← The Twenty Minute VC (20VC): Venture Capital | Startup Funding | The Pitch
The Twenty Minute VC (20VC): Venture Capital | Startup Funding | The Pitch
20VC: Benchmark's Newest General Partner Ev Randle on Why Margins Matter Less in AI | Why Mega Funds Will Not Produce Good Returns | OpenAI vs Anthropic: What Happens and Who Wins Coding | Investing Lessons from Peter Thiel and Mamoon Hamid
01:25:43
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- [00:00]
A
I think we should not be placing that much emphasis on margins today. We need a new taxonomy for AI companies like Tiger died and we got six or seven more Tigers. I don't think Ravi or Hamant or even Ben and Mark at this point. I don't think that they can go to LPs and say, we're going to get you 5x net on that. When you're writing billion dollar checks, that is your main product. Go talk to the principals, the junior partners and the associates at those firms and you tell me that Capital Velocity is not the North Star of those firms. I think Tiger's gonna end up much better than anyone thought they were going to end up.
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B
This is 20 VC with me, Harry Stebbings.
- [00:37]
C
And this is one of the best.
- [00:38]
B
Shows I've done in a long time, I think.
- [00:40]
C
So fun fact, I've never met this guest before.
- [00:44]
B
When you hear it feels and it sounds like two friends shooting the shit catching up over a dinner, I have to say I think he's just like my long lost brother. But it was so much fun.
- [00:55]
C
So I'm thrilled to welcome general partner.
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B
At Benchmark, Benchmark's newest partner, Everett ra. Benchmark are one of the best firms in venture.
- [01:03]
C
In their latest fund they have Macaw.
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B
$10 billion valuation, Sierra, $10 billion valuation.
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C
Firework, $4 billion valuation. Ligura, $2 billion valuation. LangChain, $1.4 billion valuation. In multiples, that's a 60x2, 30x's and 220x. Now before benchmark, Everett was a partner at Kleiner Perkins and before kp he.
- [01:31]
B
Was an invest fund and bond.
- [01:33]
C
But before we dive into the show today, are you drowning in AI tools? ChatGPT for writing, notion for docs, Gmail for email, Slack for comms. And you're constantly copy pasting between them all, losing context and losing time. This is the AI productivity tax and it's killing your output. At 20 VC, we're all about speed of execution. And Superhuman is the AI productivity suite that gives you superpowers everywhere you work. With the intelligence of Grammarly, mail and coda built in, you can get things done faster and collaborate seamlessly. Finally, AI that works where you work, however you work. Superhuman gets you from day one with zero learning curve and it's personalized to sound like you at your best, not.
- [02:20]
B
Like everyone else using generic AI.
- [02:23]
C
Get AI that works where you work. Unlock your superhuman potential. Learn more@superhuman.com podcast that's superhuman.com podcast. And speaking of tools that give you an s That's exactly what AlphaSense does for decision making. As an investor, I'm always on the lookout for tools that really transform how I work. Tools that don't just save time, but fundamentally change how I uncover insights. That's exactly what AlphaSense does. With the acquisition of Tagus, AlphaSense is now the ultimate research platform built for professionals who need insights they can trust fast. I've used Teagus before for company deep dives right here on the podcast. It's been an incredible resource for expert insights. But now with AlphaSense leading the way, it combines those insights with premium content, top broker research and cutting edge generative AI. The result? A platform that works like a supercharged junior analyst, delivering trusted insights and analysis on demand. Alphasance has completely reimagined fundamental research, helping you uncover opportunities from perspectives you didn't even know how they existed. It's faster, it's smarter, and it's built to give you the edge in every decision you make. To any VC listeners, don't miss your chance to try AlphaSense for free. Visit AlphaSense.com 20 to unlock your trial. That's AlphaSense.com 20 and if AlphaSense helps you spot the winners, AngelList helps you hire them. If you're listening to 20 BC, you know we have a really freaking high bar. Well Angellist is the modern platform used by the best in class venture funds where over 40% of top endowments and banks are LPs. Their customers include a top five venture firm, 20 VC and they now have, check this out, 171 banks billion of assets on the platform. They combine an all in one software platform with a dedicated service team that moves as fast as you do. One manager said this awesome quote angellist feels like an extension of my fund. Another said Angellist gives me total peace of mind. The attention to detail, lightning fast response time and just real sense of ownership from the team are exactly what I need to stop worrying about back office ops. So if you're starting a new fund, don't be a moron. Just use Angellist. They're incredible. Head over to angellist.comtuz0vc to learn more.
- [04:39]
B
You have now arrived at your destination. Ev. I am so excited for this. I cannot believe we have not done this before. I think I personally timed it pretty well. If I'm honest, I'm rather chuffed with myself. But thank you so much for joining me today.
