The Person Behind the Products
How a doctorate in ED became a career in AI, and why that path makes more sense than it sounds
I didn't set out to build AI products. I set out to understand how people learn. That's what my doctorate in education was all about — the messy, fascinating question of how humans take in information and actually make sense of it.
Then I spent years watching that same question play out in software. And I noticed something that stuck with me: the technology was rarely the problem. The way information was organized was. When people got lost in a product, it wasn't because they weren't smart enough. It was because someone had structured the experience in a way that made no sense to a real human being.
That realization sent me down a new path. I became a trained Information Architect — someone who thinks carefully about where things go, why they go there, and what happens to people when they don't. And it turns out that skill is exactly what AI needs most right now.
What I Do Today
I'm Dr. Kimberly Dunwoody — Dr. KD to most people. I lead AI product strategy, and my job is to turn tangled, complicated systems into intelligent platforms that work the way people expect them to.
I work across the fast-moving edges of the field: agentic AI, machine learning, and knowledge graphs. I also work in the genuinely uncharted territory of quantum computing, where the rules for how information behaves are still being written as we go.
The tools keep changing. The core challenge never does. Someone has to decide what matters, where it lives, and why a person should care. That's the work I do, and I still find it genuinely exciting.
Why an Information Architect Belongs in AI Right Now
Here's the part most teams miss. Machine learning models and knowledge graphs are, at their heart, about how information relates to other information.
That's not a background detail. That is the product.
Information architecture is the discipline of getting that relationship right — knowing what belongs where, which connections carry real meaning, and what to leave out so the whole thing stays clear. It's what I trained for, and it's why bringing an Information Architect into an AI project early isn't a luxury. It's the difference between a knowledge graph that guides people and an expensive tangle that leaves them stranded.
As AI generates more and more, structure becomes the rare and valuable thing. Someone has to bring order to the abundance. I'm happy to be that someone.
Visit Product Patterns
Product Patterns is where I share the frameworks, observations, and practical ideas that keep showing up in my product and UX work. It’s part working notebook, part resource for leaders and teams trying to turn insight into smarter decisions, stronger design, and better products. If that kind of thinking is your thing,