The Joe Reis Show

What I'd Do As a Junior Candidate in Mid-2026. Freestyle Fridays (June 26, 2026) 26.06.2026 21min

I get asked by junior-level graduates and candidates in data engineering, analytics, and data science about what to do to succeed in today's challenging job market. With AI rapidly changing employer expectations, there's understandably a lot of anxiety today, particularly among juniors.In this Freestyle Friday, I answer in terms of what I'd do if I was a junior candidate today - the necessary tech and personal skills, my top 5 traits in a candidate, and building one's network.Obviously I can only speak from my perspective, but hopefully there's some helpful advice here.-----------------------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

From Airflow to AI Agents: Maxime Beauchemin on Building Agor and Running a Company with AI Agents 25.06.2026 46min

Maxime Beauchemin, the creator of Apache Airflow and Apache Superset, joins the show to discuss his transition from data engineering to the frontier of AI. Max shares the origin stories of his massive open-source projects, detailing how Airflow was born at Airbnb out of a need for better data orchestration. He also explains his shift toward user interfaces with Superset and the founding of his company, Preset. We then shift to the future of software development. Max dives deep into his recent "Claude Code moment" and introduces Agor, his new command center for agentic workflows. Discover how his team is using persistent AI agents to automate everything from deal desks and legal reviews to automated bug bashing and QA testing. Finally, the discussion explores the tech singularity, the concept of a "software utopia," and how awesome hobbies like mountain biking and e-foiling will fit into an automated world.Agor: https://agor.live/

The AI Boom (and Bust?) Cycle: Lessons from the Gold Rush. Freestyle Fridays (June 19, 2026) 19.06.2026 11min

Finished a jog on the high plains near South Pass, Wyoming, where there's a lot of history. Standing near the old Oregon and Mormon trails, I look at the remnants of the 1800s gold rush to draw parallels to the current AI boom.

The Missing Half of AI: Context, Agents, and the AI-Native Enterprise w/ Prukalpa Sankar (Atlan) 11.06.2026 52min

In this episode, I sit down with Prukalpa Sankar, the founder of Atlan, to discuss the missing piece that makes artificial intelligence actually useful in the enterprise: context. We dive deep into building the "second brain" of a company, the reality of agent development, and how to transition a traditional business into an AI-native organization. If you're looking to understand why your AI agents are getting abandoned in testing hell or how the roles of data and engineering are fundamentally shifting, this is the conversation for you. As always, we keep it practical and grounded. No hype, just education from the front lines of data architecture.What an Enterprise Context Layer Actually Is (Prukalpa's new article): https://www.linkedin.com/pulse/what-enterprise-context-layer-actually-prukalpa--avdqc/?trackingId=kq8lIdYdRnKsHu%2BdREYB3Q%3D%3DTimestamps01:15 - The missing half of AI: Contextual intelligence 02:15 - Reverse engineering business context and the second brain 05:06 - Escaping testing hell and hitting the 80% accuracy threshold for agents 07:54 - Simulating context for analytics use cases 11:34 - Does data quality matter for AI agents? 15:37 - Capturing tacit knowledge and human expertise 21:08 - The organizational chart of the future and "E-shaped" humans 26:26 - How Atlan transformed into a completely AI-native company 34:22 - Banning engineers from coding and the new mental model for work 39:05 - Societal resistance, historical context, and embracing technological change 46:00 - Optimism, childlike curiosity, and the path forward

Snowflake Summit 2026 Recap, Avoiding the Semantic Swamp, and more w/ Juan Sequeda 09.06.2026 51min

Juan Sequeda stops by after a massive month on the road to unpack the latest industry shifts, including takeaways from the Snowflake Summit. We dive into the real state of AI agents in the enterprise, separating the hype from the reality of adoption. We also explore the dangers of creating a "semantic swamp," (cousin of data swamps) the shifting landscape of vendor strategies with the rise of the modern monolith, and why data teams need to accept that getting work done (not data) is the true center of the universe. Finally, we discuss why pragmatism beats pedantry every time when building data architecture.🎙️ SPONSORSRevify - surprise Snowflake bills? One customer cut theirs 50% in 48 hours.→ https://revify.com/demo

Data Work in the Real World (Detroit Edition) w/ Ryan Dolley. Freestyle Fridays (June 5, 2026) 05.06.2026 13min

