How I approached it
I worked closely with the product manager and engineers to break down the entire workflow step by step.
This included AI scanning, dependency analysis, conflict detection, time recommendation, and user confirmation.
During the design phase, we went through several rounds of prototyping and continuously aligned with the component team to ensure that the interaction patterns and system architecture worked seamlessly together.
We conducted concept testing with close partner customers including T-Mobile and GM to validate early design ideas. Their feedback helped us understand real enterprise workflows and improve trust and clarity in the AI assistant. We quickly iterated the prototype based on their input, refining how recommendations were explained and how users could adjust scheduling parameters.
