Going Infinite

What happens when a brilliant mind trained to maximize expected value finds himself building an empire based on human trust—something he never really understood? In Going Infinite, Michael Lewis delivers a riveting, close-up portrait of Sam Bankman-Fried (SBF), the MIT-trained quant trader turned crypto czar, whose stated mission was to earn as much money as possible for moral ends, but whose rational world collapsed into chaos. Lewis argues that SBF’s story is not just about the biggest financial scandal of its time—it’s about what happens when logic, math, and utilitarian ideals hit the messy world of human emotion and regulation.

Lewis, known for The Big Short and Moneyball, crafts this book as both biography and social x-ray. He contends that SBF wasn’t motivated by greed but by miscalculation: a man trained by math and the culture of high-frequency trading to quantify risk and utility, and who ultimately applied those skills to moral philosophy and, disastrously, to crypto finance. Yet beneath the rational surface lies a tragic blindness—one common to many modern techno-idealists—that numbers can trump relationships, empathy, and accountability.

A Man of Logic in a World of Emotion

The heart of Lewis’s argument is that Sam Bankman-Fried’s mind was optimized for systems, not people. Raised by Stanford law professors steeped in utilitarian ethics, SBF saw life as an optimization problem. As a child, he couldn’t comprehend why his peers believed in Santa Claus—or, later, in God. These early disillusionments with mass delusion led him to see humanity as irrational at scale, a tendency that would define his later business choices. When he discovered effective altruism—a movement encouraging people to make and give money according to measurable utilitarian values—it formed the backbone of his identity. He would make billions not to enjoy them, but to save the world.

But this moral clarity also became a trap. Lewis paints a picture of a man so consumed by maximizing outcomes that he ignored their human costs. At Jane Street Capital, the trading firm where SBF cut his teeth, he learned to reduce complex gambles into probabilities—a skill that served him well in markets but disastrously in public life. Every decision became a math problem. Should he move to the Bahamas? Yes—if the expected value of lower regulation and higher profits outweighed the risk of reputational damage. Should he date a subordinate, Caroline Ellison, who ran his hedge fund Alameda Research? Yes—if their alignment was “high EV.” Should he risk billions in customer deposits to fill a liquidity gap? The math might suggest yes, but reality didn’t follow his models.

From Quant Genius to Crypto King

Lewis traces SBF’s meteoric rise from MIT physics graduate to founder of digital-asset giant FTX. In a few short years, SBF became the world’s youngest multibillionaire and the “golden child” of crypto. His exchange promised the safety and precision of Wall Street trading combined with the speed and freedom of the blockchain. FTX grew by exploiting inefficiencies that larger institutions ignored, until venture capitalists and celebrities—Tom Brady, Larry David, and even regulators—lined up to anoint him the “JP Morgan of crypto.” To outsiders, he was a nerdy savior in cargo shorts promising to fix finance.

But behind the scenes, SBF’s empire was structurally flawed. His hedge fund, Alameda Research, secretly borrowed billions in customer deposits from FTX—money meant to be untouchable. Instead of a firewall, there was a backdoor code (written by his trusted partner Gary Wang) that let Alameda take infinity credit. SBF’s world began to unravel in 2022 when Binance's CEO, Changpeng Zhao (CZ), publicly questioned FTX’s solvency. A liquidity panic ensued, customers demanded withdrawals, and FTX didn’t have the funds. In days, the empire collapsed, revealing that its foundation—built on trust in an untrusting man—was hollow.

Effective Altruism and the Ethics of Scale

Lewis uses the lens of effective altruism to explore how well-meaning rationalism curdled into moral hazard. SBF sincerely believed in earning to give: ascend the money ladder not for pleasure, but to redistribute wealth more efficiently than governments or charities could. Yet, when your metric of success is “maximizing humanity’s utility,” it becomes easy to justify shortcuts. FTX wasn’t designed for crime; it was optimized for speed and control. But the logic of aggressive risk-taking—so natural in trading and in philosophy—met a financial system that runs on something SBF never understood: trust.