- [04:53]
A
Thank you Harry. I have actually been listening to 20 Minute VC since 2017 which ironically I think is the year that you had Peter on the first time. And it's just been so fun to watch the show and the platform that you've built grow this way. It's almost like watching a startup become an IPO worthy company or something. So congrats to you, Harry.
- [05:12]
B
Do you know what? I've had a man crush on Peter Fenton since that first show. I remember he told me that price is a litmus test for your conviction. And I think about that at least on a weekly basis. And I've repeated it to my team many, many times before we dive into benchmark. You've worked with some of the best from Peter Thiel obviously at Founders Fund, Mary Meeker at Bond, Mamoon, Hamid, one of my big bros at Kleiner Perk. If I were to ask you for your biggest takeaway from each, what would you say your biggest investing takeaway is from each of them?
- [05:43]
A
One of the things I really love about the asset class that, that we, that we practice our craft in is that there's so many different ways that you can be successful at it and there's so many different strategies and frameworks that you can employ and still generate amazing returns. And each of the people that you just mentioned have very, very different styles and very different ways of practicing their craft. I think if I was to lay out for Mary, for Peter and for Mamoon, kind of what I learned from them specifically, I think with Mary, she does such an incredible job. Everyone thinks of her as this quantitative investor. You know, she had her time as an equity researcher at Morgan Stanley during the dot com bubble and then she came to Kleiner Perkins obviously and everyone talks about these DCF models she creates and all the numbers that she does, but she's really the most qualitative investor that I've ever worked with and it's probably a surprise to hear that. But what she does is she, it's almost like she's reading the matrix, like she lays out all the sequential numbers historically for a company and then all the numbers going forward. And it's almost like she's, you know, reading the matrix code as it comes down and she's seeing what the company will become on an 8 to 10 year time horizon when she sees what the numbers are. And so she'll look at a doordash model and that was an investment that we had led at kpop out of the growth fund at the time. And she won't see, you know, seven years out, 80% growth or something like that. She'll see that 20% of households are going to be ordering from DoorDash on a monthly basis. And she can visualize that. And so from her I just learned that when you use numbers in venture growth and when you want to be quantitatively driven, don't get stuck into a quantitative lens with it. Actually use that to drive the narrative and drive the story of an investment. And that's been, that's been an incredible mental framing that I've used with someone like Peter Thiel. Peter, I think so much of his cleverness and so much of his genius is actually in the way that he builds his firms rather even than his investments. So the way that he's designed Founders Fund is that he creates all these incentive structures and mechanisms almost to like constantly be testing your conviction. So there's a program, for example at Founders Fund where anyone that works on an investment or if you're leading an investment, you can personally invest alongside the firm in that investment. Almost as if you're angel investing. And at, you know, first glance, it just looks like this amazing perk that you can have by being an investor at Founders Fund. But deeper down, it's a conviction test. Because if you're sponsoring some pro rata of a company that's like doing okay but not great, but the founder really wants you to do the pro rata to not blow up the round, but you're not doing some of your portion of the individual side of that investment and your angel investment, Peter can go to you and say, do you not think this is better than having your money in the S and P? Like, why would we, you know, give our LPs this allocation in this round if you don't even want to put your own money in this round? So there's like 100 different things like that that exist in Founders Fund that aren't, you know, explicit. Like, hey, like, are you have high conviction, but test your conviction in deeper ways.
- [08:36]
B
I absolutely love that. In terms of a conviction test, do you ever just reflecting on that fear that if you had that with a younger person, say when you were a Founders Fund, if you don't have that.
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C
Much liquid cash, it is a lot.
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B
When you have rent bills.
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C
I would hate to.
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B
I'm thinking through this as an active partner with you now because I'd love to implement that in 20 VC, but.
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C
I would hate for people to be.
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B
Scared and then say no to something because they didn't have the cash. That could be great. What do you think?
- [09:05]
A
It's super valid. I think again, if you're At Founders Fund, you are, you know, you're full in and you're all in. And so I think most of us that were young at Founders Fund at the time all had like debt lines, like unsecured debt lines that we were using to do, to do these, these side kind of personal investments. And by the way, it's turned out to be an unbelievable portfolio for myself personally and it's all worked out and so I'm very glad that I, that I had it. But I think that's part of, you know, he, throughout his entire career has really again designed his organization so people are all in. He had like a Bonus system for PayPal employees. If they lived within like a couple miles of the office, he would give them more money. Like he just designs the orgs this way. And so there's less pressure for, for the young folks that don't have much net worth yet for sure, but they still expect you to be scrappy and find a way to do it.
