Sanjit Biswas runs what may be the largest AI deployment in the physical world — and almost nobody in AI talks about it. Samsara (NYSE: IOT), the ~$20B company he co-founded after selling Meraki to Cisco for $1.2B, puts AI on millions of trucks, cranes, and industrial assets: 25 trillion data points a year, 99% of US roads driven every single day, ~$2B in ARR growing 30% profitably. In this episode we go through the entire physical AI stack — asset tags you can run over with a truck, a paper-thin disposable tracking label, engine fault codes, and dash cams running inference at the edge — then into agents, including the Agent Studio warranty agent that compresses an hour of human work into under a minute. We also get into the uncomfortable part (when AI watches you drive all day, is that coaching or surveillance — and why drivers actually want the cameras), mixed fleets of humans and robots, why autonomous trucking will take far longer than robotaxis, and a startling stat from the field: one utility building 3x more grid capacity in the next five years than it did in the previous 125, with 90% of that demand coming from data centers.

(00:00) Intro: The biggest AI deployment nobody talks about

(01:16) What is physical AI?

(03:04) From IoT dashboards to agentic action

(04:36) Why physical AI is harder than software AI

(06:07) Safety, cybersecurity, and real-world consequences

(07:11) What Samsara does

(08:22) $2B ARR, 25 trillion data points, and 380,000 crashes

(09:44) How AI can prevent road accidents

(11:28) From an MIT research project to Meraki

(13:42) Learning physical operations from scratch

(15:42) Samsara’s stack: sensors, intelligence, and action

(16:39) Inside Samsara’s industrial asset trackers

(18:36) Bluetooth, battery life, and connected infrastructure

(19:49) A disposable tracking device built like a sticker

(21:08) Vehicle gateways and engine diagnostics

(22:16) How AI dash cams coach drivers in real time

(23:28) Turning the dash cam into an AI interface

(24:49) Organizing physical-world data in the cloud

(26:32) Selling AI to traditional industries

(27:52) Is Samsara’s real-world data its AI moat?

(29:22) The network effects of covering 99% of U.S. roads

(31:23) Edge AI versus cloud AI

(32:35) The models running inside Samsara’s devices

(33:52) Generative AI and video reasoning

(35:57) Which AI models does Samsara use?

(36:50) Inside Samsara Agent Studio

(37:56) How an AI warranty agent works

(38:50) Starting with practical, lower-risk automation

(40:10) Combining agents, workflows, rules, and guardrails

(42:07) What today’s AI agents still cannot do

(43:07) AI ride-alongs and the future of driver coaching

(45:17) Is workplace AI becoming Big Brother?

(46:27) How cameras can protect and exonerate drivers

(48:48) When AI becomes the judge of your work

(50:37) Robots, humanoids, and mixed human-machine fleets

(53:19) Samsara’s role in autonomous operations

(54:50) How quickly will autonomous trucking arrive?

(56:32) AI data centers and America’s infrastructure boom

(58:16) Should lawyers become plumbers? Demand for tradespeople

(59:54) Closing thoughts