The Intelligence Layer

AI-Powered Search and Chat

AI-Powered Search and Chat

Defining the UX foundations for GenieAI, semantic search, and assistant-driven workflowsbringing meaning, relevance, and guidance to a historically scattered content ecosystem.

Defining the UX foundations for GenieAI, semantic search, and assistant-driven workflowsbringing meaning, relevance, and guidance to a historically scattered content ecosystem.

2023 - 2025

Product

Senior Product Designer

UX

Search

Platform Systems

Trust & Safety

Summary

AI features were being shipped as isolated capabilities — impressive in demos, but unclear in real workflows.


Users didn’t know when to use AI, what it was doing, or how to trust the output. Prompts lived in disconnected surfaces. Results lacked context. Teams struggled to explain value beyond “we added AI.”


As pressure grew to infuse intelligence across the platform — not just bolt it on — we needed a clearer mental model for how AI fit into everyday work, within real technical and data constraints.


This work established an AI interaction framework and intelligence layer that aligned user intent, system capability, and trust — and became the foundation for future AI initiatives across Search, Coaching, and Meetings.

My role

  • Diagnosed where early AI experiences broke down due to unclear intent, low transparency, and fragmented entry points

  • Defined and validated an AI interaction model grounded in user goals, confidence levels, and system constraints

  • Designed core AI surfaces (entry points, prompt scaffolding, results states, and feedback loops) to make AI behavior legible and trustworthy

  • Partnered closely with PM, Engineering, and Data to align UX, model limitations, and rollout strategy

  • Shaped a phased AI approach that delivered value early while creating a scalable foundation for future intelligence features

Impact

AI became understandable, not magical
Confidence and trust increased
Established the intelligence foundation