I’m back! After about 7 years (or more) of bi-weekly publishing, I gave myself a break (to have the flu, in part), but now it’s back to business! In 2026, I’ll be focusing the podcast more on the commercial side of data products. This means more founders, CEOs, and product leader guests at small and mid-sized B2B software companies who are building technically impressive B2B analytics and AI products. With all the focus on AI, I want to focus on things that don’t change: what do value and outcomes look like to buyers and users, and how do we recreate it with analytics and AI? What learnings and changes have leaders had to make on the product and UI/UX side to get buyers to buy and users to use?
So, that brings us to today’s episode. Today, I’ll explain why I think model quality, analytics data, and raw AI capability are quickly becoming commodities, shifting the real challenge to how effectively companies can translate their data and intelligence into value that buyers and users can clearly understand and defend.
I dig into a core tension in B2B products: fiscal buyers and end users want different things. Buyers need confidence, risk reduction, and defensible ROI, while users care about making their daily work easier and safer. When products try to appeal broadly or force customers to figure out how AI fits into their workflows, adoption breaks down. Instead, I make the case for tightly scoped, workflow-aware solutions that make value obvious, deliver fast time-to-value, and support real decisions and actions.
Highlights/ Skip to:
- Refocusing the trajectory of the show for 2026 (00:31)
- Turning your product’s intelligence into clear, actionable solutions so users can see the value without having to figure it out themselves (4:32)
- You’re selling capability, but buyers are buying relief from a specific pain point (7:33)
- Asking customers where AI fits into their workflow is poor design (16:57)
- Buyers and users both require proof of value, but in different ways (20:05)
- Why incomplete workflows kill trust (24:18)
- The importance of translating technical capability into something a human is willing to own (30:09)
