The Joe Reis Show
Joe Reis, a best-selling author and recovering data scientist, hosts this podcast where he shares candid thoughts on the data, tech, and AI industry. Each week, he broadcasts from wherever he is in the world, sometimes solo ranting and other times chatting with smart people he knows. The show offers an unfiltered perspective on the state of AI, data, and tech.
Episodes
The Mixed Model Arts Manifesto
I discuss the The Mixed Model Arts Manifesto. That's it. That's the show.
Agentic Analytics and the Death of Dashboards? | Oliver Laslett (CTO of Lightdash)
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
The Great Recomposition: Why Everything is Blurring Together
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 m
Stop Overpaying for AI! The Rise of Small Open-Source Models w/ Daniel Svonava (Superlinked)
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
The "X Is Dead" Fallacy
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 evol
Building Real AI Systems: Inside "Architected Intelligence" with Jacob Miller and Jeremy Mumford
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 impor
My Podcast is Invitation Only. Please Stop Spamming Me.
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 th
The Post-Literate Engineer
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, wh
The AI Backlash Is Real! - AI Journalist Sharon Goldman on Data Centers, Hype, the Future of Writing
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 invitati
The Data Engineering Lifecycle & Undercurrents - Mental Model Mondays
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
Why AI Agents Are Replacing Traditional Data Engineering w/ Matt Glickman
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 dat
Conway's Law - Mental Model Mondays
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.
Party's Over. The AI Market Is Entering Its Accountability Phase
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
The Database Is Not the Data Model
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
Why 80% of AI Projects Fail & How to Build an AI-First Company - Steve Brown (AI Futurist)
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 integra
The Data Anarchy Tax: Why No One Owns Your Data
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: FivetranWith the rise of AI and agents, having centralized, trustworthy data is
How I'm Actually Using AI to Write a Book
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.: htt
Is AI Replacing Data Engineers? - Kirill Bobrov (Luminousmen)
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/
What I'd Do as a Junior Data Engineer in 2026
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
Max Beauchemin on Agentic AI and His Claude Code Moment
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.
The AI Boom Looks a Lot Like the Gold Rush
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.
Why Your AI Agents Die in Testing - Prukalpa Sankar, Atlan
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.
The Semantic Swamp: Snowflake Summit 2026 Recap - Juan Sequeda
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..🎙️ SPONSORSRevify - surprise Snowflake bills? One customer cut theirs 50% in 48 hours.→ https://revify.com/demo
Building a Data Career Outside the Coasts - Ryan Dolley
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.🎙️ SPONSORSRevify - surprise Snowflake bills? One customer cut theirs 50% in 48 hours.→ https://revify.com/demo
AI, Energy Shocks, and the End of the Old Playbook
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
How AI Agents Are Changing Data Consulting - Chris Tabb
Chris Tabb, founder of LEIT Data, joins me live at Confluent Current London to talk honestly about how AI agents are reshaping the consultancy business model, from billing structure to internal knowledge management.
Why You Feel Behind in AI (and Aren't) - Eric Weber
Eric Weber makes the case that the feeling of falling behind in AI is mostly manufactured. We're miscalibrating what's true for the top 0.1% in San Francisco against everyone else. We get into judgment as the real bottleneck, and why so many people are quietly leaving corporate roles.
Tristan Handy: AI Agents Are the New Consumers of Data
Tristan Handy and I unpack a shift coming to data infrastructure: within 12 months, the primary consumers of data won't be humans, they'll be AI agents. We dig into compute costs, "context stores," and why the industry shouldn't just build horses with wheels.
Why 90% of Data Teams Are Failing at Data Modeling
NOTE - Sorry for the edits in this video. I used Descript to edit out the umms and uhhs, and it was a bit too aggressive. Will make it less jarring in future videos. Thanks.Walking around Salt Lake City, I break down results from the April 2026 data modeling survey: 90% of respondents have a modeling pain point, and only 4.8% think better tools would fix it. We cover physical vs. logical modeling,
The Hidden Cost of AI Agents on Your Cloud Bill - Sanjay Agrawal
Sanjay Agrawal, CEO of Revefi and co-founder of ThoughtSpot, joins me to talk about how AI agents are quietly driving unpredictable spikes in cloud data spend, and why most FinOps practices are built for a world that no longer exists.
Data Engineering in 2026 - Zach Wilson
Zach Wilson and I happen to be in Stockholm on the same night, so we sat down to talk about what it actually takes to be a data engineer in 2026.
AI Agents Can't Fix Data - Josh Wills
Josh Wills has spent 25 years writing data pipelines. He uses coding agents daily and keeps hitting the same wall: they jump to conclusions and ship pipelines nobody understands. We get into the $200K vibe-coded pipeline problem, and why politics is the last job LLMs will ever touch.