In this Freestyle Friday episode, Ryan Dolly and I record straight from the historic Guardian Building in downtown Detroit to talk about life, tech, and data outside the San Francisco bubble. We had an amazing time connecting at the Data in the D town hall and exploring a city undergoing massive revitalization. Detroit was once the Silicon Valley of its time, peaking at nearly 1.9 million residents. Now, the city has a tangible "comeback" energy, moving past its history of empty fields and boarded-up buildings to build something entirely new. We discuss why building a career away from the coasts offers incredible lifestyle advantages, especially if you want to avoid the hyper-focus on AI software tools and work with real-world physical assets like automotive, mobility, and robotics.I'm excited about Detroit's potential and plan to spend more time here.🎙️ SPONSORSRevify - surprise Snowflake bills? One customer cut theirs 50% in 48 hours.→ https://revify.com/demo

Notes From the Field: AI, Energy Shocks & the End of the Old Playbook. Freestyle Fridays (May 29, 2026) 29.05.2026 24min

It's been a few months on the road, bouncing through San Francisco a bunch, across Asia and Europe, and a quick stop in Detroit. In this audio-only Freestyle Friday I unpack what I've been seeing out there. If I had to pick one word for the mood worldwide, it's uncertainty: energy and supply shocks rippling out of the Middle East, fuel and resource shortages, flights getting canceled with no notice, and AI scrambling the playbook for vendors, practitioners, and leaders alike.I get into why so many data tooling companies are quietly having existential conversations, how Atlan tore its product down to rebuild AI-native (a full conversation with Prukalpa is coming next week), and a fun experiment I shipped this week with DuckDB Quack.I also dig into the split I keep seeing: senior practitioners getting superpowers while juniors face a brutal job market, leaders being asked to do far more with less, and why I think the industrial-age org chart is finally on its way out.Plus some personal updates: the new book is now targeting late July and a companion course is on the way.Finally, I'm mixing audio and video formats going forward (Freestyle Friday will probably be mostly audio), the Practical Data Community newsletter is live, and there's a Salt Lake City conference brewing for late January. Lots in the hopper...------------------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.------------Timestamps0:00 — Intro & travel recap — Sets the stage: months of globe-trotting across Asia, Europe, and the US1:10 — Global uncertainty & resource scarcity — Fuel/water shortages in Southeast Asia, flight cancellations in Europe, ripple effects of geopolitical tensions5:30 — 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 less17:51 — Key takeaway: everyone feels behind — Even top AI insiders are uncertain; give yourself grace, upskill, and consider building something for yourself20:38 — Announcements — Book drops July 27th, course coming, Practical Data Community Newsletter live, fall travel schedule (London, Paris, possible Salt Lake City conference)

How AI Agents Are Changing the Data Consultancy Game w/ Chris Tabb (Confluent Current London 2026) 29.05.2026 23min

If you're a consultant and you're not using AI agents yet, your competitors are. No surprise, but they're delivering faster, cheaper, and better than ever.Chris Tabb, founder of LEIT Data, joins me live at Confluent Current London 2026 to talk honestly about how AI agents are reshaping the consultancy model, from billing structures and team rollouts, to building internal tribal knowledge and outpacing firms that are still staffing up the old way.Timestamps:0:33 — How Chris is Going Agentic1:56 — Token Maxing Leaderboards5:26 — AI Agents: Year-Over-Year7:08 — Tagile: Agentic Development9:00 — AI in Consultancy17:22 — Prompt Management & Context Quality

Why You Feel Behind in AI (And Aren't) w/ Eric Weber 27.05.2026 49min

Everyone in tech is telling you to go faster. Eric stepped away from his role to do the opposite.In this conversation, we get into why so many people feel like they're falling behind in AI, and why that feeling is mostly manufactured. Eric makes the case that we're miscalibrated: assuming what's true for the 0.1% (the SF AI inner circle) is true for the 10%, when by definition almost no one is keeping up with that group. We talk about why judgment, not throughput, is the real bottleneck right now, why most AI products feel boring even as code output explodes, what the "flatten the org" experiments are actually measuring (spoiler: yesterday's stock price), and why people are leaving corporate roles at a rate that's hard to ignore.We also get into the parts nobody wants to say out loud: layoffs by email, the gap between who people are in private vs. on LinkedIn, the ghost routines after you leave a job, and what walking around San Francisco actually feels like when every billboard is AI and every person you pass looks depleted.If you've felt the FOMO and wondered whether the problem is you or the framing, this one's for you.Eric Weber is a data and product leader formerly at Grammarly, Yelp, LinkedIn, and Stitch Fix.

