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
The technology industry is prone to moving fast and forgetting its history. This is a shame because our industry is built on the shoulders of many giants, often long forgotten.
Bill Inmon, Roger Whatley, and I discuss the history of technology and computing, covered in their new book, From Stone to Silicon. We talk about the big people and moments in technology and computing, and much more.
From Stone to Silicon (book): https://amzn.to/4pLfqat
Welcome to 2026! In this spontaneous Friday AMA, I take listener questions on ontologies, the “leaky abstractions” of AI coding tools, why the “button pusher” era of engineering is a professional dead end, and the shifting landscape of data engineering.
I also provides an update on my upcoming book, Mixed Model Arts (launching in March 2026), and discuss the unexpected convergence of library science, ontologies, and traditional data modeling, something not on my 2025 bingo card.
Great turnout, especially for no notice. Thanks to everyone who showed up!
Happy 2026! In this episode, I rant about whether vibe coding and AI coding agents makes the Law of Leaky Abstractions obsolete, making your first dollar (or whatever currency), and more.
The Law of Leaky Abstractions: https://www.joelonsoftware.com/2002/11/11/the-law-of-leaky-abstractions/
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2025 is nearly gone, and in this episode, I give some thoughts on what I think might happen in 2026. I also chat about this week's surge of interest in Kimball vs Inmon (and the podcast I tried to organize with them) and much more.
“What I built today might be obsolete tomorrow.”
This is something I heard this week from a developer, and this is not uncommon given the warp speed nonstop advancement of AI models every week. We used to measure the rate of change in months or years. Now it’s days or weeks.
In this episode, I talk about why writing code is rarely hard part, and why having good taste and shipping things that people love is the most important things we can do.
In this episode, Nik Suresh returns to the show to discuss his first year running a bootstrapped services company. And no, he probably will not throat punch or pile drive you.
Nik explains why he moved away from hourly billing to fixed pricing, why writing code is often the least profitable part of a project, and how to spot "status games" in the tech industry. We also dive into the current state of AI, why bad leadership is the real problem behind failed tech initiatives, and trade stories about MMA and boxing.
We debunk the myth that starting a business has to be miserable, explore the performative nature of "hustle culture" in Silicon Valley, and break down why engineers often struggle with consulting sales.
Oh yeah...ontologies. In this mini-clip from Matt Housley and I, we chat about why ontologies are super popular now.
Had an interesting discussion with my 15 year old son. He and his friends see white collar work as “cooked.” They see it as a rat race where the work is increasingly insecure, abusive, and meaningless. Then there’s the looming question of AI…
Instead, they’re interested in careers they find meaningful and not as exposed to whatever AI does to work. And if they own a company, they’ll just hire “clankers” whenever that moment arrives.
I’m excited that these kids are looking at what’s happening right now, questioning if it’s their path, and choosing a life that’s fit for them.
More broadly, especially in the age of AI, I think some of the most important conversations we need to have is over what we find valuable and meaningful, making a living and the nature of work, and the nature of community.
It's Friday! Matt Housley and I catch up to discuss the aftermath of AWS re:Invent and why the industry’s obsession with AI Agents might be premature.
We also dive deep into the hardware wars between Google and NVIDIA , the "brain-damaged" nature of current LLMs , and the growing "enshittification" of the internet and platforms like LinkedIn. Plus, I reveals some details about my upcoming "Mixed Model Arts" project.
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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