Tokenmaxxing Is for Fools
Everyone says if you're not maxing out AI every second, you're getting left behind. I disagree. I talk about minimizing AI use for deep cognitive work, my new minimalist travel setup, and the skills that will actually get you left behind.
The Future of Data Catalogs --Shinji Kim, Snowflake/SelectStar
Shinji Kim, founder of SelectStar (acquired by Snowflake), joins me to talk about the deal, and why in a few years we may stop calling these things "data catalogs" at all as the category evolves into a living AI context layer.
WTF Is a Software Moat in 2026?
Recovering from jet lag and hiking the hills of Salt Lake City, I break down a conversation with a VC friend about what's actually defensible in the age of coding agents, and what isn't.
The Future of Open Data Infrastructure - George Fraser, Fivetran
George Fraser, CEO of Fivetran, breaks down why the "modern data stack" has evolved into "open data infrastructure," and why data gravity is the most overrated concept in data management.
Why Electricity, Not Dot-Com, Is the Right AI Analogy
From Shibuya Crossing in Tokyo, I make the case that the 40-year adoption curve of the electric grid is a better analogy for the AI boom than the dot-com bubble, and why most AI failures come down to the organization, not the technology.
Data Governance vs AI Governance - Bob Seiner
Bob Seiner has worked in data governance since before it had a name. We dig into his Non-Invasive Data Governance approach, why he pushes back on the term "data enablement," and the state of data security in the age of autonomous AI agents.
Do Data Fundamentals Still Matter in the Age of AI?
From the hillsides of Phuket, Thailand, I push back on the idea that teams "don't have time" for fundamentals anymore, and make the case that AI actually makes data engineering more critical, not less.
Wes McKinney on AI Agents and His Wild Coding Setup
Wes McKinney returns to talk about his complete reversal from AI skepticism to being fully locked in on coding agents, why he thinks Go has become the best language for AI agents, and how he's building his own local data sovereignty tools.
Surviving the AI Grind: Hustle Culture, Fear, and Finding Value w/ Eric Weber (Freestyle Friday Episode)
In this Freestyle Friday episode, I catch up with Eric Weber after our recent walk through downtown San Francisco. We dive deep into the very real fear and identity crises sweeping through the tech industry as AI accelerates. We discuss how packing a year of change into a single week is disorienting workers and how the constant hustle culture in SF might finally be hitting its threshold.We also ge
Why 90% of Your Data is Wasted (and How AI Reclaims It) w/ Amit Prakash
I recently sat down with Amit Prakash, the brilliant mind who co-founded ThoughtSpot and led AI teams at Google and Microsoft, to talk about a massive shift happening in the data world.For decades, we’ve been forcing the "messy reality" of business into rigid database tables, losing about 90% of the actual information in the process.Amit is now building Ampup to flip that script. We dive
Breaking Into Data Engineering in 2026: AI Tools, Standout Resumes, and more w/ Chris Gambill
In this episode, I sit down with Chris Gambill, a data strategy and engineering leader, fractional consultant, and career coach. We dive into the realities of the data engineering job market in 2026, exploring what it takes to stand out, the massive shift AI coding tools are causing, and why mastering the fundamentals of data engineering remains crucial.Chris shares his unfiltered thoughts on coac
AI in Healthcare - The Real-World Realities w/ Gowtham Chilakapati
In this episode, I sit down with Gowtham Chilakapati, an analytics veteran of 18 years and Executive Director at Humana , to pull back the curtain on the reality of Agentic AI in the enterprise.We dive deep into the recent wave of tech layoffs—like the news of Block cutting 40% of its workforce —and debate whether AI is truly driving these decisions or simply serving as a convenient excuse for bro
Freestyle Fridays - AI Changed Everything, Except the Hard Parts
The new Practical Data Community Pulse Survey for March 2026 just came out, and I unveiled some of the findings at yesterday's Undercurrent event in San Francisco. The short version is: AI is here to stay. Everyone's using it, but the hard parts we've always dealt with as an industry still remain unresolved. Listen and find out why.
Inside the AI "Frankenact" Disaster & The Fight for Developers w/ Jake Ward
In this episode, I sit down with Jake Ward, founder of the Application Developers Alliance. We dig into the AI "Frankenact," aka the EU AI Act, and why policymakers regulating tech they fundamentally misunderstand creates a cold wind for software innovation.Jake drops some harsh truths about why giving developers a voice in Washington is harder than it looks, why collective bargaining an
Freestyle Fridays - Thoughts on the Data Job Market, Going Solo, and More
The data job market is evolving, but it's still there. In this episode, I give my thoughts on the data job market, ways to navigate it, going solo and having a Plan B, and more.