Why AI Agents Are the New Consumers of Data with Tristan Handy (CEO @dbt Labs) 20.05.2026 47min

In this episode, Tristan Handy and I sit down to unpack a massive shift coming to the data industry: over the next 12 months, the primary consumers of data won't be humans. They will be AI agents. We dive deep into what this means for data infrastructure, compute costs, and the tools we use every day. We also talk about processing high-volume agent queries, building "context stores", and why the industry shouldn't just build "horses with wheels" when designing agentic data engineers. We also take a fun detour comparing the current AI landscape to the early days of dial-up modems and Mosaic browsers , and discuss why stepping away from the screen and going old-school might be the ultimate productivity hack.

Why 90% of Data Teams Are Failing at Modeling - Freestyle Friday (May 15, 2026) 15.05.2026 16min

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.Freestyle Friday, May 15, 2026Walking around Salt Lake City and unpacking the April 2026 data modeling survey results (334 respondents). Across three surveys now: January's State of Data Engineering (1,100), March's AI usage poll (193), and April's data modeling deep-dive. Not surprisingly, the same two pain points keep surfacing: time pressure and lack of clear ownership.90% of respondents have a data modeling pain point. When asked what would actually help, only 4.8% wanted better tools. Training, business requirements, time, and ownership crushed tooling in the rankings. Will AI improve things or make them worse? Time will tell...Also covered:Why physical data modeling has become the default (and why that's a problem)Data modeling vs. schema design - they're not the same thingSemantic layers (yay or nay?), Lloyd Tabb, and MalloyConway's Law, Reis's Law, and what changes when org charts get flattened by AIWhy leadership is under more pressure than everThe June half-year survey is coming🎙️ SPONSORSFivetran - stop cobbling pipelines together. Set it, forget it, scale as you grow.→ https://fivetran.comRevify - surprise Snowflake bills? One customer cut theirs 50% in 48 hours.→ https://revify.com/demo

The Hidden Costs of AI Agents & Cloud Data with Sanjay Agrawal (Revefi, co-founder ThoughtSpot, MS) 14.05.2026 52min

Are AI agents silently draining your cloud data budget? With the rise of consumption-based pricing and autonomous AI queries, data teams are facing a perfect storm of skyrocketing costs and operational chaos. In this episode, I sit down with Sanjay Agrawal, CEO and Co-founder of Revefi, to discuss the intersection of data engineering, cloud warehouse optimization, and FinOps in the age of AI.We chat about how legacy on-prem habits are bankrupting modern data platforms, why query optimization is more about ROI than just speed, and how AI agents are changing the landscape of data consumption. Sanjay shares his deep expertise from building world-class databases at Microsoft and ThoughtSpot, revealing how to automate cost management and performance tuning for Snowflake, Databricks, and BigQuery.Key Topics:The evolution of cloud data warehouse pricing and why it breaks traditional budgets.How AI agents are causing massive, unpredictable spikes in compute spend.Real-world horror stories of ""lift and shift"" cloud migrations.Why database benchmarks focus on speed but ignore the actual ROI of data.The future of open table formats (Iceberg) and multi-engine routing.

Zach Wilson - Data Engineering in 2026, Traveling, and more - Freestyle Fridays - May 8, 2026 09.05.2026 10min

Zach Wilson and I happen to be in Stockholm, Sweden, this evening. In this Freestyle Friday chat, we talk about what it takes to be a data engineer in 2026 and much more.

AI Agents Can't Fix Data - Josh Wills on Where AI Breaks in Data Engineering 07.05.2026 55min

Josh Wills has spent 25 years writing data pipelines, with a career spanning Cloudera, as Director of Data Engineering at Slack, on the dbt DuckDB adapter, and now training foundation models at Datology AI. He uses coding agents every day. And he keeps running into the same wall: the agents jump to conclusions, fix the wrong thing, and ship pipelines no one understands.In this conversation, we unpack why AI agents struggle with the messiest, highest-stakes parts of data work, and what it means for the engineers managing them.We get into:- Big Data is back- Why AI agents jump to conclusions on benchmarks and complex bottlenecks- The $200K vibe-coded pipeline problem nobody wants to talk about- Why there's no training data for the gnarly enterprise pipelines that actually power businesses- "We're all managers now" - managing unreliable agents like managing unreliable people- Wicked problems and the limits of intelligence- Why politics is the last human endeavor to fall to LLMs (the data is never written down)- Whether classical ML still has a place (yes)- What Josh would tell a new grad starting in data today

TOKENMAXXING IS FOR FOOLS - Freestyle Friday (May 1, 2026) 01.05.2026 25min

Stop Tokenmaxxing and step off the AI hamster wheel. Welcome to another Freestyle Friday! What's the overwhelming vibe in the AI zeitgeist? "If you aren't maxing out AI every second, you're going to be left behind." Therefore, Tokenmaxxing is the way, right?I strongly disagree. We're burning ourselves out with fake productivity and a graveyard of abandoned AI-generated projects.In this episode, I talk about my new minimalist travel setup, why I'm purposefully trying to minimize my AI usage for deep cognitive work, and what skills will actually get you left behind (hint: it's not missing the latest model release).Solve real problems. Focus on the fundamentals. Take a walk. You're going to be fine.

