Data in the D

John K. Thompson has spent 38 years in AI, data and analytics at IBM, Dell and EY, where he led AI and built what EY called the world's largest private, secure gen AI environment. He grew up in Marlette, in Michigan's Thumb, has written five books on AI and teaches at the University of Michigan.

Ryan Dolley and Aaron Wilkerson talk with him about AI from the Midwest, where companies make trucks, coats and chemicals, not software. A little more reality, a little less hype.

We cover:

- Why everybody feels behind on AI, and why that means nobody is

- Context engineering as nested prompts: company, department, process and personal

- What an agent harness actually is. It's control and governance, inner and outer loops you've probably already built

- The five families of AI – generative, predictive, symbolic, causal and physical – and why stringing them together beats one giant agent

- What gen AI is genuinely good at, and where people misuse it

- Why AGI and recursive self-improvement aren't two weeks away

- One practical money-saver: drop back a model version or two and cut your token bill

- John's advice for students: be AI fluent, not just AI literate

Data in the D Conference is October 16–17 in downtown Detroit, with workshops, demos and a hackathon on Friday and five tracks of talks on Saturday. Agenda and tickets at datainthed.org.

What does it actually take to write a tech book? Aaron Wilkerson turns the mic on co-host Ryan Dolley to talk about writing his forthcoming Wiley book, Building Business Intelligence Apps with AI. From landing a publisher and understanding royalties to surviving edits and finding time to write, Ryan shares what aspiring authors should know before signing a contract. Plus: why he built a BI dashboard to track his own writing deadlines.

Everyone who's been to a good data conference has thought about starting one. Almost nobody knows what's actually involved.

Ryan and Aaron are joined by Stephanie Saville, the nonprofit event planner behind the Data in the D conference, for a soup-to-nuts look at how it really got built — including the parts that don't make the highlight reel.

We get into: why you need a community before you need a conference; the chicken-and-egg problem of putting down a venue deposit with zero dollars in the bank; choosing between a ticket-funded conference and a sponsor-funded one, and what that decision does to everything else; how sponsorship actually works, including why sponsors now want attendee job titles before they'll write a check; and why the sessions — the part everyone wants to talk about — are the easy part.

Plus the details nobody plans for: shipping vendors' boxes home after the show, a keynote whose travel falls through the day before, a two-hour AV check that turns into six, and the single loudest piece of attendee feedback we got in year one. (It was the coffee.)

Tickets for this year's Data in the D conference: dataintheD.org

Detroit's data community goes home for this one. Ryan and Aaron are joined by Mary Wilkerson (theology teacher with 25 years working with adolescents — and Aaron's wife) and John Breyer (Director of Partnerships at Longbeard, the Catholic AI company behind Magisterium AI) to talk about what AI is actually doing to kids in classrooms and living rooms.

What we cover:

- Why students genuinely don't consider AI use cheating, and the "write it like a fourteen-year-old so I get a B" trick teachers can't catch

- John's four real concerns for K-12: academic honesty, disrupted learning, distortion, and kids starting to sound like the machine

- The MIT "Your Brain on ChatGPT" study everyone got wrong: AI layered on a trained brain is a superpower; AI instead of one is a disaster

- Oral exams, note cards, and why AI is pushing schools back to analog assessment

- Building AI for 2,000 years of Church documents: RAG over 32,000 sources, digitizing books in Rome, and training the first Catholic language model

- Parenting in practice: The Anxious Generation chapter summaries, paid "internships" for your 12-year-old, and why virtue beats skills when you can't predict the job market

Data in the D is the official podcast of Detroit's data community.

This week on Data in the D, Ryan Dolley and Aaron Wilkerson sit down with Harini Rajagopal from AAA Life, Pete Cooney from Jackson National Life, and Jason Touleyrou from Parable to talk about what’s really happening in data engineering.

Cloud modernization, AI pressure, cost control, ontology, enterprise architecture, and the messy reality behind the hype straight from practitioners building this stuff in the real world.

Is the data job market broken — or just reshuffled?

The vibes are all over the place. Some people have tons of opportunities; others have been job hunting for six months. What separates the two camps?

Ryan and Aaron sit down with Jeff Wolgamuth and Michael Butts from Birchworks, a 19-year executive search firm specializing in data engineering, data science, and AI placements, to get the real story on what's happening in data hiring right now.

We dig into:

- Where the demand actually is (and where it isn't)

- Why listing tools on your resume doesn't cut it anymore — and what to show instead

- The three things employers want to see from every candidate

- How fraud is reshaping the hiring process

- What it takes to break into leadership — and why the CDO role has fundamentally changed

- Compensation trends: who's getting raises and who's getting squeezed

- The fractional career path and why PE firms can't get enough of it

- Honest advice for juniors entering a brutal entry-level market

- Emerging trends: RLHF, frontier LLM certifications, and what's next

Whether you're actively job hunting, thinking about your next move, or just want to know where the market is headed, this one's for you.

Guests: Michael Butts (CEO) & Jeff Wolgamuth (Senior Recruiter), Birchworks — birchworks.com

What's it like trying to build a data career in 2026? Lilah Kole is 26, based in metro Detroit, and has already stacked an impressive resume — from decision science at IPG Media Brands to Power Platform development at Webasto and Agri, with stops at startups and steel companies in between.

Ryan and Aaron sit down with Lilah to get the perspective that most data podcasts miss: what it actually looks like from the early-career side.

Topics covered:

- Navigating the data job market as a young professional

- Why networking (not job boards) landed almost every one of her roles

- AI as a second language — why some peers lean in and others resist

- The environmental and ethical concerns her generation has about AI

- Building a content brand around data, tech, and finance on YouTube

- Which social platforms actually matter (YouTube > everything)

- Generational differences in workplace culture and professionalism

- Advice for early-career data people who are struggling right now

- Wayne State, Detroit pride, and the hustle culture that shaped her career

Lilah's take: "The people who avoid emerging tech and aren't willing to learn about it are the ones who get left behind."

Find Lilah on YouTube and LinkedIn — just search Lilah Kole.

Scott Smith has spent 20 years leading analytics consulting at Wit Solutions in Detroit — from the Business Objects and Qlikview days through Power BI and now AI. In this episode, we dig into why just being "a data person" won't cut it anymore, what mid-market companies actually need from their data teams, how vibe coding is shaking up enterprise consulting, and Scott's blunt advice for new grads worried AI is coming for their careers. Plus: why Detroit's data scene is slower than the coasts — and why that's about to change.

The founders of Data in the D share the story behind Detroit’s fastest-growing data community—why it started, how the conference came together, and what’s next for analytics data leaders, engineers, and BI teams in the Motor City. Follow us at datainthed.org

Featuring Aaron Wilkerson, Ryan Dolley, Jason Touleyrou and Dom Leo.