What Tesla and Zoox Should Learn from Waymo
Operational Mastery demands choosing agility over control.
By Patrick Hunt
In Deep Tech hardware, if you don’t follow the principles of Operational Mastery, you’ll probably go bankrupt. That’s not an exaggeration - I’ve seen it happen too many times. I’ve written before about Operational Mastery, but to quickly recap: Resolve technical risk first, then demand risk, and finally execution risk. Attempting them in any other order or all at once will end in disaster.
Waymo’s Winning Blueprint
Waymo’s journey is a masterclass in Operational Mastery. It systematically retired technical risk before engaging customers, avoiding premature hype. From its inception in 2009 until 2015, Waymo kept its cars off public roads. Even when Waymo started offering public rides in 2018, it was still in a controlled environment with safety drivers - a phase better described as advanced product testing than customer acquisition.
With the technology working, Waymo then turned its focus to demand risk. Charging for rides in Phoenix began in 2020, followed by expansions to San Francisco in 2022 and Los Angeles in 2024. Waymo won approval to begin charging for rides in California in 2023 and now serves over 150,000 paid rides (and 1,000,000 miles) per week. Customers love Waymo.
While Waymo is well known for incredible technology, its approach to execution risk has been under-discussed. Managing an autonomous fleet is a complicated operation. Each local market team needs to optimize pricing, maintenance, vehicle utilization, facilities, charging, routing, and fleet size. Waymo is maturing these operations in real time, progressing down a learning curve every competitor will have to repeat.
But Waymo’s execution stands out not for what it did - it's what it didn’t do.
The Path Not Taken: Firefly’s Legacy
In 2014, Waymo unveiled the Firefly - a custom vehicle with no steering wheel or pedals, designed to be a dedicated robotaxi. A dedicated robotaxi promised several benefits, such as stronger branding and tighter hardware integration. And yet, in 2017, Waymo abandoned the Firefly entirely. Why?
The answer reveals Waymo’s deep understanding of execution risk. Car production only becomes cost-effective at a massive scale - typically around 50,000 to 100,000 units per year. Building capacity at this scale would have demanded capital, manufacturing expertise, and executive bandwidth. Without revenue to match these costs, finances would get unstable quickly. But, most critically, committing to a custom vehicle would have constrained Waymo’s flexibility, binding every part of their business - tech development, market expansion, fleet operations - to the grueling timelines of vehicle production.
The Firefly would have become a financial, strategic, and operational anchor - a drag on Waymo’s chances of success. In opting to buy vehicles from established automakers, Waymo chose agility over control.
The Dedicated Robotaxi: An Expensive Mistake in the Making
Seven years after Waymo’s decision to abandon the Firefly, Tesla unveiled the Cybercab — a dedicated robotaxi slated for production in 2026. Zoox, too, is committing to its custom vehicle. These announcements raise more doubt than confidence.
The maturity of Zoox’s technology is unclear, but Tesla has certainly not finished retiring technical risk. Neither firm has acquired customers or built robotaxi operations. Yet both are committing to a vehicle design that will consume vast amounts of capital and management bandwidth.
Consider Waymo’s current run rate of 1,000,000 miles per week. If a robotaxi lasts 200,000 miles, Waymo is on pace to consume about 260 vehicles per year. The run rate is growing, but it will have to grow about 200x before dedicated vehicles are economical. And Waymo’s been doing this for four years.
Tesla and Zoox display a profound misunderstanding of execution risk. If they stay committed to the dedicated robotaxis, they will have less capital to invest in technology, demand, and fleet management operations. They will also have less strategic flexibility, as their timing, pricing, market expansion, and fleet size will be driven by the constraints of vehicle development and manufacturing. By committing to these vehicles, they are violating Operational Mastery, refusing to address execution risk last.
Squandering the Late Mover Advantage
Later market entrants typically learn from the successes and failures of first movers. Google wasn’t the first search engine, and the iPhone wasn’t the first smartphone. While Tesla and Zoox will be disadvantaged as they follow Waymo on the learning curve, they will have the advantage of learning from Waymo’s example. By canceling the Firefly, Waymo showed the value of preserving capital and maintaining flexibility. But Tesla and Zoox seem intent on making a mistake Waymo carefully avoided. Dedicated robotaxis could be the anchor that drags down these would-be Waymo challengers.