With Harry Stebbings, Jason Lemkin, and Rory O’Driscoll
We’re back!
Ramp data put a number on what OpenAI has been avoiding: 73% of new enterprise AI spending is going to Anthropic. Ten weeks ago it was 50-50. That shift — plus a Figma stock rout, a $100B Bezos bet on AI-transformed manufacturing, a $20B Grok deal that cost founders roughly 60% in effective taxes, and the uncomfortable math on unicorn exits — made for a dense week.
The bigger story underneath all of it: we are past the point where enterprise buyers are browsing. They are locking in. And for the companies on the wrong side of that lock-in, the window is closing faster than anyone is willing to say out loud.
Top Takeaways
Anthropic Is Winning the Marginal Enterprise Buyer — and That’s the Only Number That Matters
OpenAI still has more total enterprise spend than Anthropic. That’s not the point. The point is the marginal buyer — the company making a new AI decision right now — is going 70% Anthropic. That’s the leading indicator. And OpenAI’s response to the Ramp data, snarking about “extrapolating from a lemonade stand,” was exactly the wrong move.
Ramp touches somewhere between 0.5% and 1% of US GDP in transactions. Their data scientists are good. And their customer base skews toward the digital companies that are making these decisions first. The data is real.
What’s driving it isn’t one thing. Claude Sonnet and Opus 4 through 4.7 have been a genuine step function since December — if you’re deep in vibe coding or building AI agents, you felt it immediately. More importantly, once a company has spent weeks dialing in an AI workflow on Claude — QA’d the outputs, built the scaffolding, trained it on their context — they are not switching. The soft costs of switching are enormous even when the hard costs (token pricing) look attractive. Anthropic has been consistent about what it is and what it’s building. OpenAI has been lurching: keep headcount flat, no double headcount; go deep on agentic commerce, Walmart says it doesn’t work; launch hardware, hardware gets deprioritized. That inconsistency has a smell to it now.
OpenAI still owns the consumer market. ChatGPT has the muscle memory. That’s real and shouldn’t be dismissed. But the enterprise coding market — which is the motherload app for enterprise AI spend — is locking in right now. If they let Claude be the default for another six to twelve months, they’ve sacrificed value they won’t get back.
The Real Figma Problem Isn’t Google Stitch
Stitch is a proof of concept from a company that abandons most of what it launches. The odds Google decides to compete with Figma for a decade approach zero. The market overreacted. That’s the first-order read.
But the market isn’t wrong. It’s just reacting to the right thing for the wrong stated reason. The actual worry isn’t Stitch. It’s that Figma Make — Figma’s own AI product — is among the worst vibe coding tools available. It can’t pull context from a live website. Every other tool in the space, including Replit, Lovable, and yes, Stitch, can do this now. A company doing $35% growth, with an enormous installed base and a smart CEO in Dylan Field, somehow has an AI product it isn’t even charging for because it isn’t good enough to charge for.
That is the diagnosis. And the installed base is part of the cause. At scale, the existing customer base becomes a resource trap. It demands constant attention — 50 years of features, offline integrations, non-agentic gaps. If you’re not deliberate about ring-fencing resources for the new thing, the old thing consumes 98% of what you have. Intercom had to consciously let its core business enter partial decline to build Fin. That’s a hard decision for a private company. For a public company headed toward IPO, it’s almost impossible without enormous conviction at the board level.
The market’s test is simple and harsh: are you charging for your AI product? If no, you’re not an AI company yet. And right now, almost no public SaaS company is passing that test.
What It Takes to Actually Pass the AI Monetization Test
There are two signals worth tracking. For SMB products: is ARPU 50% higher than pre-AI? Notion appears to have done this — their AI tier is $20/month versus a $10 base, and they’ve reportedly doubled ARPU. That passes. For enterprise: is revenue reaccelerating? Something has to be moving — new product attach rate, ACV expansion, net revenue retention. If nothing is moving, AI is a feature, not a business.
Token costs are a red herring for most applications. Yes, there’s an open router world where cost-sensitive builders are switching between Kimi, Haiku, and Mini to optimize spend. That market exists and is real. But there are many applications — AI agents doing sponsor management, marketing ops, customer success — where token spend is $2,000 a month and the delivered value is 100x that. For those applications, the idea of saving $500 a month by switching models isn’t a business decision, it’s noise. The companies building in this zone are not going to churn off their tuned, dialed-in Claude setup for a marginal cost reduction.
Jeff Bezos Wants $100B to Do What Amazon Did to Retail, But for All of Manufacturing
The clearest way to understand this: when Amazon was starting, there were three ways to bet on the internet transforming retail. Build software and sell it to retailers (Shopify, $200B outcome). Buy an existing retailer and AI-transform it (Walmart, roughly a 2x on a lot of capital). Or build the full-stack retailer from scratch and kill everyone (Amazon, $2T from zero).
Bezos did the third. Now he’s 60, he has more money than time, and he doesn’t want to build from scratch again. The Bezos $100B fund is the Walmart play for AI and manufacturing: buy existing companies across semiconductors, space, and defense, inject AI, and capture the transformation upside without the 25-year grind. It’s less IRR but faster and more comfortable from Indian Creek Island. It’s what you do when you’ve already proven you can do the hardest version.
