An article by product designer Jess Brown that shares concrete, real-world examples of how she uses AI tools—especially large language models—in her day-to-day work at Faire. She groups her practice into two main areas: informing design decisions and exploring content. On the research side, she shows how internal chatbots and ChatGPT help her uncover customer pain points from support tickets, synthesize user interviews more consistently, organize large event datasets (like trade show vendor lists), and enrich spreadsheets by combining data from disparate sources, all while stressing data privacy and the need to verify outputs rather than blindly trusting them.
On the content side, Brown demonstrates how AI supports microcopy exploration, light competitive and go-to-market research, and the creation of realistic placeholder data such as shop or product names, often in combination with tools like Figma’s Content Reel. Throughout, she is explicit about limitations—such as hallucinations when summarizing too many interviews at once—and frames AI as a collaborator that speeds up mechanical work so designers can focus on deeper thinking and better decisions. The article is useful for product designers, UX researchers, and content designers who want practical, nuanced examples of bringing AI into a design workflow without losing human judgment or craft.
