Common Sense Data
Juha Korpela, Eric BrodaWritings on data that (should) make sense. Tackling the difficult non-technical problems relating to data modeling, data governance, data team operating models, and many more!
| Platform |  | Pricing | Only free issues | Publishes | Weekly |
|---|---|---|---|---|---|
| Issues | 21 | Founded | a year ago | Last Issue | 5 days ago |
| Active | |||||
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Semantics for the Emerging Enterprise Agent Ecosystem
This article is a collaboration between Eric Broda and Juha Korpela. It’s published on both our Substacks, Agentic Mesh and Common Sense Data.
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We hear a common refrain: today’s coding agents, and soon agents...
Understanding Value Delivery with Three Categories of Data Products
The one thing we are really, really bad in this data & AI industry of ours is figuring out business value. This is to a large degree because of our chronic inability to cross, or in most cases to even consider, the last mile from “a dataset...
Notes from Data Mesh Live 2026
One of my favourite conferences (besides Helsinki Data Week, of course1) is Data Mesh Live in Antwerp, Belgium. The content, the people, the atmosphere, and the slick practical arrangements all “mesh” together in what can only be described...
Building Semantics with Conceptual Models
Data consumers need to understand what they are consuming. This was always true, way before AI agents. I’ve been practicing, speaking, writing, teaching, and learning continuously more about conceptual modeling for well over a decade now, a...
Solution-level Thinking is Killing Us
It’s cheaper, faster, and easier than ever to produce solutions to various problems. Tell Claude what you want, and it is done; we have entered an era of abundance for software. The economics of this post-scarcity world1 are both enthusiasm...
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Authors
The writers behind this newsletter.
Data modeling enthusiast & independent consultant at Datakor Consulting
We discuss enterprise-grade agents operating in an enterprise-grade ecosystem at fleet scale, with trust, control, and traceability. Our goal: to explain how agents find one another and safely collaborate, interact, and transact at scale.
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