Will he raise $100 billion? He can sell Amazon stock if he needs to. The more interesting question is whether this is the right frame for the AI era — and the honest answer is it’s inherently less disruptive than either the Shopify play or the Amazon play. It’s financial engineering plus operational improvement. Meaningful, but not the biggest bet.
SpaceX at $2 Trillion: How You Build the Math
The TerraFab announcement — effectively building a chip fab at 70% of TSMC’s capacity for roughly $25B CapEx, primarily to serve SpaceX’s data center and Tesla needs — is the latest step function in a pattern. SpaceX’s operating model isn’t linear growth. It’s big, chunky technical milestones every five to seven years, each of which unlocks a new layer of TAM. Government launch contracts. Starlink internet. Remote cellular. Data centers in space. Now: chip manufacturing to support all of it.
Starlink’s profit margins are reportedly exceptional. If you believe that’s the baseline and TerraFab extends that flywheel by two orders of magnitude, a DCF case for $2T can be built on a spreadsheet. Polymarket put the probability of that valuation at IPO at 50-60%. Tesla stock didn’t move on the announcement, which is meaningful — it suggests the market sees this as SpaceX value, not shared value.
The reasonable pushback isn’t “Elon can’t do it.” His record on hard engineering problems is unmatched. The pushback is timing. His track record on when things happen is spottier than his track record on whether they happen. That’s a cost-of-capital question more than a binary question.
The Grok/NVIDIA Deal: $20B for Sub-$100M Revenue, and Why the Structure Is a 60% Tax
When does someone pay $20B for a company doing under $100M in revenue? When the strategic value to the acquirer justifies it. NVIDIA has a $5T market cap and just announced Grok is going into production. The value isn’t the current revenue — it’s what NVIDIA can do with the technology through their distribution. WhatsApp had no revenue when Facebook paid $16B. Same logic.
The structure, though, is brutal. To avoid antitrust review, NVIDIA bought the assets rather than the company. That means Grok pays corporate tax on the gain (assets were on books at under $1B, sold for $20B), then distributes the remaining cash to investors who pay again on their gain. Effective tax rate to the founder: approximately 60%. You don’t get to roll into NVIDIA stock. The deal was probably 3x the last round — a classic M&A multiple — but the double-taxation structure wasted somewhere north of $4-5B in value.
The perverse incentive this creates for antitrust policy is worth noting. Companies now face two options: lobby extensively at the highest levels of the administration for a review waiver (pay up front), or use the asset purchase structure (pay up back). The government wins either way.
The Exit Math Nobody Wants to Run Out Loud
The most uncomfortable question in venture right now: what is the ratio of potential acquirers to unicorns? That ratio is at its lowest point in memory.
Private equity is out — can’t underwrite these multiples. The hyperscalers aren’t buying a hundred companies. Microsoft and Google are building their own. The old-generation software companies can’t afford to buy the AI-native companies that are replacing them — if Harvey is worth $10B and the incumbent legal practice software is worth $2B, there’s no acquisition. And the structure of the AI opportunity makes this worse: because AI expands TAMs, the new company gets marked to a bigger outcome, which prices out the acquirer class that would logically want it.
That leaves IPO. IPO markets are barely functional, not closed, but barely. The result: it’s easier right now to get a $9B valuation than to achieve a $1B exit. That gap should terrify anyone writing checks at late stage. Billion-dollar-plus rounds are being done at a pace that has outstripped any realistic exit path for most of these companies.
The strategy that has worked — do the round, get the markup, do the next round — has worked precisely because it’s predicated on IPOs eventually clearing. But the ratio of potential acquirers to unicorns has never been this low. It’s win or die. The M&A escape valve, which existed even in the 2021 bubble, is essentially closed.
Quotable Moments
Jason Lemkin
“There is no way we’re going to switch the model. This is dialed in. It works. These apps, which we rely on every day — there’s no way we’re going to switch them to Codex. It took us weeks to dial it in. Now that they’re great, I will not invest the time. That is lock-in. I would have a code red on this.”
“If you’re a software product and you don’t think AI is going to disrupt not just how you build but what you build, then you actually probably want to actively short it.”
“You’re not an AI company if you can’t charge for it. Very few public companies can effectively monetize AI. And that’s why they’re almost all in terminal decline right now.”
Harry Stebbings
“I just worry there’s some ratio of potential acquirers divided by unicorns, and I think we’re at the lowest ratio of our careers.”
“It’s so much easier to get a $9 billion valuation than a $1 billion exit. That should be terrifying if you’re the person giving the $9 billion valuation.”
“My biggest regret is not being more elastic, disregarding the Series A mandate and saying — I’m going to leverage the brand and access I have to get into the super hot companies much earlier and be a momentum investor in a hot environment.”
Rory O’Driscoll
“OpenAI grabbed the consumer mindshare with ChatGPT and nobody has taken that away at scale. But enterprise coding is the motherload app — and if you let Claude run away with that for another 6 to 12 months, you’ve probably sacrificed value you’ll never get back.”
“When the TAM becomes bigger, the new company gets marked to that bigger outcome. What it means is once it gets marked via a late-stage round, it precludes the prior generation buying in. It’s structural. It’s basically win or die.”
“Things are never as good or as bad as they seem. It was never as good as people thought a year ago. OpenAI still owns the consumer business. Job one is figuring out how to monetize that. You still have a comfortable chance to be the winner — if you focus.”
