video1.0<iframe src="https://www.loom.com/embed/3a2ffa40206f4f64a4d9caa4b11aa23e" frameborder="0" width="1920" height="1440" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>14401920Loomhttps://www.loom.com14401920https://cdn.loom.com/sessions/thumbnails/3a2ffa40206f4f64a4d9caa4b11aa23e-7d59c736e2d5c4a7.gif91.914This Loom demonstrates a multi-agent app for scraping Wayfair product data and tailoring sofa recommendations to customer constraints. The speaker explains the app’s structure with Trapper Goal, Constraint, and Source, where Source is JSON scraped from a URL, and notes plans to integrate 11 Labs with the agents. Agents such as R.S. and Vivian’s Luxury discuss products based on their programming, and the user can interrupt the flow to refine requirements, including a specified sofa size of 80 inches width and 36 inches depth instead of 82 inches. The team emphasizes customer focus and highlights why Wayfair matters through its provided dimensions and delivery and configuration details.