HWIL: We’re Test Driving the Future with the Headlights Off
This is the first in a series I’m calling HWIL—Here’s What I Learned.
It captures the learning-out-loud ethic behind Untrained Data and quietly riffs on “Hardware in the Loop”—a systems-testing concept that’s all about humans staying in the feedback loop as technology evolves. That’s the spirit here too: reflections from the front lines of change, told in real-time. Not polished. Not retroactive. Just raw insight, captured before it calcifies.
This week, I sat in on a high-stakes internal conversation about AI implementation.
The topic? Choosing an enterprise-grade AI platform to power customer experience.
The reality? We’re all still guessing.
“It’s like choosing a car without test driving it.”
That stuck with me. We’re trying to evaluate tools that evolve weekly. Even the vendors don’t fully know what they’ll be six months from now. And yet, the decisions we make now—on platforms, structure, adoption mindset—will ripple outward for years.
“In three years, we’re going to look back and say, wow—AI completely changed how we work and who we hire.”
That wasn’t hype. It was calm, grounded, long-term thinking. And I felt a jolt of recognition. Because I’ve been waiting for that moment—the one where we stop debating if AI matters and start grappling with how to adopt it responsibly, practically, and with the humans still in the loop.
For two and a half years I’ve been doing the quiet work:
- Studying how LLMs think.
- Testing AI tools in scrappy, behind-the-scenes workflows.
- Building mental models for what “good” AI adoption could look like.
- Learning how to translate complexity in a way real people can trust.
But all of that lived in internal docs, backchannel conversations, and half-finished notes—until now.
Untrained Data is my way of turning that inner work into public proof.
This post, and the ones that follow, are how I show—not tell—that I’m ready to lead in the AI era. Not with perfect answers, but with a mindset built for ambiguity, context-switching, and human-centered thinking.
I don’t have a crystal ball.
But I do have headlights.
And we’re already driving.
Let’s see where it goes.