- [09:50]
B
What do you think no one knows about the inner workings of Founders Fund.
- [09:54]
A
That they should know from the outside in? I mean, obviously Founders Fund is a bit of like a black box. Everyone's like, wow, the returns are amazing. There's a bunch of weird personalities within that place. Like, how does it all happen? When I was actually doing back channel references on Founders Fund before joining, something that everyone said to me that they thought was a negative but ended up being a huge positive, they're like, oh, you really got to watch out about the culture. Because I've heard that they yell at each other during ICs, like investment committee meetings and like they get super intense. And then a few months into the actual job at Founders Fund, I realized that like, yeah, sometimes people did yell at each other at ICs, but it was because it's almost like yelling at your brother or like yelling at your sister or yelling at your best friend. Everyone was so secure in themselves and the relationships that they had with each other. And they all have extremely deep relationships with each other that you could actually just be extremely truth seeking. You weren't afraid to step on toes. You weren't afraid to do anything that might be seen as like, oh, you shouldn't say that to a GP or something. It was just no holds barred, complete truth seeking, everyone trying to get to the best answer. I remember a few months into the job I was like on an email thread and just like teed off on Keith or a boy, our good friend. And you know, at any other firm that might be a fireable offense or you might get, you know, tongue lashing for doing that. But at Founders Fund, it was like a pat on the back. It's like, yes. It's like that is how we do things here. It's flat. We're just trying to get to the truth. We're not trying to uphold some political bureaucracy or something like that.
- [11:16]
B
And then Keith fired you, to be fair. That is a bold take though, for a younger person in their first years. Parton. That's conviction going up against Keith in that way. If we go to Mamoon, what are the takeaways for Mamoon? I think Mamoon is just one of the greats. He's done so well with Kpop. What are the takeaways from Mamoon?
- [11:37]
A
Yeah, Mamoon. I have learned so much from Mamoon. He's a wonderful mentor. I mean, we were talking before the show, Harry, about the kindness that he showed you when you were young. And he did the same thing for me. I think the biggest thing that Mamoon has taught me this is a reflection of what he did and has done in his career. I think the two biggest things are, one, he really imparted onto me that you need to early in your career see excellence up close. And you really, and in terms of like a company, a management team, a founder, you need to see how the absolute best operate and do the job of company building. Because if you don't see that relatively early in your career, it's much, much harder to spot it in the wild. And you also don't know the bar to hold your other founders and your other management teams too. I think he does a very good job of getting younger folks that work at Kleiner Perkins or you know, even back at social media involved in the very, very best companies in those boardrooms, seeing how they operate. Because he thinks like once you've seen it and once you know the it of like what makes an A team tick, you can one, much easier to see that in the wild. And then two, you can really, you know, hold the rest of your management teams and founders that you work with to that really high standard. Mamoon more than anyone has just developed this impeccable taste around a mix of products, market and people. If you think about his huge, huge winners, whether it's Figma, glean rippling, they all have like a common through line of the, you know, it's B2B software, but it's almost like consumer like software that, that demands really high user love and engagement. And he's just developed this really, really tight understanding of where he shines and where he has a really deep understanding of companies. And then he's like, really sharpened his taste in doing that. And so I think he's definitely encouraged me and encourages people that he works with to really develop like a specific form of taste around the people and the products and the companies that you think are going to be going to be the big ones.
- [13:29]
B
He very kindly messaged me the other day and said, hey, I'd love to bring you into one of my deals, Revo and the founder's amazing and you'd be great for it. And I messaged my team just being like, hey, we're doing a deal. It's amazing. Mahmoon's bringing us in. We're done. Diligence over. And they're like, harry, no, you can't be serious. I'm like, it's B2B. It's kind of PLG. It's Mamoon. So I totally agree and get you there. Can I just ask, before we move to Benchmark, you mentioned, I love this dude. You mentioned Mary Meeker and the mental plasticity that she had around numbers and.
- [14:02]
C
What the future could be.
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B
Where were you not mentally plastic, where you should have been and what did you learn from that? And so like, an example for me would be like, I met Alex at Deal when it was 2 on 10 and I looked at paychex.com and ADP and I was like, nah, shit market, incumbents, distribution, advantage, crap investment. What a mistake. I wasn't mentally plastic and I should have been. What would yours be?
