The Playbook That Elon Musk Relies On to Make His Wild Ideas Work
The entrepreneur is sticking with his tried-and-true formula to build a giant chip factory
March 27, 2026 8:00 pm ET
https://www.wsj.com/tech/ai/the-playbook-that-elon-musk-relies-on-to-make-his-wild-ideas-work-f41138f1?mod=hp_lead_pos9
Anyone can tap in to the powerful management techniques behind Elon Musk’s success.
At least that’s the thesis of a just-released book by former Tesla TSLA -2.76% President Jon McNeill. “The Algorithm” argues there are five steps that explain how Musk wants his teams at the electric-car company and rocket-maker SpaceX to operate.
“Much of the genius in Musk’s companies come from the legions of smart people empowered by the Algorithm,” McNeill writes. “They’re chasing stretch goals with free license to question everything and innovate boldly.”
That philosophy was on my mind as I watched Musk’s most recent event to announce plans for a joint project between Tesla and SpaceX to build the world’s largest AI chip factory.
The so-called Terafab, he said, would far exceed what all of the chip fabrication plants, or fabs, on the planet can currently make. Not the sort of thing a car company or a rocket maker would naturally get involved in doing, especially given the risks of entering a competitive and different industry.
Yet AI chips are at the heart of his vision for billions of robots being made a year globally and space missions to the moon and Mars. The goal is simple, he told an audience in Austin, Texas, recently: “Turn science fiction to science fact.”
So what exactly is the Algorithm? A series of deceptively simple steps: 1) Question every requirement. 2) Delete every possible step in a process (or part). 3) Simplify and optimize. 4) Accelerate cycle time. 5) Automate.
The approach was first detailed in Walter Isaacson’s 2023 biography “Elon Musk.” It was Isaacson who encouraged McNeill to write his own book that goes into depth about how the Algorithm works, the new author said.
McNeill, who left Tesla in 2018, was a key deputy during Tesla’s struggle to develop the game-changing Model 3 sedan and ramp production of the Model X SUV.
During that time, the framework for solving problems became so routine, by McNeill’s telling, that one executive at Tesla suggested calling it the Algorithm so they could better communicate the approach throughout the company.
It is rooted in the first principles thinking popular with Musk, McNeill told me for an episode of the “Bold Names” podcast.
“First principles thinking to me is the lowest common denominator of the problem in the elements of the problem—so like I think about breaking the problem down to…atomic level,” McNeill said.
Pulling it off correctly is beyond basic—even for Musk.
The Terafab, which some have estimated could cost $20 billion or more, has all of the hallmarks of the Algorithm.
Musk and others are investing heavily to build more computing power to fuel AI development. Key hurdles are AI chip supply and energy required to power data centers.
Part of SpaceX’s recent AI strategy is a shift toward building data centers in outer space, where solar power is abundant and, Musk says, will eventually be cheaper than operating on Earth.
But a chip supply shortage is crimping that dream. The world’s suppliers combined are making about 2% of what Musk said his companies need for Tesla’s robotcars and humanoid robots, and SpaceX’s AI data centers, to fuel his AI ambitions with xAI.
Musk said he has been trying to encourage suppliers to expand capacity quickly, but there’s a maximum rate they’re comfortable doing.
Most in business would probably say they’re stuck waiting. Not Musk.
“That rate is much less than we would like, and so we either build the Terafab or we don’t have the chips, and we need the chips, so we’re gonna build Terafab,” Musk said.
That gets to the Algorithm, McNeill told me: If Musk wants to control his own destiny, there’s no requirement that he buy chips from someone else.
“Elon has three businesses that all depend on chips, and he understands that dependence as a single point of failure,” McNeill told me in a follow-up email.
Musk’s next moves are being met with skepticism, especially as he prepares to take SpaceX public this year. Why would these companies want to get into the complicated and expensive business of making chips?
The case for the Terafab probably isn’t helped by grandiose ideas that Musk has touted in recent years that fizzled out—such as aiming to scale Tesla to build 20 million vehicles a year. (The company delivered 1.6 million vehicles last year.)
But supporters point to his success turning Tesla into an EV powerhouse and SpaceX into the dominant player in the burgeoning space economy as examples of what can happen when Musk succeeds.
The Algorithm was honed during years of struggle. Supplier bottlenecks have been huge issues for Musk’s manufacturing companies. That’s especially true in dealing with new technologies where everyone isn’t as confident as Musk is about the size of a potential new market.
Shortly after the success of Tesla’s Model S sedan, for example, Musk began making plans for building a giant battery factory. Similar to now, Musk envisioned requiring more batteries for EVs than the world was producing and he wanted to jump-start things.
Eventually, Tesla would convince battery supplier Panasonic to open a giant factory in Nevada, an important part of making the Model 3 successful.
A key ingredient to the Algorithm, McNeill told me, is the sense of urgency that it injects into everyday work. For Musk, that means latching on to one or two existential issues and riding them week after week.
“I used to sit in those meetings, saying I’m pretty dang sure that our competitors’ CEOs are not sitting in these weekly engineering reviews and not driving their companies as fast,” McNeill said. “Therefore we’re compounding an advantage against them.”
Today it’s clear that Musk’s new urgency is around AI in space.
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