Cognition vs Factory | Anthropic Under Threat | ElevenLabs Doubles Its Valuation to $22B
Harry StebbingsDev IttycheriaJason LemkinRory O’Driscoll
OpenAI’s reported Q3 reacceleration turns the frontier-model race from an Anthropic runaway into a fresh test of market expansion versus share rotation. Rory O’Driscoll contrasts roughly 70% quarter-on-quarter growth with just 18% from Q1 to Q2, while Dev Ittycheria says widespread switching driven by quality and price shows OpenAI is “back.” The “next shoe to drop” is Anthropic’s Q3 number: continued hypergrowth would validate a vast TAM, while a sharp slowdown would suggest OpenAI took share.
The Factory–Cognition dispute exposes a widening gap between legal freedom and reputational obligation in AI talent markets. Jason argues that “the definition of loyalty has changed” as executives and teams move faster, while Dev Ittycheria says access to confidential plans and a jump to a direct competitor can damage an executive’s standing long term. Vinod Khosla’s public description of Factory as a “struggling second-tier competitor” compounded the issue by handing rival venture firms “a weapon” against Khosla Ventures.
Reflection’s Beam could fill a strategically valuable gap: a US open-weight model near frontier quality at three to four times lower cost. Dev sees an enterprise proposition that lets customers “have their cake and eat it too,” particularly where Chinese models face regulatory or trust resistance. Jason thinks US models might capture half of open-source token flow within 12 months if they remain only three months behind frontier quality, though he cautions that published evals now require “three asterisks and four daggers.”
ElevenLabs at a $22 billion valuation earned Jason’s strongest investment call because voice quality remains less fungible than general reasoning. He would put up to 10% of the hypothetical fund into the company, citing widening product leadership, strong margins, large contracts and voice’s role as a critical agent interface. A flower-shop agent cannot merely be cheap: “It has to answer that phone in seconds, and it has to be the right flowers.”
Salesforce’s $2 billion purchase of Listen Labs validates AI-native market research, but not necessarily every standalone AI application. Rory sees a top-tier use case because LLMs can conduct adaptive voice interviews rather than march through canned surveys; Jason questions how roughly $20 million of revenue moves the needle at a company approaching $50–60 billion. Dev’s durability test is whether the startup has a proprietary data loop or is merely “a feature masquerading as a company.”
Agents are becoming a distribution channel with their own vendor preferences, making machine discoverability as important as human search rankings. Vercel reportedly gets 50% of new business from agents, up from 3% at the start of the year, while Resend’s MCP calls rose from 106,000 in April to 3.3 million in September. “When agents pick you, it’s a force of nature,” Jason says; the resulting opportunity for Profound, Peak and peers is to help companies shape the content and infrastructure that earn those recommendations.
The Groq–NVIDIA lawsuit could put license-and-hire transactions under legal and economic pressure if courts treat them as acquisitions in substance. Former engineers allege that technology and roughly 200 employees moved while some common shareholders retained equity in a hollowed-out company, challenging the principle that holders of the same security receive equal treatment. Jason’s formulation: “Just ’cause you say it’s not a duck, it don’t mean it’s not a duck.”
Aura’s pulled IPO is a warning that even rapid growth may not overcome pricing, secondary-sale optics and banker overpromising. Dev’s speculative but simple explanation is that demand did not support the promised valuation; Rory argues the board should perhaps have “hit the bid” once it had gone that far. With Anthropic’s IPO expected in mid-November, the broader lesson is that liquidity windows can deteriorate before an issuer finishes debating the perfect price.
1. OpenAI’s Q3 surge resets the frontier-model race
Dev’s framing is a comeback compressed into months: at the start of the year, many B2B and coding workloads appeared to work only on Anthropic; by the time of the discussion, OpenAI had products customers were adopting because they were “better and cheaper.” At approximately $70 billion of run-rate revenue, that speed of recovery is itself the signal.
Rory anchors the reversal in growth rates. OpenAI reportedly moved from 18% quarter-on-quarter growth between Q1 and Q2—which implied just under 100% year-on-year growth—to roughly 70% in Q3. At the prior checkpoint, the comparison was about $11 billion versus $6.8 billion, with Anthropic growing 10x against OpenAI’s roughly 2x.
The decisive question is whether OpenAI’s acceleration came at Anthropic’s expense. If Anthropic also posts strong Q3 growth, the result supports an enormous expanding TAM; if it falls from 10x toward 5x or lower, this begins to look like a rotating-share market. “OpenAI, you played your 70% card,” Rory says; now Anthropic must reveal its own.
OpenAI needed the acceleration because it has committed forward spending across compute, data centers and even land in Virginia. Rory calls the reported result “a big freaking sigh of relief”: without hyperscale revenue growth, many of those obligations could come unstuck.
2. Enterprise friction creates stickiness, but price and liquidity still rule
Dev separates developer behavior from enterprise adoption. Developers readily chase the “shiny new toy” or use several models at once; enterprises sign contracts, clear procurement, train thousands of employees and embed workflows. That makes replacement materially harder even when a superior model appears.
MongoDB’s internal conversations surface two enterprise constraints beyond benchmark performance: token budgets and IP rights. No organization has unlimited inference spend, while buyers must ask how models were trained, who receives their data and how proprietary information remains.
Against OpenAI’s proposed $30 billion raise at a $1.4 trillion valuation, Rory prefers liquidity at the margin. With the information set changing this quickly, he would rather own a public security than accept a private holding period that could stretch three or four years, regardless of an expected 2027 IPO.
Anthropic’s timing raises the stakes: the panel expects its Q3 figure to appear in the prospectus and be known before a possible mid-November listing. The growth disclosure—not merely the headline valuation—could decide whether investors see two compounding leaders or one taking share from the other.
3. Factory–Cognition turns implied loyalty into an investable risk
Harry lays out the allegation carefully: former Snowflake sales leader Chris Degnan was a Factory board observer, spoke to founder Matan daily and was close to him, according to Matan, while reportedly interviewing for Cognition’s CRO role. Dev’s conditional judgment depends on whether Degnan had access to confidential product, financial, board and competitive plans.
Jason’s counter is that perhaps 95% of CROs would view accepting a career-defining job as normal, particularly because Degnan was not a full-time employee or director. Rory adds that even full-time executives can join competitors carrying current knowledge; the adviser problem arose because expectations appear to have remained implicit rather than made concrete.
Dev rejects the idea that AI erases reputation. A leader has recruited people on a company, vision and financial opportunity; leaving for a direct competitor can make those employees wonder whether they were sold “a bill of goods.” Jason sees the old “rule of two” recruits disappearing as respected leaders now take eight or ten colleagues immediately, but Dev says human management remains much as it was in 1998.
Khosla’s intervention drew the clearest consensus. After leading Factory’s Series C and most recent round, Vinod Khosla publicly called it a “struggling second-tier competitor”; Dev says that gave every rival firm a deal-winning question: “Is this the partner you want when things go bad?” Rory’s verdict on competitive portfolio companies: investors must “love your children equally,” praise publicly and chastise privately.
4. Reflection’s opening is sovereignty plus good-enough economics
Dev’s case for Reflection’s Beam is specific: a US open-weight model near frontier intelligence, priced three to four times more cost-effectively, offers enterprises sovereignty, lower cost and less discomfort than Chinese models in regulated or data-sensitive industries. Jason’s Dreamforce conversations reinforce the demand signal: buyers using Chinese models often felt they were doing so “under duress for cost.”
Frontier parity is unnecessary for most workloads. If a model is within six months of the frontier yet covers 90% of coding, reasoning and agentic use cases, Dev sees little reason enterprises would not engage. The hard frontier model can remain reserved for “the hard stuff” while cheaper systems absorb routine volume.
Rory’s economic trigger is the absolute bill: if OpenAI and Anthropic each reach $70 billion of ARR, their combined $140 billion exceeds what Microsoft historically made across Windows and Office. At that scale, CFOs will order CIOs to shave millions from token spending, forcing routing across model tiers and open weights.
Jason could imagine US models taking 50% of open-source token flow within a year if they reach “X minus three months.” Rory says even 10–20% would be consequential because foundation models on OpenRadio receive perhaps 20–30% of the tokens but 90% of the dollars; enterprise-oriented US adoption would also de-risk inference platforms.
5. Falling token costs expand usage, while evals lose credibility
Dev does not see open weights and frontier labs as a zero-sum contest. Enterprise capability currently exceeds actual deployment because organizations lack experienced practitioners; as costs decline and teams gain fluency, Jevons paradox should bring more use cases, more consumption and room for multiple winners.
Demand is already outrunning current deployment capacity. Jason says every Dreamforce executive he met was overwhelmed by internal requests for tokens, with latent demand perhaps an order of magnitude above what companies have surfaced. Some spending will be wasteful or routed to suboptimal models, but the volume creates a substantial opening.
Safety will join cost and sovereignty as a procurement variable, though Dev concedes that defining it is difficult and “beauty is in the eye of the beholder.” Enterprises need some benchmark-like mechanism for trust, even if—as with performance tests—it can be gamed.
Jason’s warning is that Beam’s published results are not enough: “Every single eval needs like three asterisks and four daggers.” Speed, actual outputs and performance inside a mission-critical workflow matter more than narrowly optimized tests or “chess championships.”
6. ElevenLabs wins the rare 10%-of-the-fund recommendation
At a $22 billion valuation, Jason would allocate up to 10% of the hypothetical fund immediately rather than wait for another round. His case combines widening leadership despite intense competition, impressive margins and growth, “sub-millisecond response rates,” and voice becoming one of the ten most important underpinnings of agentic applications.