- [14:31]
A
An instance where I haven't been, where I haven't exuded neuroplasticity enough. I actually have a very recent example of this was actually the OpenAI round at $32 billion. I started my career in private equity, which I think there's a lot of strengths that come from that, but has also definitely given me some blind spots in venture that I've needed to unlearn a little bit. And when I was at Founders Fund, I was actually extremely positive on opening. I. This was. I had left Founders fund right after ChatGPT came out. And ChatGPT when it came out, was one of those moments where you're like this. Like this product is it like this is so unbelievably cool. And you could just tell that it was going to be a massive, massive product. And then the $32 billion round of OpenAI came around. When I was at Kleiner Perkins and all of A sudden I was like, oh, man, this structure seems really gnarly. You know, they're going to have to convert this somehow. It's a nonprofit. They're selling these employee units, and I think they're going to dilute the hell out of the investor base. And so I got spooked, and I missed the forest for the trees, both in terms of the structure of the company at the time and the potential future dilution, by the way. Both of those things were very valid risks that, you know, I mean, the structure at certain points have almost taken the company down, and then they have diluted a ton, given that they've had to attract all these AI researchers and all this incredible talent. But it didn't end up mattering. Like, it didn't. Like, none of that ended up mattering. What ended up mattering is that it's had the strongest and highest growth trajectory of any technology company in history, and it's probably the best and most useful product that anyone that uses it has in their pocket. And so I think Josh Kushner actually does probably the best job of this where, you know, he talks about his intuitions and, you know, he saw Spotify and just kind of knew that no matter what, he needed to invest in the company. And same with Instagram. I still need to learn to trust my intuitions more because sometimes I let silly things like that cloud my thinking.
- [16:21]
B
Josh taught me one of the most valuable lessons, actually. He taught me that if you're ever willing to do less in a deal, don't do the deal. I'm happy to take 10%. If it means giving my buddy 3%, don't do that deal. It's a bad signal. I remember Vince came on the show when he did that deal, and he said, harry, listen, if it's a trillion dollar company, we'll all make money. And we laughed at the time. And now it's like, oh, it might be a trillion dollar company.
- [16:45]
A
Three trillion, who knows?
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B
Yeah. Do you think it'll be a trillion dollar company next year?
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A
I think it'll be a trillion dollar company next year, yes. They could probably raise at the end of the year. You know, end of the year Q2, I think OpenAI could raise it a trillion dollars, no problem.
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B
Would you rather be in OpenAI at 500 or anthropic at 350?
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A
Obviously, at Kleiner Perkins, we invested in Anthropic, and we had this debate a lot internally. This is like a fun debate. You know, OpenAI are anthropic@ last, last round price, I think they represent relatively different things. I think that like, in terms of downside risk, it's hard to imagine anything that could knock ChatGPT off of its growth trajectory. Like, I don't know what could stop ChatGPT from growing at the rate that it's growing. And so I think that asset alone is just unbelievably valuable and is like completely locked in. Like there's. There's just no way that it's not going to be the most important kind of consumer destination over the next five years. And consumer app over the next five years, where everything else is still kind of hand to hand combat, is obviously encoding. I think OpenAI has actually done an incredible job with Codex and made up a bunch of progress against Anthropic that they didn't have before. And then obviously on everything on the B2B side, I think right now Anthropic probably has a bit of an edge on B2B. They've spent a lot more time and resources towards really mastering the kind of commercialization effort there. And then encoding Anthropic still with Claude Code and Sonnet and all the models that they have is probably still a little bit ahead of OpenAI. But I think given ChatGPT, I think I would probably rather do OpenAI at 500 than Anthropic at 350. But I both think that they're relatively good investments. Even today I would be thrilled with.
- [18:20]
B
Both, just in case Dario or Sam are listening. Very happy to take some shares if.
- [18:24]
A
Very happy.
- [18:25]
B
If you want to help me out here, Sam, I'll buy Brad Gerstner's if you want that one. Okay.
- [18:30]
A
Because he doesn't want me.
- [18:32]
B
Yeah, I won't ask any questions. I'll just wear a Sam Sam T shirt. What happens to cursor? Because you see Codex crush it. Actually, as you said there, Claw Code has done so well. What happens to curse? I don't know. I mean that with. No, I'm purely lost on that one.
- [18:50]
A
I think the thing that everyone has underestimated thus far is just how immense of a potential market code can be. So when you think about cursor, I think a lot of people are like, well, they're like relative market share has gone down a lot because at first it was really just them and then Claude Code came out and then Codex came out and now cognition is scaling. So instead of like, yeah, I don't know, like 80% of the market or something, maybe they have 25 to 30% of like the overall ARR. In the market today, again, what people are missing is that the market of co generation has gone something like, I don't know, over the last two and a half years. It's gone from essentially zero to probably like six or seven billion dollars of ARR. And something that we used to do at KP and Founders Fund is try to identify what are the golden categories. And a golden category is a category that as like the entire market for a single product adds a billion of net new ARR in a single year. And like if you find a golden category, you essentially, especially if you're a multi stage fund, you have to have a bet in that category because it means that it's going to produce really big outcomes. Instead of adding a billion dollars of net new this year, I think cogeneration is going to add, I don't know, four or five billion dollars of net new across every single product and service that's available for people to buy. Both on the B2B and B2C side.
