video1.0<iframe src="https://www.loom.com/embed/cd555c7088084196ad739e843a9da1e5" frameborder="0" width="1152" height="864" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>8641152Loomhttps://www.loom.com8641152https://cdn.loom.com/sessions/thumbnails/cd555c7088084196ad739e843a9da1e5-102b970b8d31d02b.gif259.57This Loom explains how Praveen is building a vision-based browser agent memory system that enables agents to reuse prior successful web workflows. The project indexes working steps from an agent run by capturing click coordinates, typed and extracted content, and navigation paths, then stores and retrieves them using a “hybrid” approach in supermemory. On subsequent tasks, the agent uses the retrieved playbook rather than starting from scratch, including coordinate normalization for different screen sizes. Praveen reports an initial run taking over 3 minutes and a repeat run taking 34.80 seconds, demonstrated by successfully finding the Cloud Code YouTube video description.