New Operating Systems for the Physical World
Traditional software for physical-world industries like construction and fleet operations hasn't evolved in 20 years, but AI agents, robots, and wearable-equipped humans now create a new operating system opportunity. These new systems will manage human and robot labor together, capturing end-to-end work data that incumbents lack, while operating in industries that spend 10-100x more on labor than software.
Summary
The transcript discusses a fundamental shift in how work gets managed in physical-world industries. Currently, 80% of the global workforce operates outside traditional desk environments in sectors like construction, maintenance, and fleet operations. Existing software solutions handle only basic functions: dispatching workers, tracking their locations, managing assets, and billing customers. However, the introduction of three new worker types—AI agents capable of quoting complex work and scheduling, robots deployed in the field, and humans equipped with wearables that record their activities—makes today's operating systems obsolete. These legacy systems were never designed to coordinate and manage all three worker types simultaneously. This technological shift creates significant startup opportunities centered on solving new problems: routing jobs intelligently between agents, robots, and humans; establishing safety protocols when humans and robots work side-by-side; and measuring reliability across these hybrid systems. The market opportunity is substantially larger than existing software markets because these industries currently spend 10-100 times more on labor costs than software costs. Furthermore, new entrants building these operating systems will have a competitive advantage: they'll capture comprehensive, end-to-end data about actual work as it happens, data that frontier AI models, robotic startups, and current software incumbents won't possess.
Key Insights
- 80% of the global workforce doesn't sit at a desk, but software for the physical world has remained fundamentally unchanged for over 20 years
- Three distinct types of workers now exist in physical-world businesses: AI agents that quote and schedule work, robots deployed in the field, and humans using wearables to record their activities
- Current operating systems are architecturally incompatible with managing human and robot labor together, creating core unsolved problems around job routing, safety, and reliability measurement
- Incumbent software companies charge for human coordination and visibility through dashboards, while new operating systems will manage human and robot labor as an integrated system
- New operating system builders will possess a structural data advantage because they'll capture complete end-to-end work data that frontier AI models, robotic startups, and existing software incumbents won't have access to
Topics
Transcript
[0:00] 80% of the global workforce doesn't actually sit at a desk, but the software for the physical world hasn't really changed in over 20 years. In construction, maintenance, fleet operations, software basically does some combination of dispatching people, tracking them, managing their assets, and ultimately billing the [music] customer. We're excited about how AI changes that entire model of work. There are now three kinds of workers in these businesses. [music] AI agents that can quote complex work [0:31] and schedule teams, robots [music] actually deployed in the field for the first time, and humans who increasingly use wearables to record everything they're doing in their job. Today's operating systems just weren't designed to manage all three types of…
Full transcript available for MurmurCast members
Sign Up to AccessMore from Y Combinator
Susan Kare: How I Designed the Original Apple Mac Icons
Susan Kare discusses her pioneering work designing icons and fonts for the original Apple Macintosh, sharing design principles focused on simplicity and metaphor, along with advice from influential figures like Paul Rand that shaped her career in digital design.
Chelsea Finn: This is the State of the Art in Robotics
Chelsea Finn discusses advancements in physical intelligence, highlighting the development of general-purpose robots capable of performing various tasks autonomously. Key techniques include reinforcement learning, efficient data utilization, and the importance of memory in complex task execution.
Circleback CEO Ali Haghani: Recording Company Meetings Will Become The Norm
Ali Haghani discusses CircleBack, an AI note-taking tool designed to capture, organize, and automate meeting content. He shares insights on his hardware setup, unexpected uses of CircleBack, and the evolving landscape of software engineering as AI capabilities grow.
Why Robotics Still Isn't Solved - But Could Be Soon | YC Paper Club
YC Paper Club discusses why robotics remains unsolved despite repeated predictions of breakthrough years, presenting four fundamental challenges (physical modeling, deformable objects, sensorimotor feedback, embodiment drift) and showcasing recent advances in memory-augmented policies, embodied reasoning, sim-to-real learning, and world action models.
Max Hodak: What Really Kills Deep Tech Startups?
Max Hodak, CEO of Science (a retinal prosthesis company), explains that deep tech startup success is determined by infrastructure and iteration speed rather than technical brilliance. He emphasizes that proper systems for purchasing, recruiting, and performance management are as critical as the core technology, and shares specific processes Science uses to scale efficiently.