The Joe Reis Show

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.

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

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

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.

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.

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

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/

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.

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

Wes McKinney is back to discuss his complete transition from AI skepticism to becoming heavily "locked in" on coding agents.Wes shares how he overcame his initial "existential dread" about the future of software engineering and completely rebuilt his personal productivity stack using tools like Claude and Codex. We dive deep into the reality of coding agents, why he believes Go has become the ultimate language for AI agents, and how he manages massive, multi-agent workflows to build production-level software without touching DevOps. Wes also breaks down his mission to fight the platform decay of services like Gmail by building his own local data sovereignty tools.

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 deep into how he’s using dynamic ontologies to extract high-fidelity insights from unstructured data, like the nuances of a 60-minute sales call—to drive massive ROI.In this episode, we explore:- The "SaaSpocalypse" and the Future of Agents: Why the early stages of the sales cycle might soon be a "dance" between AI buying and selling agents.- Sales as Athletics: Why high-stakes negotiation is more like football than a desk job.- The "Business Brain": Moving beyond simple CRMs to a central strategy engine that understands every department’s unstructured data.- Human-to-Human Trust: Why large contracts will always require a human touch, even in an AI-saturated world.- Amit’s perspective on how AI can deliver real value to the GDP by fixing the "distribution bottleneck" of innovation is a must-listen for anyone in tech, data, or leadership.

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 broader management failures.Gowtham shares his firsthand experience navigating an astounding $1 billion AI investment during the early adopter rush of 2024. He details the chaotic first six months of that initiative and the multi-dimensional framework his team developed to measure true return on investment beyond the traditional, and often flawed, software implementation mindset. From the massive risks of pasting PII into LLMs to how AI prototyping is finally bridging the historic gap between product and engineering teams, this conversation is a masterclass in pragmatism for anyone looking to cut through the AI hype, especially in highly regulated industries.

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 creation pipeline, from the bizarre rise of AI OnlyFans to the "Doorman Paradox" of automated content. Finally, we spill some serious inside baseball on the tech sponsorship game, calling out the sheer audacity of heavily-funded startups expecting free labor from communities , and why protecting your reputation is worth more than any quick paycheck.