Gubagoo: Chat Copilot

Before ChatGPT made “copilot” standard product vocabulary, I designed Chat Copilot, my first project building user-controlled AI into a product experience. It looks rudimentary now, but it’s interesting to see what’s held up and how AI patterns have matured.

Context

Gubagoo’s chat AI greeted every dealership chat lead, then handed the chat to a human operator when it was ready, with no way for AI to reengage. Operators working several chats at once were left typing out contact-info requests and simple inventory lookups by hand. My brief was simple: let operators bring the AI back into the chat. I turned it into a stance: the operator stays in the loop, and the AI works for them rather than taking over.

In pilot testing, operators described it as having “my own personal assistant all day long.” An operations manager said the AI now took the repetitive work, so operators could focus on the conversations that need a person, and teams were “hitting more team goals than ever.”

About the solution

Copilot sits in a control bar above the message composer. It suggests the one most relevant task, runs it with the team’s first machine-learning model, and shows its progress on each chat card. If anything goes wrong, it pulls the operator back in. The human stays in the loop and the AI can be called back in: these are the patterns AI copilots use today.