The Joe Reis Show

Former Gartner VP Analyst and principal at SanjMo, Sanjeev Mohan, joins me to break down the reality of AI adoption, data foundations, and why enterprises are hitting roadblocks with agents and LLMs. From comparing the current AI boom to the dot-com era to unpacking his new concept, ECL (Extract, Context, Link), Sanjeev explains why moving data around is no longer viable and why "there is no AI stack, only one stack." We also dive into capability overhang, artificial guardrails, the race to standardize semantic context, and why writing books and understanding core primitives still matter in the age of generative models

This week at dbt Summit, Tristan Handy (co-founder of dbt) asked me why I write books. It's a good question, especially today when reading is declining and any answer is seemingly at your fingertips.

In this Freestyle Friday, I discuss why I write books, why they still matter, and much more. If you're interested in writing a book, this episode is definitely a must-listen.

I talk to executives and practitioners around the world about AI and what comes next. Everyone has predictions and pontifications, and everyone seems to think someone else has the answers.
But the more conversations I have, the clearer it gets that nobody knows what's next.
In this episode, I explore that uncertainty and how we move forward anyway.
Because in the end, nobody knows...

In this episode of The Joe Reis Show, I catch up with my good friend Christophe Blefari, co-founder of NAO, to dig into what's actually happening on the front lines of AI agents and data engineering. We talk about the evolution from building SQL IDEs to agentic analytics harnesses, how prompt-driven workflows are reshaping data teams, and why age-old problems like data discovery, modeling, and documentation are suddenly roaring back. We also dive into the risks of "token slop," whether data and software engineering roles are destined to merge, Christophe’s take on DuckDB’s acquisition by AWS, and the realities of building AI tools across Europe and the US.Nao: https://getnao.io/

In this episode, I sit down with Sami Hero, CEO of Ellie.ai, to talk through the evolution of data modeling and why foundational conceptual modeling is more critical now than ever. With the explosion of AI agents, LLMs, and semantic layers, many teams assume they can bypass data modeling and just let an AI infer meaning directly from raw tables.
We dig into why that mindset leads to bad decisions, how companies end up with 15,000 Snowflake tables and thousands of unmaintained dashboards, and why defining core business concepts is the real prerequisite for reliable AI. We also discuss the resurgence of ontologies, lessons from old-school methodologies like MERISE, and how to balance speed with sound architecture.