WHAT I DID

• Architected Conversational Strategy: Led the development of the training framework for AI-generated Rufus "Pills," specifically for Search Post-Add-to-Cart (PATC) Trade-Across experiments within Amazon’s Progressive Discovery initiative.

Engineered Intent-Based Frameworks: Designed a scalable system organized around Customer Intent and Shopping Objective Strategy, moving beyond static recommendations to create contextually aware, conversational prompts.

Transformed Product Discovery: Developed specialized categories—such as Discoverability and Explanation—to guide the LLM in surfacing benefits, trade-offs, and routines that reflect natural customer thought patterns.

Reframed Customer Value: Created high-impact messaging strategies that shifted focus from product attributes to user-centric goals, such as reframing oral care as a "wellness routine" or addressing specific concerns like "grout-friendly" cleaning.

Optimized Conversational Diversity: Implemented a key innovation to ensure each set of prompts represented a broad range of motivations, preventing repetitive patterns and making the AI experience feel more adaptive and human.

Balanced Persuasion with Trust: Established strategic guidance to address customer tensions—such as the balance between "gentle" and "powerful" cleaning—to build confidence and reduce friction during the shopping journey.