I’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.
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. ----------------------- 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.
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. ----------------------- 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. ----------------------- 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
In this episode, I chat with Steve Brown, an AI futurist, independent consultant, and former professional at Intel and Google DeepMind. Steve shares his insights on helping global leadership teams decode the future of artificial intelligence. We dive into the common pitfalls of corporate AI adoption, including why so many AI initiatives fail due to poor communication and a lack of cultural integration. Steve outlines a definitive three-step path to AI transformation, emphasizing the critical difference between 20th-century cost-cutting and 21st-century labor amplification. The conversation also explores how AI is reshaping middle management, the distinct differences between "AI-first" and "AI-native" businesses, and the staggering acceleration of physical AI and humanoid robotics.
In this Freestyle Friday episode, I break down results from the June 2026 Pulse Survey on organizational dysfunction among data engineers. I also dig into why data product ownership (or lack thereof) is one of the fundamental issues standing between companies and success with data and AI. ----------------------- 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. ----------------------- 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
I walk through exactly how I use AI for idea generation, review, editing, and drafting on my upcoming book, Mixed Model Arts. This is also the first in a new Wednesday format where I answer listener questions about what I'm building. -------------------- Mixed Model Arts will be out soon. If you want to get a good deal on the e-book and on-demandcourse, please go to Practical Data Modeling.: https://practicaldatamodeling.substack.com/
Kirill Bobrov, a senior data engineer at Spotify and author of the blog Luminousmen, joins me to talk about his viral "Drunk Post" repost, whether the AI boom is real infrastructure or another bubble, why engineering judgment can't be automated away, and the process of writing a technical book on concurrency. Luminousmen: https://luminousmen.com/
With AI reshaping employer expectations, junior candidates in data are facing real anxiety about the job market. I share the technical and personal skills I'd focus on, my top five traits I look for in a candidate, and how to build a network from scratch. ----------------------- 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. With a five-minute, zero-touch setup, it deploys 18 specialized agents across your data estate to automatically manage FinOps, performance tuning, and data quality. If you want to cut your cloud costs by 30% to 70% and get back to actual data architecture, check out what they are building at revefi.com/ai-dba
Maxime Beauchemin, creator of Apache Airflow and Superset, joins me to talk about his path from data orchestration to the frontier of AI. We cover his "Claude Code moment," his new agentic workflow tool Agor, and what a software-utopia future might actually look like.
Standing on the high plains near South Pass, Wyoming, where the Oregon and Mormon trails once crossed, I look at the remnants of the 1800s gold rush and draw a direct line to the current AI boom.
Prukalpa Sankar, founder of Atlan, joins me to unpack the piece most AI projects are missing: context. We get into building an enterprise "second brain," why agents get abandoned in testing hell, and what it actually took to rebuild Atlan as an AI-native company.
Juan Sequeda joins me straight off a month of travel to unpack the real state of AI agents in the enterprise, the danger of a "semantic swamp," and why pragmatism beats pedantry every time in data architecture.. 🎙️ SPONSORS Revify - surprise Snowflake bills? One customer cut theirs 50% in 48 hours.→ https://revify.com/demo
Ryan Dolley and I record from the historic Guardian Building in Detroit to talk about building a data career away from the coastal AI bubble, and why Detroit's comeback energy makes it a city worth watching. 🎙️ SPONSORS Revify - surprise Snowflake bills? One customer cut theirs 50% in 48 hours.→ https://revify.com/demo
Back from months on the road across Asia, Europe, and the US, I unpack the mood I kept running into: uncertainty. Energy shocks, supply chain chaos, and AI upending the playbook for vendors and practitioners alike. Plus updates on my book and an upcoming Salt Lake City conference. ------------------ This episode is sponsored by Revefi, who gives you full cost and performance visibility for Snowflake by warehouse, user, and workload. One team cut Snowflake costs ~50% across 711 warehouses in under 48 hours. Book a demo at revefi.com/demo . ------------ Timestamps 0:00 — Intro & travel recap — Sets the stage: months of globe-trotting across Asia, Europe, and the US 1:10 — Global uncertainty & resource scarcity — Fuel/water shortages in Southeast Asia, flight cancellations in Europe, ripple effects of geopolitical tensions 5:30 — AI dominates every conversation — The #1 topic at conferences worldwide; vendors facing existential questions and forced to rethink everything (Atlan pivot, DuckDB agent idea) 10:14 — AI's impact on workers at every level — Senior practitioners gaining superpowers, juniors worried about jobs, leaders expected to do more with less 17:51 — Key takeaway: everyone feels behind — Even top AI insiders are uncertain; give yourself grace, upskill, and consider building something for yourself 20:38 — Announcements — Book drops July 27th, course coming, Practical Data Community Newsletter live, fall travel schedule (London, Paris, possible Salt Lake City conference)
