This Was Made for Me
How a ceramicist-turned-AI consultant rediscovered the power of presence, design, and precision in data work.
Before I began working in AI and data—and long before loyalty programs and grocery analytics—I was at the wheel, hands in clay, learning the quiet discipline of shaping with purpose.
My journey into tech didn’t begin with code. It began with understanding people. I spent years immersed in the world of grocery and retail, thinking deeply about how customers shop, why they stay loyal, and what they expect from the brands they trust. That focus on customer behavior led me into insights work—then into AI-driven insights—and eventually into full-scale data consulting for retailers.
But at every step, I’ve never stopped thinking like a ceramicist.
Because in ceramics, you learn something fundamental: form isn’t enough. What you create needs to feel right—balanced, intentional, quietly understood by the person who holds it.
And lately, I’ve been asking myself: What does that kind of craftsmanship look like in the world of AI?
What “Goodness” Really Means
Recently, a senior leader challenged me and my team with a deceptively simple question:
“What other goodness are we bringing?”
At face value, it was about value-adds. But to me, it echoed something deeper: Is this not just functional, but actually good? Does it feel thoughtful? Human? Is this something a client will remember—not because it checked a box, but because it solved a real problem in a meaningful way?
It reminded me of standing in a studio, running my fingers along a vessel that held both utility and intention. And it made me wonder: in our rush to deliver fast and scale big, have we forgotten what it means to craft something people wouldn’t want to work without?
Because when craftsmanship shows up in data work, it doesn't usually lead to applause—it leads to something better. A quiet moment when the client leans back and says:
“Honestly, this hits the nail on the head.”
“I wish more of our tools felt this intuitive.”
That’s how goodness reveals itself—not with fanfare, but with fit. With a solution that aligns so closely with the problem, it feels like it’s always been there.
That’s not just added value. That’s presence. That’s care. That’s the difference between “it works” and “this works for us.”
The Quiet Gap Between Function & Feel
In tech, we’ve developed a vocabulary of productivity:
“The engineering is clean.”
“The architecture scales.”
“The dashboard meets requirements.”
“The model is performant.”
Those things matter. But they’re not the whole story. Especially in retail—where the systems we build ripple through real lives and real decisions—function isn’t enough. Our tools must be intuitive. Trustworthy. Aligned with the mental models of the people using them—not just the assumptions of those who built them.
As Matthew Crawford writes in Shop Class as Soulcraft:
“The craftsman’s task is not to generate meaning, but to cultivate a sensitivity to the real.” (Crawford, 2009, p. 64)
Craftsmanship isn’t about embellishment. It’s about being attuned—about caring enough to build something that understands its purpose and its user.
What Craftsmanship in AI Looks Like
So what does that look like in our world?
A personalization model that reflects how customers actually behave—not just what the data suggests they might.
A forecasting tool whose logic makes sense to planners without needing translation.
A dashboard that’s not just pretty, but purposeful—surfacing what matters at the right moment, without noise.
A handoff that feels more like onboarding than abandonment—because you considered maintenance and longevity from the start.
That’s when a client stops saying, “Good work,” and starts saying,
“This is spot on.”
“You really got what we were going for.”
That shift—from output to outcome, from use to trust—is the signature of craftsmanship in tech.
So, Where Is the Craftsmanship?
It’s in the architecture that reflects the business, not just the backend.
It’s in the line of SQL someone wrote at 11 p.m. that prevents reporting failures at scale.
It’s in the extra half hour someone took to align a dashboard to a real-world decision, not just a KPI.
It’s not about going slow—it’s about being present. And it’s not just about quality for quality’s sake. It’s about earning the right to be used—day in, day out—by people who have real jobs to do.
That’s the bar.
A Call to Build Differently
If you’re building AI or data solutions—especially for retailers—this is your invitation to pause. To ask:
Does this feel right for the people it’s meant to serve?
Would a client say, “This made my life easier”?
Would I be proud to say, “Yes, I made that—and I made it well”?
Because in a landscape full of platforms, tools, and automation, the ones that last are the ones that feel like they were built with someone real in mind.
Like a bowl that rests just right in your hands.
Like something made with presence and purpose.
Like something you’d hold on to and say,
“This was made for me.”
Works Cited
Crawford, M. B. (2009). Shop Class as Soulcraft: An Inquiry into the Value of Work. Penguin Press.
