While most enterprises struggle to scale AI prototypes into reliable products, a proactive architectural framework can bridge the gap between concept and reality.
Ken Knapton, the Chief Information Officer at WIN Brands, explains that leaders must plan for scale from day one by focusing on the ultimate business objective.
By embracing iterative feedback, making decisions with incomplete information, and modeling costs for success, leaders can de-risk new projects and ensure they are prepared for scale.
Most enterprises can build a functional AI prototype. But the real challenge is scaling that prototype into a reliable product. A concept might work perfectly in isolation but forget to account for the stresses of real-world traffic or the need for long-term stability. The result is a gap between working ideas and production-ready assets—a gap that requires thoughtful leadership to bridge.
To better understand this journey, we spoke with Ken Knapton, the Chief Information Officer at WIN Brands, where he serves as the head of technology for both Costa Vida and FatCats. While his resume is impressive—he’s a CISSP and C|CISO who architected Symantec's Norton Corporate Edition and designed a global banking system for 173 currencies—his solution is a simple but powerful filter.
"If your goal is growth by acquisition, scalability has to be paramount," Knapton says. "If you expect a consumer app to go viral, you have to be thinking about scalability from day one."
Before any code is written, Knapton insists on a conversation about the ultimate business goal. "You need to be conscious of the end goal. It’s not just about how people will use a solution," he continues. "It's about why you are building it in the first place."
When failure calls: Years ago, Knapton says he learned the cost of poor planning firsthand when a critical system couldn't keep pace with the company's growth. It was a lesson in a fundamental truth of development. "The system just bogged down," he recalls. "I knew that every morning at 9:30, my phone would start ringing because people couldn't log in."
The reactive trap: Eventually, the daily crisis forced a painful reset. "We had to rip out the database and put in a new one. When the CEO asked why we hadn't done it six months earlier, I had to tell him we'd been working on it for six months." That experience, and others like it, helped shape his core philosophy.
But external success is not the only scaling threat. Sometimes, an internal tool's unexpected popularity can cause the biggest headaches. "You build a tool for one department, and then another department discovers it," Knapton says. "Suddenly you're trying to scale a system you never planned to grow." Because of this inherent uncertainty, waiting for perfect data often leads to paralysis.
The 60% solution: Instead, Knapton champions an agile approach that prioritizes quick feedback. First, leaders must get comfortable with making decisions without all the answers. "You have to make decisions with 40% to 60% of the data. Gather just enough to get started. And remember that, as soon as you put something in a person's hands, they're going to tell you they want something else."
Embracing the ugly: For Knapton, embracing iteration is now a strategic necessity. Rather than a failure or a setback, he sees changing requirements as simply part of the job. "My advice is, don't get frustrated. Get a functional version into their hands as fast as you can. Let them use it. And then, don't be defensive when they tell you your baby is ugly."
Knapton's philosophy of change extends directly to financial planning as well. For instance, when his team launched a new tool with unknown usage potential, their proactive modeling turned a surge in popularity into a welcome sign of success.
Planning for popularity: "We chose a solution where costs wouldn't be astronomical, even if we tripled our expected use," Knapton says. As a result, the tool’s value was proven almost immediately. "We hit our max right away, so I had to upgrade. Then we hit the max of that one, so I had to upgrade again. It's a good problem to have."
In the end, Knapton’s framework comes full circle. The same principles that solve technical problems can also heal communication breakdowns, he explains. When a prototype stops being just a technical tool, it becomes the most honest form of conversation you can have. "Nothing communicates faster than a visualization someone can actually interact with," he concludes. "It lets you ask a simple, powerful question: 'Is this what you were envisioning?' That single question cuts through all the misunderstanding."
