it back), allowing them to write data requires strict safety rails. He breaks down how Bauplan uses "Git for Data" semantics - branching, isolation, and transactionality - to provide an air-gapped sandbox where agents can safely operate without corrupting production data. Welcome to the future of the lakehouse.Bauplan: https://www.bauplanlabs.com/
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Freestyle Fridays - So You Want to Grow on Substack
Just launched your Substack? Great! Here’s what to do next.This episode covers the realities of writing long-form in public, the traps that cause most writers to stall, how to build consistency, and how to grow an engaged audience from day one.
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From Data Engineering to Context Engineering w/ Nick Schrock
Data engineering is undergoing a fundamental shift. In this episode, I sit down with Nick Schrock, founder and CTO of Dagster, to discuss why he went from being an "AI moderate" to believing 90% of code will be written by AI. Being hands on also led to a massive pivot in Dagster’s roadmap and a new focus on managing and engineering context.We dive deep into why simply feeding data to LLMs isn't enough. Nick explains why real-time context tools (like MCPs) can become "token hogs" that lack precision and why the future belongs to "context pipelines": offline, batch-computed context that is governed, versioned, and treated like code.We also explore Compass, Dagster’s new collaborative agent that lives in Slack, bridging the gap between business stakeholders and data teams. If you’re wondering how your role as a data engineer will evolve in an agentic world, this conversation maps out the territoryDagster: dagster.io Nick Schrock on X: @schrockn
What happens when a best-selling author and "recovering data scientist" gets a microphone? This podcast.
I'm Joe Reis, and each week I broadcast from wherever I am in the world, sharing candid thoughts on the data, tech, and AI industry.
Sometimes it's a solo rant. Other times, I'm chatting with the smartest people I know.
If you're looking for an unfiltered perspective on the state of AI, data, and tech, you've found it.
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