Is SaaS Cooked? Why "Local First" AI Agents Are Taking Over w/ Demetrios Brinkmann
In this episode, I sit down with Demetrios Brinkmann (godfather of the MLOps Community) to talk about the absolute Wild West of AI right now. We cover how fast coding agents are changing the game, the reality of "vibe coding" your own CRM , and how Demetrios's community saved $20,000 just by ditching bloated enterprise tools.But we don't just talk tech. We get into the weeds on the content creatio
The Buzzword Industrial Complex, AI Agents & The Future of Data w/ Matt Housley
In this episode, Matt Housley and I reunite for a Friday catch-up, bringing back some of that classic Monday Morning Data Chat energy. We dive into the absurdity of the "buzzword industrial complex," and why declaring it the "Year of Context" is mostly just industry hype, per usual.We also tackle the chaotic reality of deploying AI agents (including the ultimate YOLO, OpenClaw)
The Tech Job Market is Brutal. Is Freelancing Your Plan B? w/ Jody Hesch
The white-collar tech industry isn't what it used to be, and anyone could be on the chopping block at a moment's notice. With tens of thousands of highly skilled people getting laid off from Big Tech on a seemingly bi-weekly basis, competing in the traditional job market is brutal right now.In this episode, Jody Hesch and I discuss why building a freelance data consulting business isn'
The OGs of AI Analytics: Building Data Agents Before It Was Cool w/ Paul Blankley and Ryan Janssen
In this conversation, Paul Blankley and Ryan Janssen, founders of Zenlytic, drop in to discuss the massive shift in how we build software and handle data. We trace their journey from studying early NLP and Transformers at Harvard right when the BERT paper dropped, to building a company that relies on cutting-edge LLMs. As far as I know, they're the first to use LLM's for analytics.We dive
Freestyle Fridays - The AI Skills and Competence Gap
We often hear about the AI skills gap, where people need to get training on the latest AI tools. There's also the AI competence gap, where people might not have the skills or competence in a field, and use AI to mask over those shortcomings. The results are what you expect - chaos. In this episode, I unpack these two gaps, and do my usual ranting about learning the fundamentals and investing i
Are Software Engineers the New Data Engineers? w/ Tim Delisle & Chris Crane (514)
In this conversation, I sit down with Tim Delisle and Chris Crane, co-founders of 514, to discuss bridging the gap between software development and data engineering. We cover their experience leading global data engineering at Nike and why software teams are increasingly taking ownership of heavy analytical workloads.We also dive into how they are building the Moose Stack to give developers a loca
The AI Orchestrator & Building Human-Machine Teams w/ Sadie St. Lawrence
Sadie St. Lawrence joins me to unpack her concept of the "AI Orchestrator," explaining how it shifts our mindset from being a musician to a conductor in the age of AI. She shares insights from her work at the Human-Machine Collaboration Institute (HMCI), detailing how her team is building AI-powered solutions and tackling complex problems. We also chat about the common pitfalls in AI ado
Freestyle Fridays - The Great Data Reckoning
This week, I published an article called "2028, the Great Data Reckoning," which got a ton of response. Although I originally meant it to be satire, when I re-read it I felt like it was actually a glimpse into what's happening in our field right now. In this episode, I chat about the implications of the Great Data Reckoning on practitioners, leaders, and founders. Article: https://jo
Marketing to Developers During the AI Gold Rush w/ Prashant Sridharan
In this episode, I sit down with Prashant Sridharan, a 30-year veteran of developer marketing who has shaped go-to-market strategies for tech giants like Sun Microsystems, Microsoft, AWS, Facebook, and Twitter, and currently runs product marketing at Supabase. We dive deep into the origins of DevRel and how marketing to developers has evolved in an increasingly noisy, AI-saturated landscape.Topics
Freestyle Fridays - The Data Industry is the Definition of Insanity
For 40+ years, the data industry has tried to teach good practices and get adoption, often in the same way. And for 40+ years, that approach keeps failing over and over. Based on the recent Practical Data Community Survey, practitioners face challenges like time pressures, lack of direction, and lack of clear ownership. Do we need to try something else as an industry? Or do we continue to be the p
From ODBC to ADBC: Modernizing the Data Stack for AI and Analytics w/ Ian Cook
Why are we still using row-based protocols like ODBC and JDBC in a column-oriented world? In this episode, I sit down with Ian Cook, co-founder of Columnar and a long-time Apache Arrow contributor, to discuss the critical infrastructure changes needed to speed up modern analytics and AI.We dive deep into the technical bottlenecks of legacy standards - specifically the "serialization tax"
Freestyle Fridays - The State of Data Engineering in 2026, Book Writing, and More
The 2026 Practical Data Community State of Data Engineering dropped this week. It's full of some obvious and very counterintuitive information about the state of data engineers around the globe, in all sizes and types of organizations. Check it out!Also, I talk about the book writing process, where I messed up on this latest book, it's progress toward publication, and more.Survey: https://
Vibe Coding, Agents, and The Future of Streaming Data w/ Paul Dudley and Ricky Thomas (Streamkap)
I sat down with Paul Dudley (CEO) and Ricky Thomas (CTO) from StreamKap to catch up on where the world of streaming data is heading—and things have changed fast since we last spoke.We dive into the concept of "vibe coding" and how AI is radically accelerating how we build software (I even share a story about building a data analysis tool in an hour). But the real meat of this conversation is about
Freestyle Fridays - The SaaS Slump and the Rise of Disposable Software
This week was a doozy with new AI releases, the stock market, and more. It really feels like this was the first tremor in AI's impact on the SaaS market. What's do I think is next? Listen and find out.
