Building the Physical AI Stack | Travis Kalanick on TBPN

Travis Kalanick returns to discuss his new venture Atoms, a company focused on industrial AI that automates physical tasks across multiple industries including mining, food production, and transportation. After previously operating separate companies for different verticals (mining/transport and food), Kalanick consolidated them into a single entity after investors expressed interest in backing him rather than specific business lines.

On the mining side, Kalanick describes visiting operations in the Amazon and the Saudi-Iraq border, where Atoms' autonomous haulage systems operate on 2-million-pound vehicles traveling at 35 mph. The technology increases productivity by 30-40% while improving safety and reducing operational expenses simultaneously. He explains the go-to-market strategy involves proving productivity gains to mining CEOs who want 20% more output annually, with pilots demonstrating human-level or better-than-human performance before full deployment.

The installation and commissioning process is complex because existing mining equipment wasn't designed to be drive-by-wire, requiring actuators and mechanical systems to enable autonomous control. Kalanick describes the long-term vision as 'no-entry mines' where humans are removed from active pit areas entirely, with remote control or fully autonomous operation as intermediate steps.

On the business model, Kalanick rejects percentage-based revenue sharing, instead using enterprise software pricing approaches where baseline pricing increases based on proven productivity outcomes. He emphasizes never pitching customers on giving up a percentage of profits, but rather charging for the value delivered.

Regarding hiring executives, Kalanick prioritizes problem-solving ability over pure management capability, arguing that the most important quality is strategic problem-solving at scale. He describes his management style as 'problem solver in chief,' where he identifies the most impactful unsolved problems and that mentality cascades downward through the organization.

On the transportation side, Kalanick frames it as 'wheelbase for robots'—specialized industrial robots that move through physical space. This includes autonomous freight vehicles for supply chains and 'autonomous burritos' (temperature-controlled food delivery boxes) that can deliver food for 75 cents versus the $12 per delivery that traditional services charge.

Concerning automation and job displacement, Kalanick argues that when automation reduces prices in an industry, surplus capital emerges for other activities. He points out that robots don't have bank accounts, so the money ultimately flows to humans, creating new opportunities. He references the historical pattern where certain jobs become extremely high-value (like plumbers earning LeBron-level wages) as other tasks become automated.

On regulation, Kalanick discusses his philosophy against seeking regulatory capture, arguing that insurances companies and trial lawyers have historically pushed rules that limit competition in transportation. He notes that insurance companies actually benefit from accidents within their actuarial tables, creating perverse incentives against autonomous vehicle adoption.

The company raised $1.7 billion and Kalanick indicates there will likely be a second close with other interested investors currently reaching out. He frames the investment thesis as giving him capital to execute across multiple industrial automation opportunities simultaneously rather than trying to pick winners in the physical AI space.