He has not abandoned his forecast that cheaper voice models will substitute for premium ones. His distinction is that ElevenLabs spans low- and high-end models while serving workflows where quality failure destroys the product: a phone agent that misunderstands an order or invents inventory has no value.
Reference calls showed even relatively modest companies happily spending hundreds of thousands of dollars annually. Jason therefore rejects blanket model fungibility: reasoning can be slightly weaker in a non-critical task, but real-time voice must work. “I don’t think anybody’s gonna catch them here today.”
7. Listen Labs makes market research an obvious AI-native category
Harry cites a $2 billion Salesforce acquisition, about $850 million returned on $96 million invested, a roughly 25x result for Sequoia across the seed and Series A, and a 4x return for Ribbit’s Series B in eight months. The speed and magnitude make timing as important as company-building duration.
Rory sees market research as a large, fragmented, pre-technical spend pool previously represented by consulting firms and companies such as Qualtrics, Medallia and SurveyMonkey. Voice is now a viable model interface, while LLMs can synthesize responses and alter subsequent questions dynamically.
His best contrast is the old survey that asks whether the bed was comfortable after a respondent says they never checked in. Listen Labs could replace that canned sequence with a conversational interview, making the application one of Rory’s “top five, top 10” AI use cases.
Jason understands the category but questions the buyer logic: roughly $20 million of revenue may not move Salesforce, which is approaching $50 billion and targets $60 billion. Dev expects more such purchases because distribution-rich platforms can absorb clever applications that are still features rather than independent franchises.
8. A $2 billion early exit is rational unless the company is generational
Dev’s durability test separates a copied feature from a franchise: users must create proprietary data, that data must improve the product, and the improved product must attract more usage. Competitors can copy functionality, but not the accumulated interactions powering that loop.
Harry contrasts Listen Labs’ three-year path with Intercom’s roughly 15 years of building. Rory refuses the envy frame—“life ain’t fair, and venture outcomes are very random”—and notes that timing could let 10% of today’s AI apps sell at 30x revenue while others grind toward six-times revenue with thousands of employees.
Jason would usually take $2 billion within five years unless the founders sincerely believe they are building “a Mongo or better.” Companies without a generational ambition have a terminal value, and a credible early offer can dominate the net present value of years more execution.
Dev’s BladeLogic history shows the choice recurring at every stage: Cisco’s John Chambers and EMC explored purchases before BMC ultimately paid about $900 million, roughly 9x the company’s $100 million of revenue, in 2008. He felt good continuing earlier and equally good selling when the eventual moment arrived.
9. Agents are becoming the buyers that determine infrastructure winners
Vercel reportedly reached $600 million in ARR while agents rose from 3% to 50% of new business. Jason recalls roughly 170% growth alongside something like a 20% increase in customers, implying extraordinary expansion as autonomous systems spin up applications and consume infrastructure.
The advantage was not designed in hindsight: Vercel predates the agent wave, just as Replit dates to 2016. Both had the right substrate when demand shifted. “When agents pick you, it’s a force of nature,” Jason says, because their preferred stack is surprisingly difficult for human operators to override.
Resend is his concrete example. After SendGrid setup repeatedly failed, Jason asked an agent what to use and received Resend; separately, Resend’s MCP calls rose from 106,000 in April to 3.3 million in September. That is not conventional lead generation—it is software directly recommending and activating another product.
An agent’s choice is also more contextual than a generic ChatGPT answer. It knows the application, infrastructure and dependencies, then selects for that stack; Jason’s own agent recommended Render over Railway, Fly.io and Vercel for one project, creating a qualified lead without the buyer previously knowing Render.
10. Machine visibility could become a deeper market than SEO analytics
Dev recasts 25 years of search optimization: companies once fought to appear on Google’s first page; now they must ensure agents can find them, understand their product and access current, accurate information. “If you’re missing from an AI-generated answer, it’s like being invisible on Google.”
Startups face an asymmetric corpus problem. Incumbents have 10–15 years of documentation and information, while challengers may be nearly absent from model context. To become a first-class agent choice, a startup must expose excellent documentation, APIs, integrations and infrastructure.
Profound and Peak can become more than monitoring dashboards if they close the loop: diagnose where a vendor is absent, then shape and create the content that fixes the absence. Rory compares the expansion path to HubSpot, which began with an immediate SEO pain point and layered adjacent marketing problems into a platform.
Jason proposes a simple field test before the full product exists: ask ten trusted teams with production agents, every two weeks, what those agents recommend in a category. The emerging market is not merely tracking generic LLM responses; it is observing stack-aware decisions made by live agents doing real work.
11. The Groq case challenges license-and-hire deals at their foundation
Harry introduces a $17 billion Groq–NVIDIA license-and-hire dispute; the complaint, as described, alleges an $11 billion license plus roughly $3 billion in stock, with core technology and around 200 employees transferred while common holders retained a hollowed-out company. Two former engineers brought the Delaware action.
Rory’s legal intuition begins with equal treatment: common shareholders own the same security, and directors owe duties to all of them. A buyer cannot ordinarily allocate rich consideration to employees it wants while ignoring former employees holding identical shares. That makes the plaintiffs’ “clever little case” potentially settlement-worthy.
Dev expects employees to begin asking a question investors already negotiate: what happens to my equity if the technology and selected staff are bought but the corporate shell is not? Rory warns that once established common-law protections erode, every employee must price increasingly elaborate transaction scenarios before joining.
The structure exists because a conventional acquisition might face nine months of regulatory review while a license-and-hire can close on Sunday and move employees on Monday. Jason thinks meaningful legal liability, added to double taxation, could end the practice: “Just ’cause you say it’s not a duck, it don’t mean it’s not a duck.”
12. Shipping separates Muse from Dots, while Aura tests the IPO window
Harry praises Muse’s launch and calls Dots’ enterprise-travel demo tech-centric and underwhelming. Rory, previously skeptical of Meta’s execution, credits the team for resourcing Muse with compute and shipping a state-of-the-art product: “They put their heads down and shipped product,” which “cures everything.”
Jason asks for a developer rather than consumer verdict on Dots. Its initial value may be integration with Codex as a persistent 24-hour coding agent. He notes that Replit and Lovable could stay on in the early days, while Claude Code and Codex are hard to keep running 24 hours; he says that limitation helped OpenClaude take off. He would allow 30–90 days before judging it by a weak travel-booking presentation.
Aura supplies the capital-markets counterpoint. Jason is troubled that a company described as doing $1.2 billion, growing 74% with an attractive recurring-revenue portion, pulled its IPO; Dev, explicitly speculating, thinks pricing failed, while Forerunner’s full exit hurt optics. Rory’s prescription is blunt: distrust banker optimism, “hit the bid,” and remember how much can change before Anthropic’s expected mid-November offering.
Full transcript
It will be super interesting to see where that Anthropic Q3 number comes out. I've never seen a CRO flip from one competitor to another.
But I think in the AI age, the definition of loyalty has changed.
I think the reputational damage that you can do long term is going to come back and bite you. You've basically handed every other firm a weapon when they're competing on deals, saying, “Is this the partner you want when things go bad?”
When agents pick you, it's a force of nature right now.
There's a lot that's got to happen between now and the Anthropic IPO in the middle of November.
Boys, it's so good to be back, and we have a phenomenal guest joining us today. Dev, thank you so much for joining us, dude.
Thank you, Harry. Thanks for inviting me and being part of this amazing group.
Do you know what? I don't know if you guys know, but Dev gave me feedback that we needed to move on faster from just OpenAI and Anthropic.
I love it.
And we really took it to heart. Taking it to heart, I thought we'd start on OpenAI.
Well done.
Good start.
1. OpenAI Reenters The Race
OpenAI nears a $70 billion run rate and goes for $30 billion at a $1.4 trillion valuation, but the IPO is going to wait until 2027, despite Anthropic going out in the next few weeks, it would seem. What do we think, boys?
The crazy thing to me when I think about the story is that OpenAI is back, right? $70 billion in revenue, but more importantly, if you look at your portfolio companies and others, Astro, Sol, and Luna are everywhere, right? Everyone's using them. Everyone is using them.
When we started this year, a lot of things in B2B only worked at the end of last year, and only Anthropic could get this stuff to work. Even coding at the start of this year only worked on Anthropic. Then we went into the summer, and it seemed like OpenAI was on the ropes because consumer was the wrong path, and they couldn't get back.
I mean, the rate of change here and the rate at which the OpenAI team got back in the game and made something that is truly epically competitive—to the point where people are switching out their models for real because it's better and cheaper—is crazy. That pace at that scale, and it's $70 billion, says it all, right?
You counted them out 3 or 4 months ago—not literally, but figuratively—and now, if they launch a truly competitive set of models, it's instantly massively competitive. It's crazy. Massive kudos, I think.
What happens if Anthropic's numbers for Q3 aren't blowout? Every team that I speak to has diverted some meaningful portion from Anthropic to Codex, and everyone says how amazing it is. What happens if they're not blowout numbers, like the world really just assumes Anthropic always has now?
The interesting thing that we should also learn from this—and having sold to developers for the last 12-plus years—is that there's not a lot of loyalty. Developers are very quick to switch from one tool to another or, frankly, use multiple tools. I think what we're seeing is that developers are quick to find the shiny new toy.
The question is, what will Claude or Anthropic come out with next, and what are the other alternatives? The other thing that's interesting is that what OpenAI has done has shown that when you have essentially 1 billion people using ChatGPT a week, that's a great distribution channel. Potentially, where the moat is, is the enterprise business.
