{"type":"video","version":"1.0","html":"<iframe src=\"https://www.loom.com/embed/39c4214527ed4dd5a4bfc712ab65483a\" frameborder=\"0\" width=\"1726\" height=\"1294\" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>","height":1294,"width":1726,"provider_name":"Loom","provider_url":"https://www.loom.com","thumbnail_height":1294,"thumbnail_width":1726,"thumbnail_url":"https://cdn.loom.com/sessions/thumbnails/39c4214527ed4dd5a4bfc712ab65483a-cd65537a98d93048.gif","duration":142.315,"title":"Adaptive AI Memory Layer and Ingestion Flow","description":"In this Loom, I explain our new prop context and the memory layer we are building to be adaptable for agent to agent communications and readable by humans. I walk through our ingestion flow, showing how data is verified, normalized, classified, enriched with Lovable when needed, irrelevant noise is dropped, and the result is re indexed in our Vicky page index. I also show how agents use the index.vicky file to understand the folder structure and update it with new contexts and files. No specific action was requested from viewers."}