Experiences with AI Vibe Coding and Prototyping

Last week, I launched a fully vibe-coded AI youth sports platform to support player development for Lexington Youth Lacrosse ( http://HitTheWallBall.com ).

The platform helps coaches structure at-home training, verify progress through video submissions, provide AI-assisted coaching insights, and motivate athletes through rewards, recognition, and skill progression.

What surprised me most wasn’t that AI could generate the code; it was that AI could help build for scale.

As someone who has spent decades leading technology organizations, I expected AI to accelerate development. What I didn’t expect was how often it anticipated future needs without being explicitly directed.

As I built the platform, AI consistently suggested patterns and architectures that supported future growth:

• Multiple youth programs instead of a single club

• Multiple teams and coaches instead of a single organization

• Multiple sports instead of just lacrosse

• Flexible workflows instead of hard-coded processes

Now, let’s be clear. Vibe coding does not eliminate the need for technical expertise. You still need to understand architecture, data models, scalability, security, testing, and software development lifecycle principles. You still need to know what you’re building and why you’re building it.

The difference is that AI dramatically accelerates execution when paired with strong product vision and sound engineering practices.

In just a few weeks of nights and weekends, I was able to take an idea from concept to a live production platform that is already supporting real athletes and coaches.

The next phase is even more exciting. We’re beginning to introduce more advanced computer vision capabilities to reduce administrative burden on coaches while helping athletes receive faster, more objective feedback on skill development and technique.

This will grant coaches more time to do what they do best: motivate, teach, inspire and focus on team play at practice… instead of teaching basic skills.

At the same time, we’re empowering athletes to take ownership of their development through structured practice, measurable progress, accountability, and a little friendly competition.

I believe AI has the potential to fundamentally change how youth sports programs develop athletes—not just by creating better players, but by helping build disciplined, resilient, self-motivated leaders.

Excited for what’s next.

Stay tuned for more updates on AIthl33t (https://aithl33t.com/) as we continue to push the boundaries of AI-powered athlete development.