Managing liaison statistics is a persistent challenge in academic libraries, especially as liaison models evolve toward team-based, collaborative structures. At the [UNIVERITY NAME] Libraries, a redesign of the liaison model exposed significant gaps in existing data collection methods. This presentation describes how [NAME] Libraries moved from that fragmented system to a streamlined custom web interface built on the Asana API, developed with the assistance of ChatGPT. After evaluating Asana's native tools and finding they required too much direct platform interaction for liaisons, the team built a lightweight custom interface that lets liaisons log, view, and edit their activities without ever touching Asana directly. ChatGPT helped generate the initial code framework, authentication logic, and workflow structure, and showed how generative AI can be utilized to build custom solutions in a fraction of the time it would have taken otherwise. Attendees will come away with a sense of how to evaluate API-based tools for workflows, how AI-assisted development can make creating custom solutions more accessible, and how to design statistics collection that actually reflects the way liaisons work today, including collaborative and team-based activity. The interface and the approach behind it are designed to be adapted and reused by other libraries.
