<?xml version="1.0" encoding="UTF-8"?><oembed><type>video</type><version>1.0</version><html>&lt;iframe src=&quot;https://www.loom.com/embed/cb2373f7d2c24fd08513e559aeac39d6&quot; frameborder=&quot;0&quot; width=&quot;1280&quot; height=&quot;960&quot; webkitallowfullscreen mozallowfullscreen allowfullscreen&gt;&lt;/iframe&gt;</html><height>960</height><width>1280</width><provider_name>Loom</provider_name><provider_url>https://www.loom.com</provider_url><thumbnail_height>960</thumbnail_height><thumbnail_width>1280</thumbnail_width><thumbnail_url>https://cdn.loom.com/sessions/thumbnails/cb2373f7d2c24fd08513e559aeac39d6-ecbaad26c9afc3a4.gif</thumbnail_url><duration>912.98</duration><title>Walkthrough of AI-PD Design Challenge - FlytBase - Dhiren Valecha</title><description>This Loom explains a Flight Base design challenge focused on how operators make decisions during live drone incident response. The author argues that the operator is not a pilot but a decision maker: in phase 1 the operator is the judge while AI accesses the threat before they see it, in phase 2 they become the commander with a map-first interface and confirm or coverage actions, and in phase 3 they become the archivist as evidence is captured automatically and reviewed afterward. The incident scenario runs for 4 minutes and 12 seconds with one operator, and the UI uses AI to generate situation guidance and a team brief. The Loom also describes evidence packaging for three audiences, including a chain of custody certificate for police, and notes the design as an add-on to an existing live response library.</description></oembed>