- [20:07]
B
Does AI not make every category a golden category? And I don't mean that stupidly, but like customer service? Of course, tens of billions of dollars. But even if you think about much more verticalized software plays, could you not apply golden category to everything then? And should we not move a billion to 10 billion?
- [20:24]
A
I think that it does for a lot of categories. I mean it remains to be seen, right, because let's say you're doing AI for veterinarians. Maybe there's just not enough vets that have enough money to actually create a billion of net new in a given year. But I do think that, yeah, for so many categories that seemed like, you know, maybe they were kind of middling in size. A lot of what AI has been able to do, especially if it can touch something that a labor force within a category was doing before, we're seeing much, much bigger markets. As one example that I'll give you of this impact, we at KP were invested in a home services AI business that was essentially a 24 7. Like its first product is a 247 receptionist for, you know, h vac people, home services, anyone that would be a service titan customer. And we were calling customers and we're like, okay, how much do you spend on service titan? They're like, you know, 250K. And it's like, okay, well how much are you spending on this company? And they're like, you know, 250K. It's like, okay, you have seven products from Service Titan from SAS 2.0 and you have one product that's just out of beta from this new startup in voice AI. And you're spending as much on that as you are on Servicetitan, like the system of record for everything that you're doing. And they're like, yeah, well, you know, like we no longer have to staff, you know, three receptionists. We can staff two. And then we're now able to actually accept calls and book appointments 247 rather than, you know, the 9 to 4 schedule that our receptionists were sitting there. And so it's driving more revenue and more impact than even ServiceTitan was doing. You know, given that capabilities are just so much broader and real than the impacts that SaaS can have on companies.
- [22:02]
B
Are we going to be fast enemies?
- [22:05]
A
Oh, no.
- [22:05]
B
Was that Pro Book?
- [22:07]
A
No, no, this one Lee Marie led around in Avoca is the company's name.
- [22:11]
B
Oh, thank God. I lost this deal and I didn't know who I lost it to. And it's exactly that. It's exactly the same way. How much do you spend on service Titan? And then it's like the same, if not more, more, and you're like, oh my God, that is like one incredibly valuable segment then that we're covering.
- [22:27]
A
Yeah. I think it gets to something that I desperately want us to do in the venture industry, which is we need a new taxonomy for AI companies. And what I mean by that is AI app companies are meaningfully different than SaaS companies in like a dozen different ways. Yet we keep trying to shove all the metrics from these AI app companies into the frameworks that we created for SaaS.
- [22:50]
B
What metrics do we try and shove in that we shouldn't?
- [22:54]
A
If you just think about the P and l of a SaaS company, you know, Robert Smith, the CEO of the first firm that I ever worked at, Vista Equity Partners, always used to say, probably still says SaaS is great because it tastes like chicken. All the businesses are the same. And the whole thesis behind Vista was that SaaS companies are so similar that you can do the same exact things to each of them in the whole, like Vista playbook style and make them way more profitable and run a lot more efficiently. And so we're used to like, oh, like gross margins need to be 80%. Gross retention should be, you know, high 80s%. Net retention should be over 120. There should be very little capex. That's what makes a good company. And I think what you're seeing with AI app companies is a very different situation where if they're good companies with a lot of usage. You have a lot of AI inference in your COGS that you don't for normal SaaS companies. And so people are like, oh, you know, these are worse companies because they have worse gross margins. But if your average gross profit per customer can be 4 or 5x that of a normal SaaS company, then you actually have much more absolute dollars of gross profit per customer and potentially a much, much larger market than you do for SaaS companies as well. So instead of talking about gross margins and revenue multiples, I hope that it's someday we talk about gross profit multiples and we talk about absolute gross profit dollars per customer. Because if your, your relationship with a customer can be much, much broader because you're taking part of their labor budget or you're giving them more economic value than you would if you were having a SaaS company, it's just not appropriate to be grading them on a metric on like, you know, oh, do they have 80% gross margins? It's like, well, if Servicetitan has, you know, $200,000 of gross profit per customer and this other company has $500,000 of gross profit per customer, I don't care that that second company has 50% gross margins and Service Titan has 75% gross margins, it doesn't matter. So I think that's the biggest example, is that the contract sizes can be much larger even if the gross margins are lower. But I think there's several others in terms of train their own models, and so there's training costs and other various changes as well.
- [24:54]
B
So should we not help me out? Should we not place such emphasis on margins?
