Case Study: Building an AI Dashboard
A real-world walkthrough of designing and building an analytics dashboard using AI tools at every stage of the process.
This case study walks through building a complete analytics dashboard — from research to shipped product — using AI tools at every stage.
Research phase: We used ChatGPT to synthesize 12 user interviews, identifying that users wanted 'at-a-glance metrics' and 'drill-down capability'. Perplexity helped us survey 8 competitor dashboards.
Design phase: Starting with wireframes in Figma, we used the design system to compose layouts. Key decision: a card-based metric overview at the top, with interactive charts below. AI suggested adding a comparison mode that we hadn't considered.
Development phase: With MCP connected, we prompted Cursor to implement each section. The metric cards took one prompt. The chart section needed iteration — we refined the prompt three times to get the interaction right.
Testing phase: AI-powered accessibility audits caught contrast issues in the chart legends. We used the theme generator to test the dashboard in 5 different color schemes to ensure it worked across brands.
Result: What would have been a 3-week sprint was completed in 8 days. The design-to-code fidelity was higher than any previous project because the AI was reading directly from the source of truth.