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
On this episode of The Joe Reis Show, I’m joined by Dan Bennett, Head of Technology for the Enterprise Data Organization at S&P Global.We get into what it actually looks like to build with modern AI coding tools like Claude Code. Not just as a toy, but for writing production-grade C++. Dan walks through how he built an open-source RDF extension for DuckDB, why rock-solid test coverage is non-negotiable when working with LLMs, and why engineering leaders need to keep their hands dirty to understand where this tech is headed. We also react to the breaking news of AWS acquiring DuckDB Labs, talk through the shift from "human-in-the-loop" to autonomous agents running in headless VMs, and dive into why data semantics across organizational boundaries remains one of the hardest - and most important - unsolved problems in our industry.Website: https://nonodename.com/
Will AI agents solve the data industry's hardest challenges, or are we just amplifying existing chaos?In this episode, I chat with Oliver Laslett, Co-founder and CTO at Lightdash, to explore the frontier of agentic analytics, data modeling, and modern software engineering practices. We dive deep into how AI is shifting daily workflows from writing SQL and DBT models to higher-order system thinking, why the hardest data problems remain human and organizational, and the cultural differences in tech optimism between London and San Francisco.Oliver also breaks down why permissions, curation, and data lineage are still the true bottlenecks, and why high-ownership communication matters more than ever in an era of AI slop.
It feels like everything is converging right now. Data forms and systems are converging. Agile and Waterfall are starting to look strangely compatible. Software engineering, data engineering, and AI engineering are bleeding into each other.
In this episode, I explore why AI is collapsing boundaries we spent decades creating, and why semantics, architecture, specification, and judgment may matter more as a result.
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Sponsor: Fivetran
With the rise of AI and agents, having centralized, trustworthy data is the absolute foundation for building tools and training models. Fivetran automates your data pipelines, removing the need to build fragile connectors so your data arrives clean and reliable. By handling the messy infrastructure behind the scenes, Fivetran allows your team to focus on building the future. Visit fivetran.com to learn more.
The Joe Reis Show is invitation-only. Unsolicited guest pitches and PR outreach are not considered.
Are massive frontier AI models actually worth the cost?In this episode, I sit down with Daniel Svonava, Founder of Superlinked, to break down where AI is actually heading in production. We dive into why the hype around massive frontier models is shifting toward targeted, small open-source models, and how to orchestrate smart agents without blowing through your budget.Daniel shares how Superlinked is building open-source inference infrastructure, why small models are rapidly closing the performance gap, and how you can engineer faster, cheaper, and more control-driven AI systems.
Every so often, the tech industry declares something dead. Data warehousing is dead. Data modeling is dead. Semantic layers are dead. SQL is dead. Now AI is supposedly making entire professions obsolete. I get it. Ragebait gets the clicks and comments. But it's also lame and disingenuous.
In this Freestyle Friday, I unpack the logical fallacies behind these claims, why technology almost always evolves instead of replaces, and how separating fundamentals from shapeshifting implementations gives you a much clearer view of where the industry is actually headed.
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Sponsor: Fivetran
With the rise of AI and agents, having centralized, trustworthy data is the absolute foundation for building tools and training models. Fivetran automates your data pipelines, removing the need to build fragile connectors so your data arrives clean and reliable. By handling the messy infrastructure behind the scenes, Fivetran allows your team to focus on building the future. Visit fivetran.com to learn more.
The Joe Reis Show is invitation-only. Unsolicited guest pitches and PR outreach are not considered.
In this episode, I crashed Pattern's office to sit down with Jacob Miller (VP of Platform Intelligence) and Jeremy Mumford (Lead AI Engineer) from Pattern to discuss their newly co-authored book, "Architected Intelligence." We dive deep into the reality of building scalable AI systems, explaining why companies cannot simply put an LLM in front of everything. We also explore the importance of curating data to avoid the "semantic swamp," the reality of adapting organizational structures to external marketplace algorithms, and the collaborative process of writing a tech book using AI as an "anti-sycophantic" sparring partner. We also discuss the booming tech and startup scene in Utah, the future of autonomous cloud agents powered by budget-friendly AI models, and more.Buy Architected Intelligence: https://amzn.to/4haOqAr
The Joe Reis Show is invitation-only. Unsolicited guest pitches and PR outreach are not considered.
I'm getting a ton of emails from individuals and PR agencies asking to be on my podcast. Almost all of it is AI slop spam of the most bland and uninteresting kind. "I have an AI startup solving X." Yeah, you and everybody else... my Goldendoodle also has an AI startup.
As a reminder my podcast is invite-only.
If you or your PR agency sends me these types of messages, I will ignore them or berate you for spamming me with this nonsensical and offensive slop.
Marshall McLuhan predicted a post-literate world in The Gutenberg Galaxy. That world may now be arriving: humans are reading less, AI is reading more, and engineers can increasingly produce code, schemas, documentation, and infrastructure without fully understanding what they created. Perhaps this describes you? ;)
In this Freestyle Friday, I look at the gap between production and comprehension, why judgment is becoming more valuable than cranking out code and diagrams, and how software and data engineers may evolve from writing code, shipping widgets, and building pipelines to creating the context and semantic infrastructure that machines need to act.
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Sponsor: Fivetran
With the rise of AI and agents, having centralized, trustworthy data is the absolute foundation for building tools and training models. Fivetran automates your data pipelines, removing the need to build fragile connectors so your data arrives clean and reliable. By handling the messy infrastructure behind the scenes, Fivetran allows your team to focus on building the future. Visit fivetran.com to learn more.
The Joe Reis Show is invitation-only. Unsolicited guest pitches and PR outreach are not considered.
I sat down with Sharon Goldman - AI journalist, formerly at VentureBeat and Fortune, now running her own platform, Ground Level AI on Substack - for a conversation that went a lot further than I expected.We cover a lot of ground about the AI backlash, data centers, AI hype vs. reality, and the future of writing.
Check out Ground Level AI: https://www.groundlevel-ai.com/
The Joe Reis Show is invitation-only. Unsolicited guest pitches and PR outreach are not considered.
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