- [24:59]
A
I think we should not be placing that much emphasis on margins today. I think the work that we should be doing is trying to understand what does the terminal gross margin structure look like for these businesses and then also what is the absolute gross profit dollars in each of these categories that these companies can represent? Because it's just again, like, I think the folks over at Andreessen Horowitz have done a lot of good work in terms of evangelizing this idea that if you have high gross margins as an AI app company right now, it probably means that you have very little inference expense, AI inference expense in your cogs, which means no one's actually using your AI features. It's not the easiest thing to understand, like, what are these AI app gross margin profiles going to look like in five to seven years? But I think that like, at least trying to go from first principles and reason about what the, like the gross profit dollar per customer. And the gross margins of these companies in five to seven years look like that is so much more worth doing. And it's such a better intellectual exercise than trying to Compare it to SaaS, which is just a very, very different business. And it has a very different pricing and business model that isn't going to be as relevant, I think, over the next 10 years.
- [26:06]
B
It's so interesting. Rory O' Driscoll from Scale, who's basically like my adopted father, he doesn't know that. So, like, well done, you've just gained a son. But he always tells me that fundamentally, whether we make money from AI or not will be predicated on whether we see the movement from human labor budgets to AI software spend. And I think exactly to your point there, for everyone who kind of is trying to understand absolute dollars in terms of profit, your margin can be lower, but because the spend is 5x, your absolute profit is significantly higher on a per customer basis. Correct?
- [26:35]
A
Exactly. So let's think about aws, for example. Like, AWS actually don't know their exact gross margins, but they're not as high. They're not 80%. Let's say they're like 50 or 60%. I know that. Their operating margins, I think, are at about 30%. The thing about AWS is it is the largest line item for essentially any large software business versus anything else that they pay for. Like, you're paying more for AWS than you're paying for Salesforce workday, any other SaaS company, by a wide, wide margin. In the, you know, the early 2010s, you had, you know, companies doing like 100, $150 million of, of revenue, and people started to be like, what is this $30 million COGS line to Amazon Web Services? Like, what in the hell is this? And I think that's like an amazing example of. Yeah, do they, does, does AWS have lower gross margins than, you know, Adobe? Of course it does. But everyone that uses AWS and is a core customer of AWS spends multiples on AWS than they do on Adobe, which is why it's such an unbelievably large business, probably a trillion dollar business if it was spun out of Amazon. So, like that, that is the idea that I think we need to all get in our heads is like, it's not going to be every company, it's not going to be every market. But for the right AI companies in the right markets, the size of their revenue per customer is going to be so much larger than SaaS that even if they have lower gross margins. It's going to be a much, much more valuable companies going to that as well.
- [27:53]
B
What is aws? It's a commodity. And that's what I find so interesting. I was like, oh, models won't make money because they're just commodity businesses. And then you look at Google Cloud, you look at Azure, and you look at AWS and you're going, wow, maybe the best business in the world is a commodities business. To your point.
- [28:10]
A
Yeah. One of the things I've changed my mind on over the last two years, you know, there's these AI inference cloud businesses. So it's like, who's going to be the aws, gcp, Azure of the AI era. And when Core Weave was first raising in private markets, I was like, oh, my God, this is. They're reselling a commodity. You know, they're a middleman, They're a broker of compute. It's going to be low margin, yada, yada, yada. How wrong was I? The market's down a little bit, but last time I checked, it was a $60 billion public company. Nibius is a $30 billion public company. There's over $100 million of public market cap, and there's several private players that are growing astronomically as well in this AI inference cloud. So I think sometimes we can twist our mind in knots over like, oh, is the business quality okay, when you have demand like this, like you had for the initial gc, like the initial hyperscaler clouds. And I think we're seeing an even greater cohorted demand curve for AI inference. Sometimes you just got to shut your mind up and invest with the momentum.
- [29:08]
B
But it brings me to the other element, which is different than ever before. You mentioned there, the change from margin to focus on absolute gross dollars per customer. The thing that's different is growth rates. I think the thing that I'm struggling with is sustainable versus unsustainable, but also being a sucker for momentum and high numbers. How do you think about the importance of growth rate optimizing for it versus sustainability? And do we need a new taxonomy around growth rate as well?
