In 2025, we proposed an AI-driven anchored MaxDiff tracker that could evolve its own item list. We ran four waves of a survey with two MaxDiff exercises to track what respondents were happy about and what worried them, with generative AI analyzing open-ends and recommending item swaps each wave. We'll share what worked, how the LLM-analyzed results compared to human-coded results, and our overall thoughts on using genAI to support tracking respondent sentiment with MaxDiff.