A planning staff for volunteer coaches

The operations pilot

A few volunteers run tryouts, practice planning, schedules, coach alignment and communication with families, around their jobs and family life. The experiment asks whether AI can take on the preparation, the way a planning staff would, while the coaches keep the decisions.

Walter built a file-based working process for it. AI helps digitize and organize the inputs, prepare research-informed plans and a proposal for the coaches, and draft a weekly brief and practice plan. A review and debrief rhythm closes each week. The coaches approve every decision and every message to families.

The most useful lesson so far is about workflow design, not sport: an early, sophisticated plan didn't fit real life. It worked only once it was simplified around what the volunteers had time for, the transitions between activities, and what the children and coaches would actually do.

Separately, and earlier: decision support for a game plan

Before the operations pilot, Walter tried a smaller thing. An AI-assisted process combined limited scorekeeping data with the coaches' own judgment, made their disagreements and constraints visible, and prepared a versioned game plan. The coaches kept the lineup decisions. The plan exists; whether it was followed in the game, or helped performance, is not verified.

What this is not

It is not an MSL client engagement, a launched product or evidence of better game results. No real team, player or family information is published here.