By weaving personal portraiture with systemic critique, Lewis turns the fall of FTX into a cautionary tale about the limits of rationalism in a world governed by human emotion, perception, and narrative. If the financial crises of the past were about greed, Going Infinite is about intelligence untethered from empathy. As you follow SBF’s rise, crash, and rationalization, you’re left asking: Can numbers capture the cost of trust betrayed—or the irrational beauty of human restraint?

Sam Bankman-Fried’s childhood reads like the origin story of a moral calculator gone haywire. Lewis reveals that Sam’s parents, Stanford law professors steeped in utilitarianism, raised him in a universe of logic, debate, and moral math. By age eight, he wasn’t just precocious—he was alienated from human irrationality. Discovering that most kids believed in Santa Claus shocked him; realizing that adults believed in God disturbed him. From those moments onward, Sam suspected that the majority of people simply accepted delusions because they were convenient.

Learning to Think Without Feeling

At school, he treated emotion as irrelevant data noise. When teachers graded English essays subjectively, he rebelled, dismissing literature as flawed for lacking probabilities. Even his first blog post—defending abortion through utilitarian reasoning—read less like youthful angst and more like a math proof for morality. Happiness, love, even spirituality were problems of utility curves. His mental model was Bayesian reasoning: update beliefs when new data arrive, but only if the data significantly change expected outcomes. (It’s what psychologists call “detached cognition”—an overly rational bias seen in some brilliant yet socially impaired minds.)

Magic: The Gathering and Math Camp

Two things finally made the young Sam feel alive: logic games and math competitions. Playing Magic: The Gathering and attending math camp gave him the intellectual communion he couldn’t find elsewhere. Both relied on incomplete information—what economists call “games of imperfect knowledge.” These games prefigured his approach to trading: quick probabilistic judgments under uncertainty. He befriended another math camper, Gary Wang, who would later become cofounder of FTX. The pair bonded over strategy, not sentiment—a relationship made of logic rather than intimacy, a pattern that would repeat his entire life.

Sam’s takeaway from those formative years? The world was irrational, messy, and usually wrong. Human error was the largest inefficiency in existence. And inefficiencies, to Sam, were markets waiting to be exploited.

The Utilitarian Incubator

From his parents he absorbed a calm belief that moral good could be calculated. That belief led him straight to Peter Singer’s philosophy and then to a young Oxford intellectual, Will MacAskill, who co-founded the Effective Altruism movement. During a chance meeting arranged by email, MacAskill persuaded Sam that rational philanthropy wasn’t just noble—it was an algorithm for life. The best way to save humanity wasn’t to fight diseases directly but to “earn to give”: make astronomical sums of money, then donate them to causes where each dollar bought the greatest increase in well-being.

That encounter reset Sam’s internal compass. Money, once irrelevant, became his means to moral infinity. From that point forward, his brilliance fused with purpose but detached further from reality. He was no longer unclear about what to do with his life—only indifferent to the moral assumptions that governed other people’s lives. Lewis suggests this clarity would later embolden him to take risks whose consequences he barely registered because, mathematically, they made sense.

Lewis devotes substantial attention to the period that shaped SBF’s methodical brain: his years at MIT and Jane Street Capital. These were less about wealth than about mastering probability. Jane Street trained employees not in emotional intelligence or leadership but in rapid probabilistic thinking. Interns played games to reveal cognitive blind spots. One game involved flipping ten weighted coins and deciding which to bet on; another, guessing the odds an interviewer had a professional baseball relative. Each was designed to reward probabilistic agility and punish overconfidence.

