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.

It's been four years and a day since the Fundamentals of Data Engineering was published. The big mental models of the book are the Data Engineering Lifecycle and its Undercurrents. I also discuss what would change about the book if I write it again today.

Thanks to everybody who has supported the Fundamentals of Data Engineering over the years. It's super cool to see the massive impact that the book has had on the data industry and its practitioners around the world.

Are AI agents replacing traditional data engineering tasks?

I sat down with Matt Glickman, CEO & Co-founder of Genesis Computing and former Snowflake and Goldman Sachs executive, for a conversation about where data engineering is actually heading. Most organizations today are stuck in "demo mode" or using LLMs as expensive code completers, simply writing code faster to feed legacy data architectures. But if you look at the industry from first principles, humans were never meant to be data machinery.

In this episode, Matt and I break down how true agentic data systems work, why current enterprise architectures will fail under agent-scale query volumes, and what it really takes to capture institutional knowledge before it leaves the building.

We also cover Matt’s front-row seat at Goldman Sachs during the 2008 financial crisis, his early days turning Snowflake into an enterprise giant, and how AI-native companies will outpace traditional enterprises. If you're building, architecting, or leading teams in the AI and data space, this is a conversation you don't want to miss.

The Joe Reis Show is invitation-only. Unsolicited guest pitches and PR outreach are not considered.

Here's a new show where I quickly cover a mental model that applies to your work as a data leader or practitioner.

Kicking things off is Conway's Law.

It's been a crazy summer for AI. AI enthusiasm remains high, but the market is starting to ask far harder questions. Semiconductor stocks are in a bear market. IBM’s shares fell sharply. Data-center projects are facing political and community resistance. Enterprises are adopting AI, but many are struggling to turn experimentation into measurable returns.

In this Freestyle Friday episode, I look at why these signals do not necessarily mean an AI winter. Instead, they suggest that AI is moving from a "possibility market" into an "accountability market", where capability, economics, infrastructure, and organizational reality finally have to reconcile. Put another way, things are going to get real.

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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.

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Sponsor: Revefi

Save serious money on your cloud costs with Revefi’s new autonomous AI DBA, a tool built to handle the gritty reality of cloud data management so you can stop babysitting your infrastructure. Start saving money today at ⁠⁠revefi.com/ai-dba

A short rant based on my new article this week, "The Database Is Not the Data Model"

"In discussions with data practitioners, I keep seeing the same confusion. Someone pulls up a DDL file, a folder of dbt or SQL, or an ERD reverse-engineered from a Postgres instance and says: “Here’s our data model.”

Not to be pedantic, but that’s a schema. Schemas are great. But data modeling is more than just schema design."

Let’s dive into the difference in this podcast and the article.

Article: https://practicaldatamodeling.substack.com/p/the-database-is-not-the-data-model