Elon Musk’s Lessons From Hell: Five Commandments for Business

Simply put: Elon Musk can be a real jerk.

And that has probably helped and hurt him in business, according to a new biography by Walter Isaacson.

In “Elon Musk,” out Tuesday, Isaacson puts forth the idea of “demon mode” to explain the temperamental impulses behind some of the tycoon’s successes—and setbacks. But it isn’t just demon mode that has fuelled his rise. Isaacson details other teachable ways the billionaire’s methods have helped make him the world’s richest man.

Both sides of Musk are sure to become part of B-school lore for a new generation of would-be entrepreneurs and business managers picking and choosing which traits and tactics to emulate.

Isaacson had previously made the concept of the “reality distortion field” popular with his bestselling 2011 book about Apple co-founder Steve Jobs and his ability to bend perception to motivate others.

Demon mode was on display in 2018 as Musk struggled to ramp up production of Tesla’s Model 3 sedan, which nearly destroyed the electric-car company and which the CEO dubbed production hell.

That experience through hell, the book says, also helped Musk shape five commandments for how he wants problems solved by his workers across his companies, from rocket maker SpaceX to social-media platform X, formerly Twitter.

Musk, in the book, calls the framework for problem solving “the algorithm.” In short, Musk urges his employees to:

Question every requirement
Delete any part or process you can
Simplify and optimise
Accelerate cycle time
Automate

“His executives sometimes move their lips and mouth the words, like they would chant the liturgy along with their priest,” Isaacson wrote of Musk’s mantra.

In the book, Musk acknowledges he talks about the approach often. “I became a broken record on the algorithm,” Musk is quoted as saying. “But I think it’s helpful to say it to an annoying degree.”

The approach builds off a long-held method for problem solving touted by Musk called first principles, a reasoning that breaks tasks into their very basics without simply reverting to what has been done before.

“The algorithm is a five-step process for not only making good products and designing good products, but manufacturing them,” Isaacson said in an interview Monday.

Throughout his book, Walter Isaacson chases the question of whether Elon Musk could be successful any other way. PHOTO: ARIEL ZAMBELICH/THE WALL STREET JOURNAL

“It begins with first principles. He says, question every requirement, and, by first principles he means, look down at the physics. If somebody says, no, we can’t build it at this price, he says, tell me how much the materials cost. Tell me exactly what’s involved here and then tell me you can or can’t do it.”

There are other lessons in the book that Musk has long practiced, such as never asking an employee to do something you aren’t willing to do (hence his sleeping on factory floors), hiring employees based on their attitude, and saying “it’s OK to be wrong. Just don’t be confident and wrong.”

Telling Musk bad news, however, has been seen by some employees as dangerous to one’s career.

“One of his problems is people sometimes are afraid to tell him the bad news,” Isaacson said. “Those who succeed around Musk are those who figure out you got to give him the bad news even if it’s going to result in some unpleasant scenes.”

Their fear is often rooted in demon mode.

Claire Boucher, known as the musician Grimes and the mother of three of Musk’s children, coined the term in an interview with Isaacson.

“Demon mode is when he goes dark and retreats inside the storm in his brain,” Boucher said in the book. “Demon mode,” she added, “causes a lot of chaos but it also gets s— done.”

And Musk has gotten a lot done, helping usher in the electric-car era as Tesla chief executive and igniting the commercial space race with SpaceX, which he founded. His messy stewardship of X, however, is testing public perception of his business genius.

Isaacson, who shadowed Musk for two years in reporting the book, saw demon mode in person several times along with other personalities that he described as ranging from silly to charming. He suggests the roots of the dark clouds come from the 52-year-old’s childhood in South Africa.

“It’s almost like Dr. Jekyll and Mr. Hyde where a cloud comes over and he gets into a trance and he can just be tough in a cold way,” Isaacson said. “He never gets really angry, never gets that physical, but coldly brutal to people and he almost doesn’t remember afterwards what he’s done. Sometimes I’ll say, why did you say that to that person? And he’ll look at me blankly as if he didn’t quite remember what happened while he was in demon mode.”

In one instance, Isaacson described seeing demon mode emerge when Musk saw SpaceX’s launchpad in South Texas empty late one evening.

“He orders a hundred people to come in from different parts of SpaceX from Florida, California so they can all work for 24 hours a day getting this thing done even though there was no need to,” Isaacson said.

Such surges seem to play in tandem to Musk’s need for drama.

“He is a drama magnet,” Musk’s younger brother, Kimbal, said in the book. “That’s his compulsion, the theme of his life.”

Isaacson cautions that readers shouldn’t come away thinking they can be just like Musk and automatically succeed. Rather, he said, readers should see both how leaders such as Musk and the late Jobs were effective and also take away cautionary tales.

