Thomas Laffont, Coatue - Anthropic, Citrini Paper, AI Volatility & Next Mag 7

Summary

• In a discussion of Anthropic’s announced $30B fundraise, Laffont says the projections and scale of the business grew materially during the roughly two-to-three-month process. He thinks the disclosed revenue was “something in excess of $13 or $14 billion or something like that,” materially lower when discussions began. He points to Claude Code adoption—its inventor Boris, a friend who worked at Coatue for 2.5 years developing software—and a repeating board-deck pattern: one slide said spend on the tool was “way too low” and expected to at least triple next year.
• The Mag 7 has been “essentially flat over the past year or so,” with Microsoft shedding “almost $1 trillion,” and Laffont’s candidates for the next index are SpaceX, OpenAI, Anthropic, Revolut and Databricks. “If you want to outperform the index over a long period of time, you’re going to need exposure to these companies” — some of them will probably go public in the next twelve to twenty-four months.
• On the Centrine paper: he rejects the fire-in-a-crowded-room analogy and says early discussion is healthy. “By definition, if everyone thinks we’re in a bubble, then we’re not in a bubble” — and he’d “much rather have daily volatility and daily questioning than no volatility or no questioning, followed by a massive crash three years later.”
• His SaaS re-rating math is stark: Workday growing 13% organically at 28–30x GAAP earnings versus Avago growing “almost 40%” at a cheaper multiple. Either AI re-accelerates the top line or multiples settle at “some version of twenty-ish times GAAP earnings” — and a third, sentiment-driven bucket looms: “in three or four years, if Claude Code can rewrite their entire business,” terminal value is “harder for companies to control.”
• On the “sixty-four-trillion-dollar question” of software jobs, not one company he’s involved with is saying “we want to cut our engineering staff in half.” They hope engineers become more productive and enable new features. He asks whether companies such as Rippling could shift from selling software to selling “the work of an HR professional,” while keeping open the possibility of fewer outsourced engineers in India. His anti-doomer example is the ATM: a 1970s NYT article predicted 70% teller-job cuts, but teller jobs exploded through the early 2000s as cheaper branches multiplied.
• His “BFI” (big fucking idea) framework dismisses pitched TAMs: what matters is whether the TAM grows 2–3x over five-to-ten years and whether new TAMs get added, as Uber grew the taxi market “five or 10x” then added grocery and food. His biggest early Apple error was modeling the phone’s price declining 5% over five years — “the opposite happened.”
• The under-discussed half of Coatue, highlighted in his lesson from brother Philippe, is risk management — forged after the fund launched in December 1999 and the market fell “80%” over about two and a half years. “Your formative years as an investment manager will stick with you like a face tattoo over the next decades” — and “the ability to endure and compound is what really defines generational investing firms.”

Deep dive

1. Anthropic’s numbers moved during the raise — and board decks confirm the pattern

• Laffont on Anthropic’s $30B fundraise: “the projections and the scale of the business grew materially” between the raise being discussed and being announced — a process he says usually takes about two to three months — with revenue disclosed, he thinks, as “something in excess of $13 or $14 billion or something like that,” materially lower when discussions began. He points to Claude Code adoption; its inventor Boris, whom he calls a friend, worked at Coatue for two and a half years developing software. Laffont says Coatue did not predict Claude Code would take off so quickly.
• The signal he trusts: fresh off six or seven board meetings, he says most companies now report AI-tool adoption to their boards, all wanting to use the best tools and avoid being outcompeted by someone using them. One slide said: “we’re spending X on this tool, and we think it’s way too low… we expect the spend to at least triple next year.” His read: “board decks are such a treasure trove,” and repeated patterns across companies indicate something big. He says Cortex, Claude Code and others are benefiting from that pattern.

2. The next Mag 7 is still private

• His default is public markets — transparency, liquidity and access — reinforced by the newly discussed “Trump Accounts” for children when they are born. Broader access to these companies will come from both ends: incentives to go public and “more methods to democratize access to private companies.”
• The setup: the Mag 7 has been “essentially flat over the past year or so,” with Microsoft losing “almost $1 trillion of value” as investors question its AI positioning. His candidates to fit into a future index are SpaceX, OpenAI, Anthropic, Revolut and Databricks — “it is unbelievable, the amount of innovation that is now coming from this group of companies.” Some of them will probably go public in the next twelve to twenty-four months.