You have to sign contracts, train thousands of employees, and build workflows, and it may be harder to switch providers again in the enterprise. That's a little bit of the reaction I had.
Yeah, I guess in that sense, OpenAI's run rate is even more impressive, right? Maybe they're already embedded, maybe they're already through procurement, but that's pretty fast change in the enterprise, too.
Yes.
Can I ask you a follow-up question? From your seat, do you think that is a blocker for more progress in open-weight models in the enterprise—the ability to get through procurement and get approved—or do you not? Obviously, the explosion this year is crazy, but it is a hurdle to get over. What are you seeing from the Mongo and Sequoia side?
Well, actually, from Mongo's side, I was just talking to our CIO, and we were talking about token costs and token budgets. Cost is a big factor, and I think every enterprise has to consider that. No one has unlimited budgets.
The second thing is IP rights: how we train these models, who gets the data, and how proprietary the data is. I think those 2 things are also pretty important points when it comes to what models you choose and who you work with.
As you often do, Harry, you put a lot out there, and I think you—forget the valuation stuff, which we haven't even discussed yet. Just the raw number: the 70% quarter-on-quarter for OpenAI in Q3.
I tweeted at the end of Q2, when the OpenAI numbers came out for Q1 and Q2, and the gap in revenue growth from Q1 to Q2 was 18% quarter on quarter. You did that math, and it implied just under 100% year-on-year growth, which was a massive deceleration at a time when Anthropic was still growing 10X.
At the end of Q2, that was the state of the race. I don't like to make this a horse race, because you need to zoom out, but part of it is a horse race. If you noticed really early on in Q3, all the OpenAI team started tweeting, “We're having a killer July.”
Do you remember Sarah Friar commenting on that? “We're having a killer August.” It was clear that they had internalized that Q2 was the first time Anthropic's gap in revenue was larger than theirs, and it just felt like they were pulling away.
$11 billion versus $6.8 billion, growing 10X versus growing 2X. Suddenly, a 70% number—no matter what, we'll talk about Anthropic in a second, but no matter what Anthropic does—at least changes that narrative back.
If it really is correct—and we don't know, but if gap revenue grows 70% quarter on quarter, or even 60%, up from 18% from Q1 to Q2, that's a massive reacceleration. Starting with a huge win, there's a big freaking sigh of relief because, given OpenAI's forward purchases of just about everything from compute to data centers to land in Virginia, if they didn't grow at hyperspeed, a lot of things come unstuck.
So that's the first thing: if true, it's amazing for OpenAI. And then you're right, the second thing is: did that come at the expense of Anthropic? In other words, you're asking the question, is this a rotating-share game? They accelerated 70% and then Anthropic slowed down markedly, or did they both grow pretty well, in which case you can lean into the TAM?
And you're right: if the OpenAI growth rate was the key missing card—the missing data point—now that you've allegedly seen that card, and again, we're assuming the 70% is correct, you're exactly right. The next shoe to drop is, "Okay, OpenAI, you played your 70% card. Now we're going to play our still-10X-growth card." Or is it going to be 5X growth, or is it going to be, "Hey, we've slowed down a lot"?
It will be super interesting to see where that Anthropic Q3 number comes out. And I won't say it's no accident, but it's worth noting that the timing of the IPO is now such that that number will be in the prospectus, but it will be known at the time they go public.
If we disentangle the revenue from the price and the round, then Rory, as you quite rightly illustrated—I should have done this, poor Harry—$1.4 trillion, the largest private round, $30 billion more. I thought we'd dried up all private capital. Clearly, there's more. How do we think about this, Rory?
This would be the first-ever venture round above $1 trillion. That's pleasing. The first-ever private trillion-dollar-plus round. I remember in the mid-'90s, the first round above $1 billion, and we were like, "Whoa, that's kind of crazy." Moving right along with 3 orders of magnitude.
Rory, congratulations for becoming the new head of CalPERS pension fund. You are now in charge of directs, and you have the chance to do OpenAI at $1.4 trillion or Anthropic as they go public at $2 trillion. What would you like to do?
I think you lean to liquidity. It's a lot better to have liquidity than not have liquidity. You separately have to value the 2 companies, which is worth more, but separate from that, you really ask the question: liquidity versus illiquidity.
I would much prefer to be in the liquid stock when the amount of information is as unknown as it is. You either want the liquid stock, or you accept that you're holding for 3 or 4 years, because that's the risk of being private. You think it can go public next year, and it should be. It's damn it, big enough, but you never know with the world. So I probably would lean to liquidity at the margin. Sorry, boring answer.
2. Factory Faces A Talent Fight
We can go to Anthropic's IPO, or we can go to the slightly salacious one, which is Factory and Cognition. I think we should go there. I'm going to throw my hat in the ring.
I'm going to provide some context. Chris Degnan, a sales leader legendary from Snowflake for many years, was a board observer at Factory, spoke to Matan every day according to the founder, and was very close to him. And while he was very close to him, he was interviewing for a role at Cognition, according to the founder, Matan. He then took the role at Cognition as CRO.
That is when Matan came out and said, "You're barred. This is wrong," and, "How bad of you." Let's start on that before we discuss Vinod.
How did we analyze this?
I just want to be clear. I know Matan personally. I'm an angel investor. Sequoia is an investor in Factory as well, and MongoDB is a partner with Cognition.
But the fact that an advisor has access to a founder's confidential plans means there should be clarity with the founder that they're thinking about going in a different direction, especially if that's a potentially competitive situation. If I were the CEO, I'd be pretty annoyed to see someone who had access to my plans go to a competitor. Again, I don't know if that had happened. That would be quite upsetting to me if it did.
On the other side, as a CEO, it's going to be profoundly frustrating, right? Your advisor goes off and joins a competitor. It's happened to us all at some level.
I would think 95% of the CROs we would talk to would say, "This is fine, man. This is the way it works." CRO is a risky job. There's a lot of turnover. Jobs come in fast, and a lot of CROs, if it's a hot job, move very quickly.
I just think that a lot of CEOs would be frustrated. I think 95% of CROs would say, "This is how I found my last job."
Jason, I'm going to respectfully disagree, because remember that CROs also hire other people to work for them, selling them on the company, selling them on the vision, selling them on how they're going to make money and how it's going to be transformative for their family.
If that person were to leave, they've basically burned their reputation with everyone they recruited as well. So I've never seen a CRO flip from one competitor to another. I've seen a CRO go from one company to another company in a different space because they think that's a better opportunity, but I've never seen a CRO, at least that I can remember, flip from one company to a direct competitor of another.
No, I just don't think most CROs, if they were just an advisor—not a full-time employee—would see it that way. He's an advisor. He's not even on the board; he's a board observer. What he did—and that's important, right—but there is a distinction between a board observer for a little while and a board member.
A CRO, not a CTO, not a founder, not a CEO, gets somewhat retired, as far as I understand it. He made a lot of money at Snowflake, and that's fine. There's nothing wrong with retiring for many. He gets what seems to be the greatest job offer. It's going to happen.
Then he says to the other CEO, "I got this offer. I'm going to take it." It would be nice if there were a little more temporal separation, but I just think most CROs who find the job of a lifetime and are just an advisor to another company wouldn't even see a conflict.
The way we think about conflicts as founders, I think a lot of CROs think of it as a game. Competitors are often really friends with each other, CROs. They see it all as, "My job's to beat Mongo. My job at Mongo is to beat whomever," right?
Anyway, I just thought the founder's reaction was shocking, but I don't know if the CRO, as an advisor, sees this as crossing some sort of line.
Again, not knowing all the facts, what I will tell you is that different advisors have different roles. You can call an advisor for a particular part of the business or a particular function and say, "Hey, I want your advice. I'm looking to hire someone in Europe. Can you vet this person or give me some ideas of who I should talk to?"
That's very different from someone who's inside the tent, looking at your product plans, your board plans, your financial plans, and having real visibility in terms of where you're taking the business.
I think if it's the former, then yes, there's no issue. This person was talking to you, it was kind of a light relationship, and they decided to move on to a competitor. Okay, it happens. You're not thrilled about it, but it happens.
But if someone had real insight into the business, real insight into what the product roadmap was like, real insight into how they were competing and winning and losing against their competition, and then they suddenly jumped to a competitor, that would be very, very different to me.
The interesting thing is, if you think about the employee relationship first and then the advisor relationship, at the employee level, if I have a CRO working for me, at any point in time it's entirely possible that they can get a compelling offer from a direct competitor and go over there, literally knowing everything about what I was doing up until the minute they gave their notice.
Dev, you might think, "That sucks. That was a pretty shitty thing to do," because you were all in for Team A, and now you didn't go to another sport. You went to Team B in the same damn league. It's pretty shitty, but it happens.
The Factory CEO voiced anger, but it's worth pointing out that if I were a full-time employee, there's no way for me to tell CEO A, "Hey, I'm thinking of leaving," until I got the job, and then I have to give my notice. There's no halfway measure.
To some extent, this is going to happen. If you have employees, they're going to know a lot about what you're doing, and at any point in time they can go and do the same thing for a competitor. At that point in time, it's going to suck. Right up until the minute before they sign that offer from your competitor, they know all your plans.
In other words, shit like this can happen. And if—
Or you could communicate in advance. You could say, "Matan, I've been approached by Scott, and I would like to actually pursue it. I wanted to let you know and be upfront about that because I'm aware I have a position of sensitivity."
But, okay, first of all, I'm dividing a full-time employee from an advisor, and then we'll talk about the advisor, because I think one thing that Dev has corrected—there was an implicit—
This is where you get explicit and implicit understanding. There was probably some implicit understanding about the advisor that wasn't fully fleshed out on either side, and that's where I think Dev is actually correct. But going back to the full-time employee, I don't think you can, Harry.
