LLMs hit that sweet spot of mine, that intersection of data and meaning. AI turning zeros and ones into words, statistics becoming story, math becoming meaning.

I started reading the philosophies behind AI development, sitting with the debates, and following both the fears and the celebrations well before the first ChatGPT was released, watching hype cycles come and go. I dove into the platforms as soon each became available, and I continue to use them throughout the day in multiple forms.

I've spent my career translating between creative and technical teams, analytics and storytelling, engineers and executives. It’s the same at my home.

My daughter, an early adopter, immediately experimented with how AI systems interact with each other. She's quick to jump on creative tools that haven't crossed into enterprise yet, and through her I see what the next generation actually uses and how they behave. I've seen tech help her in ways that cut against the doom narrative on teens and screens. Sample of one, I know.

My husband (nuclear physicist, Wharton MBA, brilliant and deeply analytical) is almost entirely disengaged from AI. He'll use insight I surface from it, but he'll never seek it out. I live with his skepticism and understand it well.

I sit in the middle: excited but not uncritical, optimistic but paying attention. Bridging the two sides of AI is the latest iteration of my translator role, and it feels like the most consequential. I created this site because I think there's a real need for voices that aren't performing panic or hype.

If you're here because you're curious, welcome. If you're trying to figure out how to bring AI into your organization thoughtfully, let's talk.