3. Centrine isn’t fire in a crowded room — and daily volatility beats a delayed crash

• On the Centrine paper: “I don’t think that screaming ‘Fire!’ in a crowded room is obviously productive or safe… Some people have made that analogy to the report, and I don’t share it.” He nonetheless thinks bringing these conversations up early is important: “by definition, if everyone thinks we’re in a bubble, then we’re not in a bubble.”
• Living the volatility daily, he still prefers it: “I would much rather have daily volatility and daily questioning than no volatility or no questioning, followed by a massive crash three years later.” Constant questioning forces governments, companies, executives and founders to be “constantly… worried and aggressive” about what AI could do to their businesses — which he considers healthy.

4. SaaS math: 13% growth at 30x GAAP does not survive next to Avago at almost 40%

• The framework is opportunity cost: SaaS earned its premium by compounding in the mid-20s to low 30s when few other sectors offered comparable growth. Now Workday is growing organic revenue at about 13% yet trades around 28–30x GAAP earnings, which investors are increasingly treating as the gold standard, while Avago grows almost 40% at a cheaper GAAP-earnings multiple.
• Either companies benefit from AI and reaccelerate the top line, or multiples re-rate to “some version of 20-ish times GAAP earnings.” Workday is an example of a founder stepping back in to help lead the next chapter; CEO Aneel says his job is to reaccelerate the company through AI.
• The third bucket is the threat of AI to terminal value, rather than necessarily to current valuation or business: “in three or four years, if Claude Code can rewrite their entire business, what happens?” That question is “much more sentiment-driven,” harder for companies to control in the near term, and ultimately affected by product execution.

5. Selling work, not software — and why he’s not a doomer

• On whether the Bay Area’s roughly 400,000 software engineers will increase or decrease — “the sixty-four-trillion-dollar question” — Laffont says not one company he’s involved with is saying, “we’re seeing so much more efficiency. We want to cut our engineering staff in half.” Instead, they hope engineers become significantly more productive and can build features that were previously impossible.
• He sketches a conditional category shift: what if companies such as Cursor in R&D or Rippling in SG&A move from selling software to selling work? For Rippling, that could mean having the system handle routine HR requests and allowing an HR professional to shift from operational work toward strategy.
• His load-bearing example is the ATM. A famous 1970s New York Times article predicted a 70% reduction in branch-teller jobs, but teller jobs exploded from the 1970s through the early 2000s because lower branch costs enabled many more branches. He adds that there may be fewer outsourced engineers in India, but says the overall effects remain uncertain.
• At Coatue, someone recently brought in from Goldman Sachs who is “Claude-native” is pushing coding-first approaches throughout the organization. Coatue is not looking to cut its investment staff in half; if the tools make them significantly better, “we’ll want to hire more of them, not less.”
• Molly’s example was a hedge-fund sector head who told her that 85% of his job could be automated. Laffont says big-idea investing is “both creative and actually reflective of someone’s taste”; whether machines assist or replace that creative process, “we’ll see.” He uses the tools daily for communication, email and difficult problems and says, “I’ve found that they make me better.” His iPhone example recalls the 2007 objections that it needed a keyboard, lacked Flash and did not support 3G.

6. BFI: ignore the TAM, watch TAM growth — and risk management as a face tattoo

• The “big fucking idea” framework keeps the swear word because it should jolt people. Laffont’s view is that the absolute size of a pitched TAM is irrelevant. What matters is whether the TAM becomes 2–3x larger over five to ten years and whether additional TAMs get added.
• Uber illustrates both: the taxi TAM grew “five or 10x” because the product reduced friction, then Uber added grocery and food. Apple and the iPhone are another example. One early bear case was that there was not enough TAM for handset manufacturers, which “already represented 150% of the gross profit of the handset industry.” Laffont’s biggest early Apple mistake was modeling the phone’s price declining 5% over five years; “the opposite happened,” and services added further TAM.
• The lesson from Philippe is that innovation and big-idea investing are only half of Coatue; the other half is risk management. The fund began in December 1999, and the market fell 80% over roughly two and a half years. “Your formative years as an investment manager will stick with you like a face tattoo over the next decades.” The firm believes enduring and compounding define generational investors, including seeking liquidity in secondary or public markets when it is not the most in-vogue choice.