If your number two came in and said, “Hey, I got an offer from Excel. I'm thinking about it. I may go, I may not. If not, I still want you to love me as if I'd never thought about leaving, but I may go,” and I've done that. But it's generally in an operating role, and it can be difficult.
I'm with you, but that's not the case here, Rory. You're talking about a hypothetical.
I know. My point is merely that people are saying, “Hey, you had a part-time advisor who left and brought all this information.” My point is, you can lose a full-time direct-report employee who brings exactly the same information and even more. So it can happen. It happens quite a lot in business. It's not unusual.
The thing that's unfortunate here is that if the person is just doing part-time advising, you've ended up in an odd situation where you're disclosing everything. That person isn't on the board, so they have no fiduciary obligations and aren't employed by the company. They were probably, to Dev's point, under some implied understanding that said, “Hey, you shouldn't do this,” but it was never made concrete. Harry, you're shaking your head.
I think you're absolutely wrong. I think as an employee, you have very siloed information, and you don't have a lot of privileges that a board member would have with oversight of strategic discussions across the whole company and all the different functions. So it's completely different.
How would you feel if you were the CFO or COO?
If you're the CFO who moves on, you have no real insight into, maybe, the product roadmap and functionality.
But listen, Dev—I mean, how is it so different? Half of the Frontier Labs folks are rotating back and forth, right? They go in and out. They're taking tons of intellectual property and knowledge from each other.
Dev can challenge me here, and I wish this were not true, but I just think in the AI age, the definition of loyalty has changed. I think it's changed permanently. I think culturally it's changed. I see it with some of the top executives I've learned from. People move more quickly. The compensation's very different.
And I think you just have to expect people will move from competitors. They will go from OpenAI to Anthropic to wherever. We've changed culturally, and it can bother you, but the world changed. We've got to accept it.
Yeah, so what I would say is the following. It's very rare for me to see people go to a direct competitor. It has happened and, Jason, you're right: in this age, there seems to be more of that happening than not. But it's still quite rare.
And I think you also have to understand that these people have reputations, and if they're in a leadership position, they've recruited people who work for them, who believe in them and believe the story. Then, for them to get up and leave obviously leaves a bad taste in people's mouths in terms of how committed you really were to this and whether you sold me a bill of goods.
In a situation where a CRO or senior executive is leaving, the question I'd ask is, “Okay, I understand there are lots of opportunities out there, but do you have to go to a direct competitor? Is there no other company that wanted you? Is there no other company that values your skills as much as this company?” I think the reputational damage that you can do long term is going to come back and bite you.
Do we even remember next week anymore in the age of AI?
I think you do. Actually, Jason, I would say the more things change, in many ways, a lot stays the same around people, around relationships and how you work with them.
People too often use the AI era as if everything's changed. I disagree. I think how you manage people, how you recruit them, how you develop them and how you hold them accountable are all the same. In fact, a lot of these young AI founders struggle with this all the time because some of them have never hired a go-to-market person. They've never hired a finance person. So they're always asking for advice on what to look for and how to evaluate someone with skills very different from theirs.
They're all the same issues I had when I started my first company in 1998. It's the same thing all over again. It's just obviously happening maybe more visibly than it ever happened before.
Until recently, my experience was that whenever you went somewhere else, to another company, there was always the rule of two—kind of like the Sith, but different, right? Wasn't the Sith the Rule of Two? I don't know. You could take two people with you.
So when you left MongoDB to go do your own company, you could bring one, and Dev would get kind of pissed, and you'd talk about it. Then you'd ask permission for the second, and there'd be a lot of friction, but if you crossed two, the relationship was broken, right?
Now I'm seeing folks take 8 or 10 with them in the first week. It's not a cultural issue anymore, even among people I respect and think are highly ethical. Some of that, I think, is the pressure to move so quickly in the age of AI. But I do think it's related to this. I think it's a symptom of change that the rule of two seems to have died.
Was that your rule with your team over the years? Did you informally enforce the rule of two?
Yeah. I've had people who left and then carpet-bombed the rest of the organization to try and follow them. Obviously, that wasn't a great feeling, and stern words were exchanged.
Let me ask an interesting question, Dev. Would you prefer a senior executive to leave and go to a direct competitor but recruit no one, or someone to leave and go to a totally different business, broadly in your developer-tools space, but, say, recruit 4 or 5 of your top executives? Which would you prefer to defend: the talent or the knowledge?
It's a tough one. I think it depends on who that competitor was. If it was my mortal enemy, I'd be more upset about the former. If it was another company and 4 or 5 people left, it is what it is, and I'd move on.
3. Venture Loyalty Gets Tested
I would love to move the conversation along slightly because we mentioned the word loyalty. When we hear the word loyalty, I just think of Vinod Khosla, who led Factory's Series C, led their most recent round, and then went on Twitter. The wording was, “Struggling second-tier competitor.” Absolute demolition job of Matan. I don't know what to say.
Was he asleep in the partnership decision? Was he aware that he led the last round? I'm genuinely not saying that stupidly. I don't know if he was.
Candidly, I was shocked when I saw that. I was totally flummoxed by that tweet because it basically handed a weapon to every other firm competing with Khosla Ventures. Khosla's got a great team with Keith and a bunch of other people there, and it basically handed every other firm a weapon when they're competing on deals, saying, “Is this the partner you want when things go bad?”
I was totally flummoxed as to why he would do that publicly.
Yeah. Some days you just make a mistake. He will probably look back and say, “Gosh, I wish I hadn't done that.” It's a weapon in the hands of everyone who competes with them. I wish it hadn't happened.
A lot of what's going on here is the question of what are the legal obligations versus what are the implied rules, and what are the consequences of breaking the implied rules? One of the nonlegal but nonetheless implied rules is that it's really hard for venture firms when they do 2 directly competitive deals. The only way you get around it is to make this whole argument that you love your children equally. You don't say anything in public about one or the other.
Then you have something like this that crashes through every wall, and it just shows that those situations of 2 directly competitive investments are very fraught, especially if you're actively involved in the companies. It was very unhelpful for Khosla, very unhelpful for both companies. It's like, ick. It was not venture's finest hour. Let's move on. Enough.
Maybe, being the Pollyanna, he meant it positively as tough love. “Struggling second-tier competitor.” There's a theory: be harsh on the struggling, the most struggling founders. He thought “struggling second-tier competitor” would be motivating.
Harry, I yield, obviously, to Dev on the CEO-as-manager side here, but I do vaguely remember something about praise in public and chastise in private.
Yeah, it seems backwards.
I think that was the mission here. You know it.
You never know. It seems baffling.
4. Open Models Target Enterprise Budgets
We've been talking a lot about open models over the last few weeks. We saw Reflection AI ship Beam. I thought that was a really interesting story. We also discussed, Rory, one of yours before: Intercom obviously selling to Salesforce. We had Salesforce buying Listen Labs too for $2 billion. Of those 2, where would you rather go?
I think both are worth some time. I'd love to hear your thoughts on Reflection AI because, look, they've been, frankly, talking about shipping for a long time. From what we said earlier, it seems to me that being an open-weight, U.S.-sourced model is a super interesting strategic position right now.
So if someone can ship something that's near-frontier quality, even if it's 6 to 12 months off, just from the dynamics of the market, that's a nice place. What are your thoughts, Dev?
Yeah, I tweeted it out this morning. I thought enterprises can have their cake and eat it too. First, you get a US open-weight model that's near-frontier intelligence and 3 to 4 times more cost-effective, i.e., cheaper, and that's music to the ears of any enterprise because there's obviously going to be some hesitation about using Chinese open-source models, especially if you're in a regulated industry or an industry that deals with a lot of sensitive information.
To me, this was a very noteworthy announcement. Again, I do want to disclose that Sequoia is an investor in Reflection AI, but I think it's great for the enterprise.
I was at Dreamforce this year and got to have a surprisingly large number of conversations with executives. Notwithstanding the incredible force of nature of Chinese-based open-weight models, nobody I talked to really wanted to use a Chinese-sourced model. Right or wrong, fair or not, everybody who was using one felt like they were doing it under duress for cost, but no one really wanted to use one. Again, right or wrong. If they nail this, it could be a torrent of demand.
I agree, and I think this also reinforces the point that you don't need frontier-level intelligence for every workload. If it's close to the frontier, as Rory said, within 6 months of the latest models, and addresses 90% of your use cases—especially around reasoning use cases like coding and agentic workloads—I don't see why enterprises wouldn't want to talk to them immediately.
It ties back to the first topic. At one level, the evidence so far has been that there hasn't been a massive push because people are lazy, the bills haven't been astronomical, and therefore they've just used the frontier model and maybe downgraded to the less expensive Anthropic or OpenAI model levels.
But I agree. I think the interesting thing now is that the numbers are getting so huge. If OpenAI and Anthropic are each making $70 billion in ARR, that's $140 billion. That's more than Microsoft made for the longest time across both Windows and Office. That's a chunk of US corporate profits, right?
At that point, if you're a CFO, you probably come in to your CIO and say, "I don't care that it's easier to just use Anthropic. We need to shave $3 million off this token bill. Start using Jev for 20% of your decisions, start using Reflection or something for anything that's not frontier, and figure out a way to use Anthropic for the hard stuff."
I'd imagine, Dev, you guys will start to have those conversations, and all your customers will. That's why, again, these growth rates are so interesting right now for Anthropic, and whether they can still maintain that unparalleled growth rate in the context of this kind of chipping away. It's like in The Old Man and the Sea: the guy's bringing back the fish, and then the other fish are gnawing at bits of the body. They're just taking away slugs of revenue from them.
