In an era of trillion-dollar bets on AI and whiplash-inducing market swings, Nicolas Giauque has a blunt message for investors who’ve grown too comfortable with their conviction: Check yourself.
“An investment thesis is not a religion,” said Giauque, managing partner and chief investment officer of Farallon Capital Management, in a recent interview on Goldman Sachs’ Exchanges: Great Investors podcast, previewed exclusively with Fortune. “It should be provably wrong. If you haven’t figured out how you can lose money, you haven’t thought long enough.”
Giauque oversees $44 billion in assets at the San Francisco–based multi-strategy hedge fund—a firm that has had just one down year since its founding in 1986. That record, he argued in conversation with Tony Pasquariello, global head of hedge fund coverage at Goldman Sachs’ global banking and markets division, isn’t the product of clairvoyance. It’s the result of a relentlessly probabilistic mindset, one that demands every investment thesis be stress-tested against its own failure before a single dollar is deployed. It’s not for nothing that he calls himself a “self-aware paranoid optimist.”
Merger arbitrage as a mental model
Giauque told Pasquariello that his discipline traces directly to Farallon’s origins in merger arbitrage. The strategy is deceptively simple in structure: Buy a target company’s stock after a deal is announced, collect the spread when the deal closes. But the intellectual rigor it demands—mapping precise upside and downside scenarios, assigning honest probabilities to each—shaped how the entire firm thinks about risk.
“You can very easily determine your downside, which tends to be the pre-deal price, and your upside, which is the deal price,” Giauque said, explaining that doing so “forces you to think in probabilistic terms.” He shared a little bit of his method: thinking forward to the postmortem before taking a position. Imagine the investment has already failed. How did it happen? What did you miss? Assign a probability to that scenario, then decide if the expected value still holds.
“There’s more ways to lose money than can be ascertained that first instance,” he said. This means that you have to always push yourself for more scenarios about what could go wrong: “Challenge yourself in your hypothesis.”
It’s a framework that has been stress-tested in real time. Giauque pointed to 2008 as the period that most severely tested the firm’s principles—a moment when systematic risk cascaded globally, and market behavior defied almost any prior model. But he noted that “negative outcomes” since then were already anticipated, “understood before the fact, ex ante,” and the firm was prepared for them. That, he suggested, is the goal: not to avoid being wrong, but to have already priced in the possibility.
The strategy’s demands become clear when you look at how Farallon has deployed it in practice. When British Telecommunications announced its $25 billion acquisition of MCI Communications in 1996—the deal that first put Farallon on the map—the firm took a long position in MCI and a short position in BT, then had to hold its nerve when MCI disclosed unexpected problems breaking into the local telephony market, forcing the kind of granular reassessment of probabilities that the strategy demands at its best.
Two decades later, the same discipline was on display when Microsoft announced its $26.2 billion acquisition of LinkedIn: Farallon moved in to capture roughly $6 per share on the spread between the prevailing price and the deal’s closing price—a bet that looks straightforward on paper, but only after someone has done the hard work of mapping every regulatory, financial, and competitive scenario that could cause it to fall apart. That quiet, unglamorous, and relentlessly precise work is the firm’s original DNA.
The AI trade—inside and out
True to his comprehensive investing nature, Giauque said he was bullish on artificial intelligence even as he warned that it could blow a hole in one of the hottest corners of finance.
He told Goldman Sachs that AI is “the single-most exciting area in the world right now”—and that Farallon is actively rolling out AI tools internally to support investment analysis. That puts the firm in step with a broader Wall Street push: Hedge funds are increasingly deploying AI for everything from earnings call analysis to pattern recognition across filings, enabling analysts to reach investment theses faster than ever.
But Giauque said he was equally focused on AI’s destructive power—particularly its potential to upend the software-as-a-service (SaaS) businesses that underpin a staggering share of private credit portfolios.
“Those disruptions that come from AI’s involvement in SaaS but also in asset-light businesses will have meaningful impact on those portfolios,” he said. “There will be many winners, and there will be many losers.”
The numbers back up his concern. SaaS company stocks collapsed nearly 30% between October 2025 and February 2026, as fears mounted that AI agents would displace traditional per-seat software models. According to the Bank for International Settlements, outstanding loans to SaaS firms in private credit have grown from roughly $8 billion in 2015 to over $500 billion—about 19% of total direct loans—by the end of 2025. Morgan Stanley estimates software now accounts for approximately 26% of direct lending exposure, with default rates potentially rising to 8%, far above the historical average of 2% to 2.5%. UBS puts the potential damage even higher, estimating default rates could hit 13% if AI disruption accelerates—more than three times the projected high-yield default rate.
Giauque’s reading is measured but pointed. He said he doesn’t expect a 2008-style systemic crisis—“I do not expect there to be a systematic risk associated with this”—but he’s positioning Farallon to capitalize on the fallout. The real opportunity, he argued, won’t fully materialize until 2027 and beyond, when defaults mount, and balance sheets need restructuring.
The marathon mentality
Giauque, who joined Farallon in 1998 after four years at Goldman Sachs, is now the firm’s third CIO in its history—a transition he said reflects the same disciplined, ego-free culture that drives investment decisions. Asked to describe his greatest strength as an investor, he offered a characteristically self-critical answer: “I’m a self-aware paranoid optimist.” Knowing your own biases, he said, is a prerequisite for managing them.
And the best piece of advice he’s ever received? “Life is a marathon, it’s not a sprint.”
In Giauque’s telling, that applies as much to the AI disruption reshaping his portfolio as it does to a 40-year career in markets. The cycle is coming, according to Giauque. The question is whether you’ve already thought through how you lose.