Why Snowflake Bought SelectStar - and What "Data Catalog" Means Now w/ Shinji Kim 30.04.2026 46min

Shinji Kim, founder of SelectStar (acquired by Snowflake in December), joins the show to discuss the deal, the integration into Snowflake's Horizon catalog, and where data cataloging is actually headed.We get into the weeds on a claim Shinji makes early: in a few years, we may stop calling these things "data catalogs" at all. The category is evolving into an AI context layer, a living surface that combines metadata, semantic models, business glossaries, and ontologies, continuously updated by both humans and agents. Shinji walks through how SelectStar built toward this with semantic model management, MCP server support, and an AI agent that started serving data analysts and eventually answered business users' questions directly.We also dig into where data catalog implementations go wrong (spoiler: it's almost always adoption, not tooling), why marketing teams are an underrated ETL persona, and what it actually took to get acquired by Snowflake after three years as a premier partner.Plus: if Shinji were starting SelectStar today, what would she do differently? We talk about distribution in the AI era and how the startup playbook is mutating.Connect with Shinji:LinkedIn — https://www.linkedin.com/in/shinjikim/

WTF is a Software Moat in 2026? - Freestyle Friday (4/24/2026) 24.04.2026 17min

AI has completely inverted how we build and scale software, which begs the question: What exactly is a moat anymore? In this Freestyle Friday, recovering from jet lag and hiking through the beautiful hills of Salt Lake City, I’m breaking down a recent conversation with a VC friend about defensibility in the era of coding agents. I also look at this through Charlie Munger’s lens of "inversion" to figure out what isn't a moat anymore (spoiler: thin foundation model wrappers, "AI", and feature velocity are dead).I also dive into what is defensible today, from mission-critical systems of record like DuckDB and Postgres, to personal branding, to shifting SaaS pricing from per-seat to per-token.

The Future of Open Data Infrastructure with George Fraser (CEO of Fivetran) 23.04.2026 39min

Are vendors trying to lock down your data? In this episode, George Fraser breaks down why the "modern data stack" has evolved into "open data infrastructure". We discuss why data gravity is the most overrated concept in data management, how egress charges are often misunderstood due to poorly designed pipelines, and why companies must insist on having a true replica of their own data.George also shares his hands-on experience with AI coding agents, including how he manages his USTA tennis team with bots like OpenClaw and NanoBot.

We're in 1905: Why Electricity (Not Dot-Com) Is the Right AI Analogy - Freestyle Friday, 4/17/2026 17.04.2026 15min

Walking through Tokyo and breaking down the reality of the AI revolution. In this Freestyle Friday from Shibuya Crossing, I look past the current AI hype cycle to examine the real bottlenecks of AI adoption. Is the current AI boom just a repeat of the dot.com bubble? Why is simply buying Copilot subscriptions for your team failing to move the needle?Drawing parallels to the 40-year adoption curve of the electric grid, I discuss why most AI projects fail to get traction in the enterprise. Hint: it's not the technology, it's the organization. Plus, a look at the danger of firing employees before capturing their tacit knowledge, and how to actually rewire your business to be AI-native.

The Godfather of Data Governance: Bob Seiner on Data vs AI Governance, and The Data Catalyst Cubed 14.04.2026 52min

In this episode, I sit down with Bob Seiner, a true pioneer who has been working in data governance since before it was even called governance. We dive into why he calls BS on the trendy term "data enablement" and how his trademarked approach, Non-Invasive Data Governance, formalizes what organizations are already doing without beating employees over the head.We also unpack his latest concept, The Data Catalyst Cubed, and get into a fascinating discussion about the precarious state of data security in the age of LLMs and autonomous AI agents like OpenClaw. Plus, Bob shares some great war stories about building the T-DAN newsletter using Microsoft FrontPage back in 1997 and drops his best advice for standing out and building a personal brand in the noisy data industry.Where to find Bob:KIK Consulting: kikconsulting.com LinkedIn: / robert-s-seiner-445313 Books: Non-Invasive Data Governance and The Data Catalyst Cubed