Jane Street: Where Math Ruled Morality

At Jane Street, trading wasn’t about predicting the future; it was about making decisions faster than others with incomplete data. Sam excelled. He could detach completely from fear and emotion, executing trades others couldn’t stomach. As colleagues said, he viewed the market as an endless game of “weighted coins.” But this environment also rewarded a moral numbness: traders bragged about “betting on bombs”—profiting from global chaos without blinking. For Sam, it wasn’t cruelty. It was optimization. If your algorithm showed positive expected value, you acted, regardless of discomfort.

When he pranked a fellow intern with a mathematically inevitable bet that humiliated his opponent, Jane Street called it a ‘learning exercise.’ For Sam, this detached moral laboratory proved intoxicating. It revealed that markets reward those who ignore emotion entirely. Yet, Lewis argues, it also stripped Sam of empathy—the very quality most necessary to run a business that holds other people’s assets.

Leaving Jane Street for a “Bigger EV Bet”

Despite rapid success—he was on track to make millions—SBF grew restless. Trading for Jane Street no longer maximized expected moral value. Inspired by Will MacAskill’s “earn to give” logic, Sam concluded he could save more lives by striking out independently in higher-risk markets. Crypto, still largely unregulated in 2017, presented itself as the perfect high-variance experiment. There were inefficiencies, arbitrage gaps, and naïve believers—exactly the kind of irrational field he’d been preparing for all his life.

Thus, the founding of Alameda Research, disguised to sound like a boring quantitative research firm, marked his leap into radical uncertainty. His goal was no longer to beat markets but to encode morality into every dollar. Ironically, this detachment from risk aversion—a skill honed at Jane Street—would later destroy him when trust replaced probability as the governing currency.

In founding Alameda Research, SBF assumed that markets obey numbers, not human rules. Lewis portrays Alameda’s first months as brilliant chaos: a handful of twenty-somethings in a Berkeley apartment, trading crypto across Asian exchanges while sleeping under desks. Alameda exploited inefficiencies so large they seemed unreal—buying Bitcoin in the U.S. and selling it 20% higher in Japan. But because real-world logistics (banking laws, currency limits) couldn’t be optimized like code, the team skirted legality. Sam saw every barrier as a math problem, not an ethical one.

Chaos Among Effective Altruists

Alameda’s core team recruited via the effective altruism community, creating a strange blend of moral philosophers and math geeks. What united them wasn’t greed but belief: that earning billions justified any shortcut if the long-term good was greater. But soon Alameda fractured. Staff clashed over Sam’s management—his indifference to planning, meetings, hygiene, or accountability. He slept at his desk, played video games during investor calls, and measured loyalty by how well others tolerated his disorder. When funds went missing, executives accused him of recklessness and deceit. Most quit; a smaller, more obedient team stayed—those who shared his logic that intent mattered less than outcome.

The Ripple Crisis and “How to Think About Bob”

Lewis recounts an early crisis that foreshadowed FTX’s downfall: Alameda’s $4 million “missing Ripple” incident. When Ripple tokens vanished mid-transfer, Sam refused to panic. He calculated there was an 80% chance the funds would reappear. Hence, no fraud—only uncertain math. This moment birthed Sam’s famous philosophical memo, “How to Think About Bob,” a thought exercise about whether to trust a friend after learning he might be a murderer. The parallel was clear: Sam viewed moral dilemmas as statistical inputs. His refusal to accept absolute guilt or innocence poisoned his decision-making. When he turned out to be right (the Ripple was found), his logic was reinforced. Risk, in his mind, was never moral—just probabilistic.

Lewis frames this as the turning point: Sam learned the wrong lesson. The people who stayed saw him as prophetic; those who left saw him as dangerous. Either way, he realized that loyalty—and later capital—grew fastest when others treated his unorthodox reasoning as genius. Alameda survived. But its internal code, shaped by Sam’s indifference to limits, became the blueprint for FTX’s fatal design.