- [29:37]
A
Again, I think the things that we need to hold into our head when we're thinking about man, you know, we have companies going 0 to 100 in less than a year. We've never seen that. But at the same time, is it easy come, easy go? You know, we had. We had early examples of this. I'm comfortable saying this because now the company has rebounded and to my knowledge, is doing really well. But I remember when people were talking about Jasper, like the two AI investments that started the wave were Stability AI and Jasper AI and, and, well, stability, different story. But Jasper, you know, I think it went 0 to 100 very, very quickly, but then actually started shrinking. And it was because it was sort of easy come, easy go with the revenue. And they hadn't built enough scaffolding and they hadn't built enough like actual true value in order to like really sustain the customer relationships they had and sustain their growth rates. So the way I've actually been thinking about this, especially as it relates to, because I think the other aspect of this is that what is the risk for a lot of these app layer companies and who are they at danger against? It's the labs. Like, the labs are creating apps, they're creating more value via the models and they're giving them directly to users. And oftentimes as an app company, you need to be doing better than what $20 a month can get you from ChatGPT. And so I think that the way to think about it is that for a lot of these categories, the labs set the baseline in terms of customer experience. They're your competition at your base layer. And so whatever you can get from ChatGPT or whatever you can get from anything directly from the labs apps themselves, you need to be sufficiently differentiated from that because they're happy to charge 20 or $200 per month per user. And a lot of these AI companies want to charge a lot more than that in order to have a sustainable business equation and be able to actually do B2B distribution. So I think when you think about Jasper, at first, the issue that they ran into people when GPT4 came out, they started being like, wow, the outputs I'm getting from Jasper, Jasper are kind of the same that I'm getting for 20amonth from OpenAI. Like, I'm not going to pay, you know, however, much more for Jasper. I'm just going to use ChatGPT. But I think what they've done now is build sufficiently differentiated workflow software and been able to like tie in LLMs through the life cycle of how their users work and operate in a way that is sufficiently differentiated and gives them more of a moat. Like, I don't think the sources of moats have changed from SaaS to AI necessarily. Like, the seven powers are still the seven powers. All of the same ways to build differentiation are there. The stakes are just much higher because the growth rates are much higher and the labs are just getting so much better. So Quickly, especially at delivering applications.
- [32:04]
B
How do you feel about people who say the moats have changed? The moat that was technology is now fundamentally distribution in terms of access to customers and data. And access to data, and it shifted from technology to those two. Do you disagree with that or do.
- [32:20]
A
You agree with that? I definitely disagree with that. I think the moat is still fundamentally in technology, not in distribution. I think distribution obviously gives you the right to build differentiated technology, but I think one of the huge learnings that we've had as an industry is how damn hard it is to build good AI products. A good AI product is so much different to build than a good SaaS product. Like you need different people. There's so many different parts of a good pipeline in terms of where do you bring in LLMs, how do you improve them, how does it fit within a general workflow? It's not just bringing in the OpenAI API and using it within the text box or something. It's actually extremely nuanced and complex to build an exceptional AI product and one that's going to outshine the lab's applications themselves. So I still think it's technology. It might just be different in terms of like, maybe it's not a tech mode in terms of having like, you know, a unique database that no one's ever built before that's more efficient for X, Y and Z use cases. But it's really a talent scarcity and like a talent tech moat where there's just not that many people that know how to build these products and build off of these models in a super intelligent, tasteful way. Which is why you're also seeing, you know, people go for billion dollar contracts and make LeBron money. As an AI researcher, how do you.
- [33:35]
B
At benchmark think about that? I struggled with this one too. I mean My fund is 400 million. Benchmark, I believe is 500 to 600. I mean it's always kind of. You guys never really announce funds in the way that most people do because it's probably mostly just your money at this stage. My question to you is when you see like I don't mean to pick on them, but like a Mira Marathi or a Periodic Labs great and very talented people, but these are 300 million rounds, $2 billion rounds. Do you just accept that is not a world that you play in?
- [34:04]
A
This kind of gets to the question that I think some people have. I don't think you've had it, Harry. You've been very kind to us. But I think some people have asked the question, did benchmark, Ms. AI did benchmark, you know, not get in on the AI wave because they're, you know, not in one of the labs or they weren't in mirrors, they weren't in thinking machines or any of these investments. I'm a big believer in Conway's law, and Conway's law is this programming concept that when it's super dumbed down for people like us. Harry says you ship your org. Yeah, you ship your org chart or the product you ship looks like your organizational structure. I'm a huge believer in that. For venture capital firms as well, I think you ship your fund size or you invest your fund size and your team structure. If you have a $7 billion fund and you have 50 people, you definitively need to get in on these mega rounds. It is the only way that you can put, you know, a billion dollars of capital at work productively in a single shot. And if you don't and it ends up being successful, you are now left in the dust where all of your mega fund brethren got those returns, and now you're benchmarked poorly against them because you missed one of those things. For a firm like benchmark, it might not make any sense at all to invest in a $5 billion financing in a lab, even though those are good investments because of our fund structure and because of our lean size. But our lean size and our smaller fund size also allows us to do other things that we think could even generate better returns out of our last fund. Our five best investments in that last fund today, held at LRP last round price, are about a 60x. We have two 30xs and we have two 20xs. Since ChatGPT was released, there isn't an OpenAI round that touches that return multiple and that money on money multiple. And we have five of them. And each of them, I think, have a fair amount of upside even from here today, or maybe a lot of upside, even hear from today. I think you have to kind of choose the game that you're going to play, and it's based on how big your fund is and how many people you have on your investment team. But I think there's so many different ways that we can play the game and generate maybe even better money on money returns than folks that are investing in the labs. Even though I do think the labs have obviously been amazing investments, Your fund.