Well, then you've got Jev, and you've got a load of the other Jev competitors also attacking them in a different way.
Yeah, and again, the forward momentum has been such that all this is like, "Yeah, thanks, Rory, that's super interesting, but did I mention we 10x'ed last year and the year before?"
The other thing I think that's important to understand, and Jason, I'm curious what you saw at Dreamforce, is that there's a big gap between where the capabilities are and where actual usage is in the enterprise. I think there's a paucity of real, experienced skill sets inside the enterprise.
I think we're going to see Jevons' paradox come into play, where basically, as these costs come down, people will get more and more comfortable deploying these systems for more and more use cases across the enterprise. As they get more conversant and skilled around these technologies, they'll start deploying them for more use cases.
I see this even at MongoDB. I think you're going to see that this is, frankly, a massive market, and I think everyone can be successful. I won't comment on the growth rates of the frontier labs versus the open-source models, but I don't see this as being a zero-sum game.
To answer this, the Captain Obvious answer to what I learned at Dreamforce is that everyone I talked to was overloaded with the amount of internal demand there is for tokens. Whatever it is, it's more than they can imagine. Whether it's being used properly, whether it's being burned for nothing, whatever the cap is, the demand is probably an order of magnitude more than they've figured out how to surface, right?
That may lead to using suboptimal models. It may lead to a lot of waste in some ways, but everyone's got to manage it. That, and the fear of using China-based models, again, right or wrong, is just a huge opening if you can nail it.
The only thing I will add, just for fun, and then we can move on, is that personally, I'm getting more and more skeptical of published evals. Of course you can make an eval look great. How fast was it? What were really the outputs? How well did it perform on a real workflow? How well did it perform on a mission-critical workflow versus telling you an item was in stock when it wasn't, which is still kind of a mission-critical workflow?
I found that every single eval needs 3 asterisks and 4 daggers next to it today. I'm skeptical that Beam is as great as they say it is. I just asked if I could get on OpenRouter and check before we end the podcast, but it's not there yet. I would try. It's not that I don't think these are all great; I just think all the evals are so biased and focused on chess championships that I'm slightly skeptical.
We have Nemotron, we have Thinking Machines, and we have Reflection. In 12 months' time, what percentage of tokens in open source will flow through US versus Chinese models?
Just 2 things. As Dev made the point in the beginning, developers will change, especially here. This is a lot easier than swapping out your database. That could be done, but having recently done it, it's some work, man, I have to tell you. It's not easy, even with an LLM.
This is still work. You have to qualify your prompt. You have to redo your workflows. It's not nothing, like the internet says. But I could see it being half. Twelve months is a lot of time, and I think sovereignty plus being US-based is really important.
I'm not saying it will happen because I don't know that. Again, I'm skeptical that the parity is really there versus just pretending it's there. But if you're even X minus 3 months, to Dev's point, it could be half in a year. A year is a long time.
But that gives me a lot of confidence. I'm an investor in Fireworks, as is Sequoia, and I think the biggest concern I would have as a Fireworks, Base10, or Modal investor would be that big enterprises are concerned about Chinese models. That would prevent them from engaging with partners like Fireworks or Modal, and they would then go to the frontier models.
The fact that you say 50% shows me that the level of quality you think is sufficient is enough to reach that rate. That makes me excited.
I think the other thing that enterprises are going to care a lot about, above and beyond cost, is safety: being able to trust these systems. We're just getting focused on this. Obviously, there was that big conference last week in Washington. It's clear that there's going to be some self-regulatory approach to figuring out how to address safety.
The challenge is, how do you define safety? If someone knows how to define it well, I'm really curious, because its beauty is in the eye of the beholder. But we need some way or some mechanism for people to determine, much like with a benchmark—and yes, people can game a benchmark—how safe these models are.
The safer these models are, with whatever mechanisms are in place to prevent people from doing bad things, the more widely usable they'll become.
Agreed. I wouldn't guess 50%, by the way, Harry, but I think even 10% or 20% would be extremely significant in terms of tokens. If you think about it, the foundation models on OpenRadio, I think, get 20% to 30% of the tokens and get 90% of the dollars.
If the US open-weight models are even 50% or 60% of that in terms of tokens, that's a lot of traction, because it will be, by definition, the more enterprise-centric, safety-conscious customers using them. I think that would be, frankly, a huge triumph for Reflection and, as you point out, a real de-risking for all the inference guys.
5. ElevenLabs Wins The Voice Race
Ding, ding, ding. We have an investment committee. Dev, welcome to the committee, by the way. We're thrilled to have you as part of the investment team. You are sort of traditionally on the new, new firm that is O'Driscoll, Lemkin, Stebbings.
Jason, we have ElevenLabs, which doubled its valuation to $22 billion. Would we do $22 billion?
I think at $22 billion, we should consider doing up to 10% of the fund. Time is short. We're at an 18-month deployment cycle. One of our most esteemed partners is going back to run a public company, so we're losing some of the folks on the team.
The way I see it, ElevenLabs has done something quite difficult with a fair amount of intense competition.
Its lead keeps widening. Voice is one of the 10 most important underpinnings of agentic applications, and voice applications are where they're going. The rate of growth and, surprisingly, the margins are very impressive.
This is a company that, by the time we close the friends and family round—which we're hoping to do at $50 billion, right?—could be approaching $1 billion in revenue. That's the sort of growth rate that I think it's the deal we've got to do, and it's highly differentiated. I won't say they have the highest node out there in the world, but this is no... This isn't Jevons-level risk.
ElevenLabs has built an incredible team. They have sub-millisecond response rates for voice, which has become a key modality, and it's tough to find a better asset today. Do I wish it was at $21 billion or $18 billion? For sure, but I say we go all in.
Can I ask you, Mr. Lemkin? You previously said on the show that this would be the year of substitution for voice models and that cost would drive that decision. Have you changed your mind?
No, because I think ElevenLabs is, for the most part, it's always a risk. For the most part, it is covered. It has multiple models. It covers the low end and the high end, and quality here is, in many ways, more important than it is in your classic open-weights model.
We can tolerate a little bit of laxness in the reasoning for noncritical workflows, but when that flower dealer is picking up the phone, it has to work. It has to answer that phone in seconds, and it has to be the right flowers. If it fails, if it misunderstands it, if we can't populate this, this product isn't worth it.
There is a limit to price, but I'm shocked at the deal size of ElevenLabs. I'm shocked at the number of folks at relatively modest companies paying hundreds and hundreds of thousands of dollars a year happily, and our reference checks said they love it. They feel like they're getting a good deal.
So I don't think all models are fungible. Despite some of the other discussions we've had at the fund, and the fact that I did recommend putting maybe $500 million into Reflection and others, this is not a fungible use case today. In 12 months, it's hard to predict, but I'm impressed with the team, and I don't think anybody's going to catch them here today. It matters. This is where the LLM matters.
10% of the fund goes to ElevenLabs. Wow.
I just don't want to do it over 2 rounds. I don't need to see it at $50 billion or $100 billion. Dev knows what I mean, okay? I don't need to see it a second time. I just want to put all the chips in now, get the ownership I can, and move on, right?
I've got a friend of mine who's a CRO whom I want to put on as a board advisor. I think he'll be able to help out and give them some insight.
Okay. Moving from one Sequoia company to another Sequoia company. Sorry, Dev, it's not intentional. But Rory once said something like, "Whatever game you're playing, just beat Sequoia." Do you remember the one I'm talking about?
Yeah.
There's so many quotes. I mean... I've been doing this 30 years, and when I came in, Sequoia were at the top, and give them huge credit, 30 years later they're still there, you know? So, yes, I gave the Gary Lineker football quote, if you recollect.
To great surprise, Sequoia made hundreds and hundreds of millions of dollars with Salesforce buying Listen Labs for $2 billion. Now, apparently they had offers at $1.5 billion. A major win for Bryan Cheire at Sequoia. About $850 million back to investors on 96 invested. Sequoia did the best. They led the seed, they led the A, making about a 25X. Ribbit led the B, which did 4X in 8 months, so well done, Mickey. What did we think of this, guys?
I think it was a great outcome for a very clear category. Stepping back, market research is a very large, fragmented, almost pre-technical industry. There's a bunch of consulting-type companies, and then there are 3 last-generation companies: Qualtrics, Medallia, and what was SurveyMonkey, all of which got to high-single-digit, low-double-digit billions of dollars in terms of market-cap outcomes.
So it's a really good category. It is an existing category with a big-ass spend, and LLMs just do it so much better, because what are you doing in market research? You're asking questions of people and aggregating and assimilating the answers. The 2 things LLMs do well—we just talked about voice. Voice as a modality is a solved LLM problem. And then asking questions—not just these canned, stupid, last-generation surveys where, no matter what you say, the survey just asks the next dumb question.
You know, it's like, "Did you like your stay?" "No, I didn't even check in." And then the next question is, "Was the bed comfy?" That's the last generation. Whereas now with LLMs, you can adjust the questions based on what the respondent is saying.
All that means market research can be done so much better with LLMs, and I think Listen Labs was one of the early contenders that did it well and executed brilliantly and got to real revenue. Great outcome. It is one of those use cases for AI and LLMs at the app layer that comes out as a top-5, top-10 use case, and there it is.
But you know what? I would love to get Dev's thoughts on this. I am a fan of a lot of Salesforce's acquisitions, and I've been a champion of many of them. This one I don't really get. It's not that I think it's a bad idea, but Salesforce is coming up on $40 billion in revenue. Their target's $60 billion—they're almost at $50 billion. I just don't know how $20 million of revenue from a next-generation AI survey moves the needle.