“You don’t have to be this mean,” he said.

Still, throughout his book, Isaacson chases the question of whether Musk could be successful any other way.

“I try to show how that’s one of the strands in a fabric and as Shakespeare said, we’re moulded out of our faults,” Isaacson said. “If we pull that strand out, you might not get the whole cloth of Elon Musk.”

For decades, the world’s computing power has quietly expanded at an astonishing pace.

From the first transistor developed at Bell Labs in 1947 to modern processors containing billions and even trillions of transistors, each generation of technology has been faster, smaller and more powerful than the last.

But according to quantum physicist and technology entrepreneur David Reilly, that era of effortless progress is beginning to slow.

Reilly, CEO of Sydney-based Emergence Quantum and Professor of Physics at the University of Sydney, says the computing infrastructure underpinning modern economies is approaching fundamental physical limits.

And that could have enormous implications for finance, artificial intelligence and global investment.

Speaking at an industry event organised by Kanebridge International, Reilly said many critical parts of modern society depend on computing and the infrastructure used to process information.

The slowdown behind the tech boom

For years, the technology industry relied on a steady improvement known as Moore’s Law, where the number of transistors on a chip doubled roughly every two years.

More transistors meant more computing power, allowing faster software, smarter devices and ever-larger data systems.

Today, however, those gains are slowing.

“It feels to me very innate that I’m going to just find that next year there’s going to be another breakthrough,” Reilly said.

“But if you look at the data…there’s a slowing down, a roll off in performance that started some 10, 20 years ago.”

Rather than making chips dramatically faster, manufacturers are now largely increasing computing capacity by packing more transistors onto each processor.

The approach works, but it comes with growing complexity, higher costs and increasing energy demands.

The brute-force race for AI

That challenge is already visible in the massive data centres being built to support artificial intelligence.

In the race to dominate AI, companies are constructing vast computing facilities that consume huge amounts of electricity and water. Reilly described this expansion as a “brute force” approach driven by the global competition to develop advanced AI systems.

Yet the demand for computing power continues to accelerate.

Artificial intelligence, advanced robotics, healthcare research, pharmaceuticals and cybersecurity all require far more processing capacity than today’s systems can easily deliver.

The question now facing the technology sector is whether traditional computing can keep up.

Enter quantum computing

That is where quantum computing enters the conversation.

Unlike conventional computers, which process information using binary switches that represent ones and zeros, quantum computers exploit the unusual behaviour of particles at the atomic scale.

Reilly describes them as a fundamentally different type of machine.

“So a quantum computer is a wave computer,” he said.

Instead of processing information through simple on-off switches, quantum systems can use wave-like properties of particles to process many possible outcomes simultaneously.

Those waves can interact in complex ways, reinforcing correct solutions while cancelling out incorrect ones. In theory, this allows quantum systems to tackle certain types of problems dramatically faster than classical computers.

What it could mean for finance

The concept may sound abstract, but its potential applications are significant.

Quantum computers are expected to transform areas such as materials science, chemical modelling and pharmaceutical development.

They could also help solve complex optimisation problems in logistics, finance and risk management.

For financial institutions in particular, the technology could offer new tools for detecting fraud, analysing market behaviour and optimising portfolios.

But the shift will not happen overnight.

“One message to take away is that quantum is not going to suddenly solve all of your problems,” Reilly said.

Instead, he said quantum systems will likely complement existing computing technologies as part of a broader and more diverse computing ecosystem.

Why data centres may soon “go cold”

One key change already emerging is how computing systems are physically designed.

Many next-generation technologies, including quantum processors, operate far more efficiently at extremely low temperatures. As a result, future data centres may rely heavily on cryogenic cooling systems to manage heat and energy consumption.

Reilly believes that the shift will gradually reshape the computing industry.

“Over the next five years, you’re going to see data centres go cold,” he said.

“And as that happens, they almost drag with them new compute paradigms.”

Emergence Quantum, the company he co-founded, is focused on developing technologies to support that transition, including cryogenic electronics and integrated hardware platforms designed for quantum computing and energy-efficient systems.

A new technological era

For investors and businesses, the technology remains in its early stages. But the scale of global interest is growing rapidly.

Governments, research institutions and technology companies are investing heavily in quantum research, betting it could become a foundational technology for the next generation of computing.

For Reilly, the moment feels similar to earlier technological turning points.

In the 19th century, new discoveries in thermodynamics helped drive the development of steam engines and the Industrial Revolution. In the 20th century, advances in electromagnetism led to radio, television and eventually the internet.

Quantum physics, he suggests, could represent the next chapter in that story.

“Today we have, as a society, in our hands new physics that we’re just beginning to figure out what to do with,” Reilly said.

“But I think it’s an exciting time to be alive and watch what happens over the coming decades.”