Most teams trying AI start with a tool and hope a habit forms. We think it works better the other way around: start with a real problem your team has, design a small experiment around it, and let the useful thing earn its place.
In this lab, we'll walk through one of our own: PrioPals, the AI resourcing system we built to answer a question we kept getting stuck on: who has capacity and how do we match that capacity to projects? You'll see how it started, what we got wrong, and how it became something the team now engages with seamlessly in their regular workflow.
Then we'll get practical. You'll leave with a simple way to scope your own team-based AI experiment: how to pick the problem, keep the experiment small, and tell whether it's actually working.
This is a working session, not a webinar. Bring a problem your team keeps stepping around.