And I'm not saying it doesn't. I mean, at Mongo scale, you've got to move—it either has to tuck in or move the needle, right? Maybe you think about it differently, but to move the needle it's got to be big. And Salesforce even...
What I will say is that I think we're probably going to see more of these deals, right? Because I think there's starting to be a difference between whether you're building a feature that's masquerading as a company or a franchise, right? A lot of AI application companies will sell because a clever product on top of someone else's platform is frankly a feature. And if they can use the distribution of that larger company, they have the cash and distribution, they're going to take advantage of it.
I think the companies that are more durable are the ones that are essentially creating a data loop where the user creates data that no one else has, the data makes the product better, the product attracts more usage, and you create that virtuous cycle. If someone tries to copy you, they can copy the features, but they don't have all the interactions that you have.
So I think the difference here, when you look at these standalone AI app companies, is whether they're really a feature masquerading as a company or whether they're really building a franchise. And I think the founders of Listen Labs decided that this was an offer that made sense for them.
I mean, you'd be pretty pissed off if you're Intercom, wouldn't you? You're just like, you've gone through 15 years of shit and struggle and building this business, and then ABBA's answer to Justin Bieber comes along and 3 years later sells for a comparable number, and you're like, "Fuck." Sorry. I know they all made money, but you'd be like, "Oh, bugger, that was an easier route, wasn't it?"
Of course you think that as a founder. There's always someone who had the easier route, and you do think about it. Of course you do. Even at Mongo, I bet Dev thinks about it once in a while: "God, I mean, we've done great at Mongo, but those guys had an easier way with it."
The lesson I tell my boys is, "Comparison is the thief of joy." You start comparing yourself to everyone else, and you're going to be very miserable for the rest of your life.
Yeah, Rory. Yeah.
Hey, I didn't do it, Harry, you know.
Rory.
Yeah, comparison's the thief of joy, okay? God.
Good to know, Harry, but that's why you were wrong to mention that, because in the end I think both companies made money, and to Dev's point, you'll step back and say both of them will go, "Yeah, I feel good about what I did."
Now, you're right. It's a lot easier to do it in 3 years than 10 or 15. Duh, we get that, but life ain't fair, and venture outcomes are very random. More than anything, what it says is that timing and the cycle are just so interesting.
Look, we put some money in Intercom recently. Intercom achieved that valuation. It could have happened for Intercom if they had sold in 2018 or 2019, in the SaaS boom. To Dev's point, maybe we will look back. In 5 years from now, maybe 10% of these app companies will have sold early. They'll have got their 30X revenue, and the rest of them will be grinding it out for 6 times revenue at $300 million with 3,000 employees and their head exploding, right?
But you just, to some extent, can't control the outcomes. You just have to like the process, right? And if you end up doing well, then both of them have done just fine.
I will say one thing. How old was Listen Labs? When was it founded?
3 years old.
I will say, as a founder, having been through different lengths of journeys, the earliest days are always the hardest, right? They're sort of fun because it's just you and your crew—it's very creative in that way—but unless you're one of the lucky kids these days, you almost always run out of money. You don't have enough customers. It's brutal, right?
But I will say, if you can exit for a good price in 3 to 4 years, I'm not saying you should, financially, but, man, it's easier. It's so much easier to exit, no matter what struggles you go through as a team. I find it's 5-year chunks, and they take it out of you, right? I'm not saying it's a reason to sell, man, but if you can sell for $2 billion in the first 5 years, I might—I might tell them to take it. It's not that we don't all want to build a Mongo. We do intellectually, but, man, just do it in the first wave; it's so much easier.
I don't think anyone is sitting on the call screaming, “I can't believe you sold. Damn it, guys. Why would you only take $2 billion? Be a—”
No, no, that's not true.
“—magnitude.”
We've all had VC meetings where a company is like this, and no one around the table says you should sell on a deal like this, right? I had one this year at about this price, and every single VC said, “Don't sell,” right, in that first wave. And it's because there's a lot of momentum in the business, da, da, da.
But, man, getting out for that first exit—I know you can call it the first exit, but you really can do another. The thing is, you have to decide if it's generational. Are you building a Mongo or better? Then, of course, you say no, right? If you can get out for $2 billion in the first 5 years and you're not building Mongo or better, I don't know, man. I would take it and enjoy my life at Salesforce.
It's such an old story now, but for some reason it's surfaced on Twitter: the whole Zuckerberg turning down $1 billion from—was it Yahoo or Google? I can't remember—right early on, without even thinking about it twice. But I think the real point, Jason, it comes to your thing: you have to be kind of cold-blooded. What's the likely trajectory from here? How do you feel about running the tape, and how likely are you to get not just 3 times this amount, but 10x this amount and more? How do you assess that, plus the personal side?
I think you have to be honest if you're trying to build a generational company. I don't think that's a catchphrase. I think it's really important. Because otherwise, you have a terminal value, a terminal state, and if the offer is reasonable, you'll never beat the net present value of these deals. This generational stuff isn't easy. I mean, Dev's back in the seat again. It ain't easy—this stuff ain't easy, this generational company stuff.
So, and I will tell you, the best companies always get offers to sell, right? So I'll use my example, and I wouldn't say BladeLogic was a massive outlier, but every stage of our growth, we had people who wanted to buy us. I remember sitting—I guess I can share this now—I was in John Chambers's office. We were literally sitting face-to-face when he wanted to buy the company, and then, for some reason, it just didn't work out. Then they came back again. I had EMC at the table. And you just go and go, and then ultimately you sell a year after you went public.
And I think, to Jason's point, ultimately the founder has to decide: Do I feel good about continuing to build, or should I just hit the exit button? And I felt good about our decision to sell to BMC, but we came really close a number of times to selling the business earlier, and looking back, it was the right decision.
How much did you sell for to BMC?
We sold for about $900 million, which at that time was the highest acquisition price paid in 2008.
It was a killer deal. I had a small company that competed with him. He cleaned our clock. BladeLogic was the winner in that category. Actually, the number 2 was Aref, who is now at Bain Capital. He was running CenterView, CenterPoint.
CenterOne, yeah.
CenterOne. You walked all over us. Damn you.
What revenue were you doing when you sold?
We were doing about $100 million, so 9x. Which, by the way, was right on the heels of the GFC, so the market was getting quite skittish in 2008.
6. Agents Choose The Winners
One that I'm interested in is actually one that Jason suggested, which is Vercel at $600 million in ARR, with agents being 50% of the new business, up from 3% at the start of the year. Jason, I always find you quite mind-expanding for me when you talk about these topics. How do you think about this? How much budget should we give to agents for 2027? What's the takeaway for us from Vercel now getting 50% of new business from agents, up from 3%?
Well, look, I would say maybe 2 different things. One, I think there's a bunch of companies like Vercel that had the right infrastructure and the right product before AI and agents, right? So Vercel was founded in 2020, right? I mean, Guillermo did not know that in 2026, the majority of his business would be from agents spinning up applications on their own, right? Nobody saw that.
Some of the most amazing stories—even ElevenLabs is a little bit of that. Certainly Replit, founded in 2016, is a big case study where you just latch onto that and it just works, and they do have the tiger by the tail. There are a lot of competitors, a lot of really strong competitors, but agents pick Vercel. It's very strong.
And, you know, it was interesting. I think—what did they say? They're growing 170% at $600 million from a 20% increase in customers or something. I mean, the expansion revenue is astronomical. And the thing is, when agents pick you—and I'm sure Dev's thinking a lot about this, right, on the database side—when agents pick you, it's a force of nature right now.
And agents, what I've learned from them—we have 21 agents we're building all day. Between me and Emil, I'm literally building 8 to 10 hours a day. And, man, my agents have opinions, and they're really hard to argue with. And if they want to use a vendor, it's a lot of energy. I know I'm anthropomorphizing it, but it's powerful when an agent decides something, and Vercel is a major beneficiary of this.
Even last year it looked great, but it never seemed it would be as important as it is today. “Oh, that's just where I'm going to stick my code,” right? Important, but back-office infrastructure. But, man, this is where so many agents and apps are running, and I would take this one to the IC too.
I think this is really interesting, the point that Jason made: agents are picking or making decisions, right? For the last 25 years, every marketing person, every company has optimized how you show up on page 1 of Google, right? You educate human buyers. Now you have to make sure that agents can find you, understand what you sell, and have current, accurate information about you across the sources they read. And if you're missing from an AI-generated answer, it's like being invisible on Google.
Full disclosure, Sequoia has a company called Profound that helps companies with that, but I will tell you, this is a massive problem. And it's not just in tech. If you're an e-commerce site or a retail company trying to sell through e-commerce, and agents are now making the buying decisions, you've got to figure out how to educate those agents; otherwise, your business is going to zero.
When I look at this market, we too have a company, Dev, Peak, and everyone's like, “Well, it's like the next generation of Semrush.”
Is it just a next generation of SEO analytics providers, with your Profounds and your Peaks, or is this actually a much larger category?
I think the opportunity is more than just analytics that tells you where you're missing and all that. I think the opportunity for these companies is not just to tell you what you're missing, but to help shape the content and create the content to help you solve that problem. If they can close the loop, that becomes a very compelling solution versus just telling you, “You're here. You're not here. This is what the other guys are doing.”
I'm just looking today, for example—it's smaller, but look at Resend. The first agentic purchase we made was Resend for email, okay? When I was trying to set up a bunch of agents last year, I kept getting recommended SendGrid. But because they needed the CEO to go back—the founders to go back—I just couldn't get the damn SendGrid thing to work. They'd kind of deprecated the free tier; I couldn't figure out the key. It kept breaking.
