AI enablement begins with the work someone already understands. A manager has a coaching conversation to prepare for. A colleague has a project they want to start. The useful question is what would help them make progress, and how they will know the result is worth using.
Coaching and operational judgment
At Chewy, I built a scorecard to keep goals, previous conversations, and employee comments together. I taught managers how to use ChatGPT in their coaching work and later built a custom GPT around that workflow. Eleven chat managers used the approach while supporting roughly 180 to 200 agents.
The early process used manual handoffs. Managers supplied the material, reviewed the output, and remained responsible for the coaching conversation. I also managed AmplifAI onboarding for the chat team and trained participants in using the platform.
Alongside that work, I used SQL, Vertica, Excel, and Tableau to investigate operating questions. I checked analysis with fellow managers and helped Operations HR compare employee reviews during calibration. The people responsible for those decisions stayed involved.
Reference material and live help
At Nerdy, I wrote a 263-page AI guide and held office hours where colleagues could bring questions and work through their own projects. The written material gave them something to return to after a session. Live help made room for the question that only becomes clear when someone tries the work.
I developed reusable project patterns and taught colleagues how to adapt them. My manager recognized the guide as an organizational resource and the teaching as practical support for peers moving from a blank repository toward a first deployment.
These experiences shape my consulting work. I can help a team choose a useful starting point, build supporting resources, and work through the decisions that arise as people begin to use AI.