Perfection is overrated. Three Link Solutions' tech lead shares how curiosity and self-trust unlock true engineering growth.
Emma Coppin
Multimedia Content Lead, Thought Leadership and Customer Stories
Workday
When Goose the Brittany Spaniel hears his leash click, he knows it's time for a walk—and for Kenzie Girvan, that same click signals the start of her creative headspace. In fact, Girvan intentionally blocks time on her calendar for these walks. For her, stepping into nature, away from noise and the pressure, is one of the best ways to engage in deep problem-solving.
The problems she solves as technology innovation lead at Three Link Solutions span a wide range. She oversees the team's customer-facing technology, including Workday solutions and integrations—plus the roadmap for what her team builds next.
She manages all this through problem-solving habits built on lived experience and self-reflection, which she has distilled into a guiding principle: "A great developer is not someone who writes perfect code; a great developer is someone who can learn and is curious."
"A great developer is not someone who writes perfect code; a great developer is someone who can learn and is curious."
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Girvan didn't take to coding right away. The early days of finding her footing as a developer were frustrating, because the problem-solving itself is hard—coding was never going to be an easy thing to walk into. But this frustration led to an important self-discovery.
"Once you get it and it clicks, it's like the best dopamine rush ever," she says. "It's so satisfying, and that's what really kept me in it." She started to love the process of getting to a solution, not just the solution itself, and stopped treating her own confusion along the way as a personal failing.
The harder the problem was, the more it was worth solving.
"I think you get the most payoff when you struggle a little bit with something," she says. "If I didn't struggle, it wasn't as good of a payoff. It didn't feel like I solved as big of a problem."
In school, Girvan was the kind of student who wanted straight As, and got them by studying hard. "There's a finite amount that you need to know for a class," she observes. "You can read the textbook. You can read the chapters that are going to be on your exam. There's a right and wrong answer."
The professional world, she found, didn't work that way. "There was a bit of a mindset shift coming out of an academic setting into a professional one where it wasn't about me knowing everything off the bat. It wasn't me being the smartest person in the room. It was about trusting myself and my ability to learn and grow."
"It wasn't me being the smartest person in the room. It was about trusting myself and my ability to learn and grow."
That growth cultivated strong problem-solving skills. "I know how to find the things that I do need to know. I know how to research to find my answers. I know who the experts are that I can lean on to help me learn."
Failure just means one option didn't work, and it's time to try the next one.
Her scheduled walks with Goose aren't the only tool Girvan uses to practice problem-solving. "All of my hobbies are very creative," Girvan says. "I do pottery, I paint, I crochet. I really like that part of my brain, and I think it helps me problem-solve because I'm able to think about things in a different way."
The same perspective shapes how she thinks about AI. "My favorite dev tool that I can't live without is AI," she says. "I use it to read my XML and JSON—it saves me a ton of time." But she's wary of where that convenience can lead. "It's really easy to fall into a trap of just letting AI write your code for you and to not really understand what you're looking at," she says.
What she'd challenge early-career developers to do is take the time to struggle through the code themselves—not always, but enough to build real expertise. "AI is a tool, and it's a great tool for accelerating your work, but having that expertise is really important," she says.
She sees a knowledge gap coming in 10–15 years—plenty of expertise exists today, but not forever. In an era where AI handles the routine, the developers who build real expertise now will be the ones steering the future.
"You are gonna be a better developer because of it."
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