And so I asked my agent what I should use. It said, “Use Resend.” Resend went from 106,000 MCP calls in April to 3.3 million in September. That's agents saying to use products. And I'm not saying Profound isn't doing that; it may well be. My limited experience is that this is different.
I want to kind of disagree with you all. How did your agent decide? Because I assume some part of it is the general—how I show up initially in the answer engines, you know, how I show up on OpenAI. And then what else does the agent look at? Is it just the ease—
It looks at your infrastructure. It looks at the application you're building. It looks at what's trusted. It looks at what it thinks the right match is. And once in a while, it'll make wacky choices that are very specific to your use case, but you've got to be that one.
And it's not that ChatGPT is going to give you a generic answer based on a number of factors. I'm not saying they aren't using the same LLMs, right? So some of that is being baked into it, but an agent knows your whole stack. It knows everything. It knows your application. It knows what you've built on top of the system. So it will make a very specific recommendation about what to use.
This problem is even more profound, no pun intended, for early-stage companies because there's so much corpus of data for your incumbent, who's been around for 10 or 15 years. If you're trying to disrupt some incumbent, the agent's going to see all this data about the incumbent and very little about you. So when it makes a decision, it could very easily just pick the incumbent solution.
It's actually incumbent upon the startup to figure out how they educate agents on what they do—the documentation, the APIs, and all the infrastructure and the wrapper—so that they can then show that they are truly a first-class experience for an agent to make a decision on.
For what it's worth, here's what I tell my portfolio companies I've invested in or work with. I say, “Find 10 folks you know that have agents in production doing different things—10 folks you trust—and ask them every 2 weeks, ‘What would you recommend in this category? What would you recommend?’ And see what the agents recommend.”
This product doesn't exist today. I think the 4 of us should fund it. It's not the same as Profound, which is guessing what LLMs do. These are live agents in the field, in different applications, asking the agent what should be used, right?
Just to understand, where is that agent who will answer the question? I mean, that agent presumably is doing some other job, and you'll just go on and say—
The agent could be at any tech company. Any startup is going to have agents running today that are worth their salt.
Yes. And you will allow your agents to spew out what they're using internally?
Yeah. For example, I'm literally on the phone right now. I'm asking one of the apps I'm building, SaaStr Guide, through its agent, “What should I use for hosting?” It said, “First, use Render.”
Honestly, I barely know Render, okay? It says, “Use Render, my pick.” The agent said, “My pick.” Number 2, Railway. We know Railway. They're doing pretty well. Number 3, Fly.io. Number 4, ADOs. Number 5, Vercel—not suitable for this.
I would have picked Vercel for this. I don't even know—you guys may know Render. I never heard of it. And you know what? I would probably use Render. It literally says, “My pick.” So Render just got a lead. It just got a pretty good lead from this agent. You gotta win that war.
Can we get into the last round in Render? Can we get the Sequoia price at Render? What was the Sequoia price in Render? Anybody know?
I did. I did. I did, but I don't know. I don't think it's actually the same market as Profound and Peak. I actually do think it is, because I know both companies actually wrote a term sheet on the Profound A, which we got.
I think naturally both those companies, when they're finished figuring out how you show up on ChatGPT for humans, are going to quickly evolve to: “If agents are who I need to show up for, then by God, I need to tell my customers how to show up for agents.” So I think it's a natural next product extension.
Don't get caught up in the minutiae of, “Oh, we only do it for humans.” Zooming out, as Jason has convinced us, everyone—humans and agents—will make purchasing decisions using LLMs and using information they get online, and you're going to have to make sure as a vendor that you show up correctly, whatever that takes.
The opportunity there is to sell a solution to the marketing person who's got to solve that problem in any company. There's some dude at MongoDB who is going to be figuring out this afternoon, “Check how we show up on agents to make sure when Jason needs to get a database, we show up first.” If that person needs to have some way of surveying what other people are saying about them, what other agents are saying about them, that's a product that MongoDB is going to buy.
I think that's the Profound opportunity. It's the Peak opportunity. It's a bunch of other companies in the space. I think it's a good space, and for some, I think it's going to have more depth than the Semrush space, which ended up commodified and boring for a whole bunch of reasons.
I agree.
For a reminder, we did the Series C, I think, at HubSpot, and I say this over and over. It was an SEO company to start out, but they just did a brilliant job of adding a whole bunch of other stuff on top.
You solve the customer's immediate pain point, especially these marketing platforms. You solve the customer's immediate pain point, and then they realize they have an adjacent pain point, and you solve that, and then you solve the one after that.
I think every marketing person has a 3-year list of pain that they have to solve in terms of how they show up in the new world of LLMs, and they want all the help they can get for that. If you make solutions, you can make money here. So I think it's a super-good market.
What topic have I missed, boys, from the list that I have to discuss?
7. Groq Deal Tests Corporate Law
There was one I liked, but I like this one because it could change a lot of tech stuff. The engineers suing—which one was it? Which are the—
Oh, Groq. Yeah.
The license deals? I didn't think about that, but now it seems like an obvious claim: I lost the benefit of my consideration by doing this. I don't know where the lawyers come out on this one, but, yeah, give us the background on this one.
Grok's engineers sue over NVIDIA's $17 billion license and hire deal. Two former engineers sued in Delaware, alleging Groq's board effectively sold its core technology and top 200 staff to NVIDIA through an $11 billion license, plus about $3 billion in stock, leaving common holders with a hollowed-out company.
The news is that they perceive there might be a cause of action because, zooming out a million miles, corporate law tries to say everybody gets treated the same. There are 200 years of precedent, and you know exactly how it happens: all common shareholders get treated the same. Board members have a duty of care, a fiduciary duty to all shareholders. There's case law up the wazoo, and this stuff tears up all the case law.
It effectively allows the buyer to reallocate consideration in the company: “Hey, you guys are coming across, and you get a lot of money. You guys are staying behind, and you get a little money.” Crucially, these 2 employees had already left the company. I don't know this for sure, but my guess is when the acquirer is allocating capital, they don't say, “I also want to take care of the ex-employees,” because they're like, “Why would I bother?”
But Delaware law says everyone who owns common shares is treated exactly the same, and it's one of the non-negotiable principles of this stuff: You treat everyone in the same security in the same way. So when I read that, I thought, “Hmm, that's interesting. That's a clever little case,” and it'll run a little while.
I wouldn't be surprised to see it settled, because there's probably only a small number of people in the class. My guess is everyone who came across was happy. My guess is everyone who stayed and got stock is happy. So it could be a relatively small number of people who'd left already, but it's going to be an interesting case where they probably have some legal argument to make.
Yeah. I'll connect the dots. Remember we started this discussion about people leaving, and leaving very quickly, and here's the parallel I draw: Investors long ago—and actually even more recently—have learned to protect themselves in situations. They negotiate these kinds of issues up front: what happens in any kind of exit, including a weird one.
Employees never thought to ask about this. So if you're a founder, you're going to have employees saying, “Hold on. What happens to my equity if the company's tech and some members of the team get bought but the company doesn't?”
I think founders need to be able to answer that question because that's a question that, as people learn about this, is going to be coming up more and more often, especially if people switch between companies very often.
The idea of corporate law in Delaware—or even if you go to a place like Texas—is that you shouldn't have to think about it as an employee because it's like, dude, there's common law and you'll all be taken care of the same. But once that gets eroded, as you say, once it's up for grabs, then it's quite insidious.
You're right. Everyone has to think, “When I join a company, I don't just have to think what my 1% is worth; I have to think, well, what could happen to my 1% if you sell the IP? What could happen to my 1% if you sell the IP and half the employees?” I think it probably makes everything harder to pull off.
It'll be interesting to see if this leads to some kind of pushback away from those kinds of structures. I mean, they're not ideal, and the only reason people are doing them is because of the FTC. No one will ever say this because they can't, but it's because of the FTC and the fact that you can't get M&A through in any appreciable time, whereas you can get these deals done literally overnight and the employees start the next day.
It's a workaround to a regulatory problem that is, no surprise, creating a bunch of second-order issues and unfairness.
I just think it’s interesting because this structure is fading away a little bit. Politics aside, in the current administration, it sure seems easier to get a quick deal done—a Fin or a Listens lab pretty quickly, right? So some of these issues are fading at the margin. But, man, I don’t know. Some of these deals sure feel like mergers in substance to me.
So I think if one of these lawsuits wins—which, even if one fails, another may well win, right?—I think these are mergers in substance. I think these deals will die because they already have double taxation. They’re already horrific from a double-taxation perspective. Then add a whole set of risk and carve-outs for the employees we’re leaving behind with the keys at Windsurf, who will end up being the big winners in Cognition, right? But it looked like they got left with the keys and a year of cash to work it out. I think it’ll end these deals if there’s significant legal risk here.
And it also feels to me a little like a SAFE note. You know, SAFEs say—I know this sounds niche—SAFEs say they qualify for qualified small business stock because they’re stock, but they’re not. They’re clearly not stock, and all these non-merger documents say they’re not mergers. I’m sure they say it a thousand times. The more deals go by, the more clauses say it’s not an acquisition. But just because you say it’s not a duck, it doesn’t mean it’s not a duck. I think some of these are ducks.
Exactly, and that’s exactly the case they’re laying out: it was de facto an acquisition, and there’s a whole bunch of things you have to do in an acquisition. So, yeah, you’re right.
It’s just interesting in hindsight that we didn’t think about this because we may end up being like, “How the hell did we think we could do these deals?”—and completely work around not just part of the cap table, but the whole cap table.
