How I do AI Prototyping as a Designer in Healthcare
Summary
Healthcare designer at ESO uses structured discovery and data-driven PRDs before AI prototyping to avoid "speeding up in the wrong direction"—embedding product trios (engineering, product, design) and cross-functional stakeholders ensures alignment before rapid prototyping begins.
Key Takeaways
- Skip the AI prototyping sprint without discovery: Discovery process aligns product trios (engineer, product, designer) and stakeholders on direction first, preventing wasted velocity on wrong solutions.
- Build user personas from internal subject matter experts: ESO hires former firefighters, EMTs, and paramedics as full-time employees who still volunteer part-time, creating high-fidelity personas and embedded domain knowledge.
- Design for quick exit, not engagement: First responder products should minimize user time in software—opposite of consumer SaaS—since primary job is patient care, not documentation.
- Use Magic Patterns to accelerate PRD-to-prototype: Copy entire product requirement document into AI tool to generate initial wireframes/flows in first iteration, but only after discovery is locked.
- Include executive leadership and customer success in discovery de-risking: Bring stakeholders from multiple departments (sales, CS, exec team) into BRD and PRD processes to ensure business alignment.
Related topics
Transcript Excerpt
Who are the users for whom you're designing in this healthcare space? >> Our users are firefighters, EMTs, paramedics, and then trauma care professionals in a hospital setting. >> You're doing all this initial discovery to create a product requirement document which you then feed to your AI prototyping tool. Can you show me like how you're doing that? >> Magic patterns is our AI prototyping tool of choice. simply copy the entire PRDN and it starts to generate and we got pretty close our first iteration our first solution. This is very structured like you've got the competitor research. You've got all this like strategy and the user personas mapped out like why do all this? Why not just directly jump to VIP coding or AI prototyping? >> Yeah, great question for us. Yes, it was a data company…
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