{"type":"video","version":"1.0","html":"<iframe src=\"https://www.loom.com/embed/e51356c7ef2a4799adfe94378a934e24\" frameborder=\"0\" width=\"1728\" height=\"1296\" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>","height":1296,"width":1728,"provider_name":"Loom","provider_url":"https://www.loom.com","thumbnail_height":1296,"thumbnail_width":1728,"thumbnail_url":"https://cdn.loom.com/sessions/thumbnails/e51356c7ef2a4799adfe94378a934e24-8df4689755a4f128.gif","duration":152.543,"title":"Wayfinder Reduces AI Web Search Redundancy","description":"This Loom explains how Wayfinder reduces redundancy in AI agents that repeatedly re-derive how to navigate websites. It argues that with millions of agents, agents waste tokens and lack a true understanding of how each website’s buttons and workflows work, especially across legacy and enterprise sites. Wayfinder explores each site once to create a knowledge graph and an MD file, then continuously updates it when pages change so agents can reuse the indexed flows via a single API. The speaker also notes that website owners can use the tool to generate automatic MD files to keep agents updated."}