With Gary Wang’s coding genius and Sam’s vision, FTX launched in 2019 as a crypto futures exchange promising safety through automation. It was, as Lewis puts it, “a casino where the house couldn’t lose—except it could.” On the surface, FTX was a masterpiece of engineering. Gary’s code liquidated risky positions by the second, preventing the runaway losses that doomed other platforms. The interface was clean; the spreads were tight. Silicon Valley fell in love. Sequoia invested; celebrities endorsed. Forbes crowned Sam a billionaire at 29.

The Paradox of Trust in a Trustless World

Crypto’s founding promise was freedom from middlemen, but FTX itself became the middleman everyone trusted. Sam pitched FTX as the efficient frontier of finance—faster than banks, freer than governments. Yet regulation lagged. Operating from Hong Kong, then the Bahamas, FTX thrived precisely because no adult supervision constrained it. “Trust me because I don’t care about money,” Sam said, and the world believed him. He wore wrinkled T-shirts, lived with coworkers, and donated to pandemic-prevention causes. His self-presentation—earnest, nerdy, apparently incorruptible—was his marketing. As Lewis notes, the irony is cosmic: a man incapable of small emotional lies built a global empire on human faith.

Branding a Billion-Dollar Idealist

FTX’s marketing arm, run by Natalie Tien, targeted cultural ubiquity. Stadiums, Super Bowl ads, Tom Brady, and Gisele Bündchen—every symbol of credibility was for sale. Sam disliked it but saw the logic: if trust was currency, celebrity endorsements were the printing press. FTX became a household name overnight. Yet this success detached SBF from control. The company grew beyond his Bayesian brain’s capacity to model. Real-life complexity—staff emotions, government politics, reputation—couldn’t be optimized. When regulators came calling, he started paying lobbyists, thinking, “expected value positive.” Noble intentions became indistinguishable from manipulation.

Lewis’s portrayal of FTX’s rise doubles as an anthropology of Silicon Valley hubris: visionary impracticality posing as genius. Sam’s moral detachment, once his edge, was now his flaw. FTX worked perfectly as a concept—but real markets are run by humans who panic, distrust, and retaliate. The moment CZ of Binance questioned FTX’s solvency, one tweet was enough to implode it all.

When Binance’s CEO triggered a sell-off of FTX’s token (FTT) in November 2022, Sam treated it like another market blip. But this time, math couldn’t model the emotional contagion of fear. Customers rushed withdrawals totaling $5 billion in days. On FTX’s books, those funds should have been waiting. They weren’t. Secret code had allowed Alameda to borrow unlimited amounts using FTT as collateral. As Lewis writes, Sam’s empire was “built on the illusion of infinite liquidity.”

A Rationalist Confronts the Abyss

Even as billions vanished, Sam refused to admit catastrophe. To him, this was a liquidity mismatch, not theft. He clung to Bayesian optimism: some high-probability solution would emerge. While investors demanded answers, he called Elon Musk about buying Twitter and brainstormed political donations. Gary and Nishad panicked; Caroline fled; employees cried. Lewis shows him wandering the empty Bahamas office barefoot, murmuring to himself, “Saturday everything was normal.”

His reaction baffled everyone. Was it denial or discipline? When someone asked him if he’d knowingly misused customer money, Sam called it a “banking error.” That phrase, Lewis suggests, captures the moral vacuum at FTX: an inability to distinguish catastrophe from calculation. He hadn’t planned a crime—but neither had he acted humanly enough to prevent one. In his world of numbers, intent determined guilt, and his intent had been pure.

The Aftermath of Infinite Thinking

By the time prosecutors arrived, FTX’s inner circle had scattered. Nishad contemplated suicide; Caroline confessed publicly; Gary turned witness. Yet Lewis retains empathy for Sam, portraying him less as villain than as tragic type—a modern Icarus of intellect. His final months, communicating from house arrest under the watch of his parents and a German Shepherd named Sandor, highlight the irony: a man who sought to save the world by reason couldn’t save himself from his own miscalculated ethics. Going Infinite, ultimately, is about how intellect unmoored from humility becomes the most dangerous form of ignorance.