But no, it’s ask forgiveness, not permission. I don’t know. We talked about it at the time. We don’t like it. It feels unfair. But I think the pragmatic answer that I’m willing to bet—Groq was NVIDIA, wasn’t it?—I’m willing to bet, let’s say they have to settle and they have to chuck in an extra $200 million. The real answer is, my lawyers, my very smart lawyers, came to me and said, “I found a way that we can buy this company on a Sunday night and all the employees start on Monday morning, and we have the IP,” versus this other way where we put in an application to the US government and close in 9 months.
And Jensen said, “Is there some risk?” And they said, “Yeah.” He said, “I can live with it. Done.” We did the deal, and then 2 years later you go, “Yeah, there was a little bit of risk. It turns out it’s 1% extra on the price. Here’s $200 million.”
8. Muse Outshines Dots
Right. I think an additional point that just isn’t discussed enough is that Muse was a phenomenal launch and has had a phenomenal reception, and I respectfully think Dots has been very unimpressive. I thought that demo was incredibly poor and very tech-centric. How do I do flights for enterprise usage for an OpenAI employee? I thought it was out of touch, and I thought it was very underwhelming.
I’ve used Muse for a while, and you’re right. They’re doing Muse—they’ve killed it. And, as someone who thought, “That acquisition isn’t working; it seems there’s a whole bunch of gears grinding,” I just have to give the executives credit. Whatever happened between Zuckerberg and Alex Wang, they put their heads down and shipped product.
And as the CEOs on this call know better than me, that cures everything. They shipped a killer product, they launched it full-on, they resourced it with compute, and they kicked ass. And it’s good. I mean, I’m going to New York this week. I’m playing—it’s real fun. You do Instinct and Muse, and you kind of check on them and see who’s winning. It’s kind of a bit of a geeky joy, but there you are.
They’re absolute—let’s use the word frontier—state-of-the-art. This is as compelling as any fricking startup. Muse nailed it. And you’re right, conversely, I was trying to figure out Dots today. I wasn’t quite sure what it is, even at the end of it. I went and looked at the whole online demo day thing in anticipation of the program here, and I’m not quite sure I got it yet. I see where Spaces is going, but, yeah, it’s not nearly as cool.
And so, as a 30-year venture investor, Rory, how do we feel about America adopting this?
I don’t know. I’m not going to be as opinionated as that. I’m not a product guru. I’d like to hear from these guys. But my point is, I wanted to celebrate the good because in the past I’d been a little cynical of the Meta thing. They nailed it. I want to celebrate the good stuff. All I can say on the OpenAI Dots stuff is I’m still trying to figure it out.
So, Jason, did you turn it on? Did you try Dots?
Well, I don’t disagree with Harry’s point that the consumer PR element was definitely underwhelming, considering the Muse buzz, which I modestly contributed to. But I think it’s because the initial point of Dots is that it integrates with Codex and can work as a 24-hour coding agent.
And one of the annoying things—and one of the things that’s under-discussed that Replit or Lovable actually did well in the early days—is that they could be on all the time, right? At least sort of. But it’s pretty annoying. You can’t really keep Claude Code or Codex going 24 hours. That’s why OpenClaude took off, among others. I’m simplifying a lot of stuff.
Now everyone has a 24-hour persistent agent that can work with Codex, if nothing else. So I want to give it 30 days and see what developers do for real with a persistent agent optimized around Codex before giving up on the fact that maybe they weren’t as excited about booking my business-class tickets to Palm Beach over the holidays as other folks were.
It could end up being the bigger win, and, almost in a sense, it’s almost guaranteed to win in that sense, right? If it’s the persistent extension of Codex and building on the OpenAI stack, it almost can’t lose unless they stop developing on it. But maybe it’s never that consumery. Maybe it’s just a nerdy product and, like Mongo, it’s okay. You can make money in these nerdy products, can’t you, Dev? There’s money to be made. Let’s view it from the developer lens and give it 90 days and see what cool stuff gets built.
It points to the thing we’ve said before. It’s just super hard to be developer-forward, enterprise-forward, and consumer-forward at the same time. Interestingly, it ties back to the Mongo comment and where your former colleague went to run the enterprise side of Meta.
I think doing one thing well is hard. Doing 2 things well at the same time is super hard, and I think OpenAI struggles with that all the time, even on the product surface area. There’s just a lot going on.
Do you remember last week when you mocked me for buying stocks in the middle of a show? 26% up in a single week, Rory.
What did you buy again?
I bought Nubank, and I have to admit I didn’t quite know the Brazilian elections were coming and would go in my favor. I didn’t know that the Monzo deal would not happen, which would also go in Nubank’s favor. But 26% in a week—I got a lot of thank-yous from people who made thousands and thousands of dollars.
So let me get this straight. You bought a stock, and 2 things that you didn’t expect happened, and your stock went up, and you’re feeling good. That’s the takeaway here, right?
Well, I feel more charitable. We made money.
Gotcha. I just want to understand. No, but it is interesting that, as a Brazilian-based company, the stock goes up when they realize they’re not investing in a third-world country like the UK. The stock pops. Sorry, just being me and Harry.
Harry, can I do one before we lose Dev that I’d just love to get his thoughts on?
Yeah.
9. The Aura IPO Stalls
I added it to the list because I don’t think we touched enough on it. On the Aura IPO, I thought this was terrible news for venture—terrible news for venture. Because you could argue this one is overpriced, I guess, right? I mean, that’s an analysis.
Rory had a point that Forerunner was selling its whole stake, which was a large part of the IPO and adds some element to pricing. But I just think it’s a huge bummer that a company growing $1.2 billion, growing 74%, with a pretty attractive recurring-revenue portion of it, had its IPO pulled.
We talk about M&A and liquidity being easy, and M&A being everywhere, and the 1000th frontier lab being bought for $7 billion. But this one kind of bummed me out—honestly, it bummed me out that this deal didn’t happen. I felt it was under-discussed as something that didn’t happen. I don’t know what you thought, Dev, on this one.
I think, Jason, it’s like that old saying, Occam’s razor. I think we’ve got to figure out what the simplest answer is, and to me, I think it was probably price. Again, I have no inside information, but I think the bankers probably told management and the board that they could get this deal done at a certain price.
They quickly had an oh-shit moment, and rather than go through a protracted problem—and I don’t think the optics of someone selling their entire position is great, for whatever that’s worth.
I think it came down to them not being able to get the price they wanted, so they pulled the filing. That’s purely speculative on my part. I have no inside information.
But you really think they…? I mean, for sure, but the markets are pretty good overall, and it’s hard to grow much faster than 74% at that scale if you’re not an LLM.
But it’s a function of what multiple you think you have.
I totally agree. Again, disclosure: as you know, we have a small passive piece there tied to an M&A situation, so I was bummed too. But to your point, I think the super-interesting point—and there was a good piece in The Wall Street Journal on it, right?—is that it is possible they pulled it because there’s an M&A pending or something like that. Let’s assume that’s not the case. I just want to put it out there to outline the range of options.
I think Dev raised an interesting point. It’s more interesting than just Oura because it gets to banker dynamics, right? We’ve all seen it. Bankers are pitching a deal. They want to tell you as optimistic a story as possible. The problem is, this could be one of those cases where, if you convince the board that you’re going to get $50 a share when you’re trying to get the business, and then you go out to talk to the investors and you’re only offering $40 a share, this is the kind of dynamic that happens.
You see that happen in IPOs, right? It feels like a very subpar outcome. And you’re right, Dev, I do wonder—I’d love to see what the banker books were when they pitched the IPO and what they said the price per share would be. This is the problem: it’s always a weird dynamic when bankers are pitching an IPO because, to some extent, there’s always the feeling that you just go for the person who says you’re going to get the highest price. But if he’s whispering bullshit in your ear and it turns out not to be true, then you end up in this far worse situation where you think you’re going to get something done, you telegraph it, and then it doesn’t happen.
I would hit the bid on price here, boys. Come on, you look at the consumer hardware companies that have gone before, from your Jawbones to your Pelotons. I mean, hit the bid at 13 and take it out already.
Yeah, I agree. What you’re saying is the board should have said, “These guys told us $30 a share, whatever it is. They didn’t believe it, but we didn’t believe them, so our lies cancel each other out. We got offered $20 a share. That’s a good price. Hit the bid.” And, yeah, they obviously chose not to, and they had their reasons. But, yes, I think it’s very hard to go this far down.
I can’t remember, Dev. Did you guys at BladeLogic hit it the first time—
Yes.
Did you have an extended filing or something weird like that, or did you come straight out?
No, no. We got straight out. It was a little wild—the market was a little wild at the time because that’s when there were signs that the debt markets were maybe not as solid as people thought. We went out in July of 2007, and then the markets progressively got worse going into 2008. But we got out.
Got it. So you probably would be one of the last out of that class. I remember we had Omnitro in—I think it was ’06 or early ’07. But, yeah, you had that Vonage company and a couple of others, and then it got thrashed, and then it was done.
But, yeah, Harry, to your point, playing that back, listen to what he said: the debt markets were getting a little shaky. Take a look at The Wall Street Journal now. Sometimes you’re right, Harry: you should hit the bid and get it done when you get that far down because there’s a lot that’s got to happen between now and the Anthropic IPO in the middle of November.
I don’t mean to be rude, but I have to go sell some software.
Yeah, you’ve got to sell some software.
That would be great. Go.
Go sell some software, baby. Thank you for the time.
Thank you for joining.
It was great to be on the show.
That was awesome. We’re done.