How do you design software that holds up under pressure?
Recently, I gave a talk at the New Tech Northwest March Meetup. A few ideas from that talk felt worth capturing for reflection, so I’m sharing them here.
TLDR
While engineering mental conditioning systems for competitive athletes, we saw that deep user understanding drives adoption, engagement, and lasting change.
This talk draws from two platforms built at the intersection of sport and technology:
- Before the Field — an ACT-based mental conditioning platform designed to help athletes build self-awareness and resilience.
- SheSports — a moderated content platform connecting girls ages 8–18 with female college athletes for mentorship and support.
Together, these systems show that in an AI-accelerated world, user insight remains the foundation of resilient software.
Watch the video below for the full talk.
Insights for Better Experiences
Artificial intelligence is dramatically accelerating software development. But while AI helps us build faster, it doesn’t replace the need to understand what should be built in the first place.
At Flower Press Interactive, our tagline has long been: Insights for Better Experiences.
That principle guided our work long before the current wave of AI tools, and it remains true today. When you’re building systems that change behavior, support people under stress, or help them develop new habits, deep user insight matters more than ever.
AI is excellent at synthesizing information and accelerating development. But product wisdom still comes from real conversations with real people.
Two recent platforms illustrate this.
Before the Field
Former MLB outfielder Carlos Quentin experienced the pressures of professional sports firsthand. After retiring, he saw that athletes lacked structured tools for mental conditioning — systems to manage injuries, stress, and performance pressure.
Working with sports psychologists, coaches, and athletes, he helped create Before the Field, a mobile platform based on Acceptance and Commitment Therapy (ACT).
Through interviews with athletes and coaches, one insight quickly emerged: athletes needed a confidential way to communicate with coaches inside the platform.
That feature became one of the most used parts of the system and has helped prevent multiple crisis situations. The technology stack was modern — TypeScript, Node services, and React Native — but the most important decisions came from understanding athlete needs.
SheSports
The second example focuses on community.
Elite volleyball player Lexi Rodriguez and entrepreneur Kelly Krings recognized that young female athletes lacked safe places to ask questions, find mentorship, and learn from athletes ahead of them.
Their work led to SheSports, a moderated platform connecting girls ages 8–18 with female college athletes.
Because minors are involved, the system was designed around trust and safety. There are no public comment threads and no direct messaging. Instead, the platform uses structured Q&A, moderated interactions, and athlete-generated content to create a supportive environment.
AI tools helped accelerate development, but the platform itself was shaped by research with athletes, coaches, parents, and families.
Insights Still Matter
Across both platforms, the lesson is simple.
AI increases velocity. It does not increase wisdom.
Under pressure, systems reveal their design. And if we want better outcomes we must keep users at the center.