One Operator, Many Drones: Inside Skydio's Autonomy Stack — Suchet Bargoti, Skydio

Suchet Bargoti opens with a live demo instead of slides. From a laptop on conference Wi-Fi, he launches a docked drone over San Mateo, starts a second one on a power line in Colorado, has one autonomously track a car, and then sends the whole fleet back to dock. Skydio, the largest US drone manufacturer, now has thousands of these docks deployed with utilities, police and construction companies, and about 16 million people live within two miles of one. Bargoti, Skydio's Director of Inspection and Mapping, explains the shift to "drones as infrastructure." He shows a drone spotting a utility pole burning from the inside, and SFPD following a stolen car without a high-speed chase. He then breaks down the autonomy stack. It splits intelligence between the edge and the cloud, uses maps as world models that the fleet keeps up to date, tracks objects through occlusion, and lets a VLM agent find and follow a "white Jeep" using tool calls instead of hand-coded rules. He also covers where fully end-to-end learning still falls short of the reliability physical systems need. Speaker info: LinkedIn: https://www.linkedin.com/in/sbargoti Related links: Skydio: https://www.skydio.com Timestamps: 0:00 Live demo: flying drones from a laptop 1:02 Drones as infrastructure 2:12 Launching a second drone in Colorado 3:07 Autonomous car tracking 3:42 From hobby toy to tool to infrastructure 5:01 Sending the fleet back to dock 5:26 A utility pole burning from the inside 6:01 Following a stolen car with SFPD 7:06 Reliability in Alaska cold and Texas heat 7:51 Why one pilot per drone doesn't scale 9:45 Full-stack autonomy 10:40 The data flywheel 11:30 Autonomy on the edge and in the cloud 12:05 High-quality video on low bandwidth 12:54 Maps as world models 13:49 Keeping maps up to date with the fleet 14:49 Tracking through occlusion 15:49 Heavier VLM tracking in the cloud 16:19 Semantic reasoning for infrastructure 16:58 Agentic "find and follow" with a VLM 17:48 End-to-end learning and its limits 19:23 Beyond quadcopters