Dashboards vs. Agents: Navigating the New Era of BI and Analytics with Mike Driscoll
In this episode, I sit down with Mike Driscoll, founder of Rill Data, to discuss the evolving landscape of business intelligence and data engineering. We explore why the industry keeps "rediscovering" old concepts like the semantic layer and how the rise of AI agents is forcing us to rethink how we structure data.Mike shares his insights on the "shape" of analytics, debating wh
Freestyle Fridays - Why AI (Might) Mean More Work, Not Less
As I use AI, I'm finding that I create MORE work for myself, not less. One task completed means five more to do. This is the paradox of today - AI might actually mean more work, not less. I talk about this, the Data Day Texas final episode, and more.Check out the review I did of Cube's new analytics agent: https://www.youtube.com/watch?v=p3frGJOUl1E(Thanks to Cube for partnering on the rev
"I Needed to Be Back in the Game": Leaving PE & Big Tech to Build Vertical AI w/ Lak Lakshmanan
Lak Lakshmanan had a successful career in Private Equity and Big Tech, but he realized he couldn't just "coach the game" while the rules were changing. He had to get back on the field play it. We discuss vertical AI, the "foolhardiness" required to start a company , the reality of the AI technology wave, and why sitting on the sidelines is the biggest risk of all.LinkedIn:
Freestyle Fridays - The 99% of Businesses and AI, and More.
In this episode, I talk about how I'm kind of living in a bubble of cool tech and AI, and how the 99% of businesses out there are still grappling with the same old data and tech problems they've always dealt with.I also talk about how me and my friends are using AI to automate the boring stuff and scratch our own itches.
Cory Doctorow on Enshitification, The AI Bubble, Reverse Centaurs, and The Post-American Internet
In this episode, I sit down with science fiction author, activist, and journalist Cory Doctorow to unpack his viral concept of Enshitification, the three-act tragedy of platform decay: 1. be good to users 2. lock them in 3. extract value from users to feed advertisers and shareholdersWe also dive into:- The AI bubble: Cory’s case that parts of the sector are propped up by aggressive accounting and
Why Smart Ideas in Tech Keep Failing (And Why We Suck at Selling)
Tech is full of smart people with smart ideas - enterprise data models, ontologies, data mesh, proprietary AI strategies - that repeatedly fail to gain traction. When they fail, the blame usually goes to "stupid users", "lazy and immature organizations." Perhaps, but I don't think that's the whole story, and if you adopt that mindset, you're sure to keep failing.I t
Is the BI Dashboard Dead? Barry McCardel on Hex, AI Agents, and the Future of BI
In this episode, I visited the Hex office and sat down with Barry McCardle (CEO of Hex) to talk about the massive shift we’re seeing in the data stack. Countless companies have spent decades buying BI tools in the hope of "self-serve Nirvana," yet most dashboards still raise more questions than they answer. Barry and I dive into why the traditional dashboard is becoming a "jumping-o
Freestyle Fridays - Status Games
What status game are you playing? Are you trying to outcompete others, or playing your own game? In this episode, I talk about status games in data and careers in general.
A History of Technology & Computing w/ Bill Inmon and Roger Whatley
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 St
Live with Joe Reis - January 2026 AMA. Ontologies, Data Modeling, Data Engineering, and More
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 scienc
Freestyle Fridays - The Law of Leaky Vibes, Making Your First Dollar, and More
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/If you like this podcast, please take 10 seconds and give it a rating or review on your podcast platform of ch
Freestyle Fridays - 2026 "Predictions", Kimball vs Inmon Thoughts, and More
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.
Freestyle Fridays - Have Good Taste and Keep Building
“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
Bootstrapping a Data Consultancy Amidst The Great AI Grift w/ Nikhil Suresh (CEO @ Hermit Tech, Blogger)
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 curre
The "Oh Word" - Why Ontologies Are Suddenly Popular
Oh yeah...ontologies. In this mini-clip from Matt Housley and I, we chat about why ontologies are super popular now.
Freestyle Fridays - The Kids are Alright
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 “clan
The Truth About AI Agents, Hardware Wars, and Mixed Model Arts. Freestyle Fridays w/ Matt Housley
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 ab
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 con
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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