- [36:06]
B
Size dictates the problem that you're solving for. And I think when you said there about missing the OpenAI at 30 transparently, all I thought was that's what, like a 15x on a blunt multiple to where it is today, but with dilution, 12x, but with actual dilution, you're looking more like a 6 to 8x, which don't get me wrong, is fantastic. But when you do a comparison to your Lagoras, to your Lang chains, to your Sierras, to your macaws, to your firework, we're focused on cash.
- [36:35]
A
On cash, 100%. The lab investments are amazing as well. But I think if we're going to stay small, the only way we're going to impress LPs is by having incredible cash on cash returns.
- [36:46]
B
Do you worry you need them to stay relevant? I agree with you on LPs, I agree on cash on cash, but just relevancy. With founders and with community, do you worry that you need them to stay relevant?
- [36:56]
A
I think it's a question that we need to constantly be asking ourselves. And I think if we ever find that our network access, the close relationships we have and the people we have access to is slipping or we're not getting access to the right people or the right network nodes, I think it's something that we always need to be sharp on and revisiting. But I think if you think about kind of like the cultural touchstone founders of today's AI era, is there anyone more than Brett Taylor who represents this wave of AI applications? He's like the godfather of AI apps right now. And when you think about these really cracked young teams in AI, who do people look up to more than Brendan at Merkur and what they've done on the AI infrastructure side, at least thus far, even with our strategy, even with the trade offs that mean that we can't invest in every single good round, we've still been able to attract and partner with and I think build really great relationships with a lot of the founders that people look up to in this AI wave. And I think our network thus far has been exceptional. But I do think it's an ongoing question because if all there is left is these billion dollar raises in order to build relationships with these people, then that's, that's an ongoing question.
- [38:02]
B
If that happens, then all of us will either work for the North Korean army or for Andreessen Horowitz, one of the other. So, you know, that's rather.
- [38:10]
A
They're one and the same to me, Harry. They're one of the same to me.
- [38:15]
B
Mark and Ben, he said it, he.
- [38:17]
A
Said it wasn't me.
- [38:20]
B
You said the word slip and then you said about macaw. Now I'm In Macaw a little bit after you guys, sadly.
- [38:27]
C
But I did see the article which.
- [38:29]
B
Said about the ownership that benchmark had in McCor being obviously much less than the traditional and I think it was about 10%, give or take. I'm not asking specifics about company, I'm just intrigued. How do you think about discipline around ownership in a new AI world where everyone's is trending down?
- [38:47]
A
Yeah, when I think about Benchmarks, North Stars, what we really care about in our investment strategy and this relates to the ownership that we get in our investments or everyone else gets in their investments, we have two North Stars really that we think about. We want to be the highest ROI and closest partner to the founders that we partner with. We want to be their most meaningful VC and partner that they have from the moment that we partner with them until the company no longer exists, like it can go public or still be on the board until the company no longer is a going concern. And we want to generate the highest money on money returns that any of our LPs have in their venture portfolio. But that's basically it. As the asset class evolves, there are ways to really serve those two North Stars without having to necessarily get 20% ownership every single time. We're all believers. I think you're a believer. We're certainly a believer that the outcomes are much, much, much larger in today's technology landscape than they were 10 years ago, 15 years ago. There's more bytes at potential $100 billion or trillion dollar companies. There's just so many bites at the apple in terms of how you can both be a really meaningful partner to the founders and two generate really, really exceptional returns. So in the Mercour case, yes, we didn't get high teens or 20% ownership. But I think if you talk to the Merkur folks and who their most impactful VC partner has been, I think they would say Benchmark and I think that's going to generate unbelievable returns for LPs. And it's one of the those ones that's, you know, you can do the math on, on what the money on money return has been thus far from our ownership stake. And so I, I think sometimes people confuse the inputs for the outputs at Benchmark where it's like, oh, like they have to have 20% ownership and they only want to invest at 100 post and all these things. And I think that's, that couldn't be further from the truth. We really have those two North Stars and whatever the asset class allows for in terms of the Relationships that we build and how we can deliver the best for LPs and our founders. That is what we're serving to and that's what we're optimizing for, not some vanilla percentage ownership number. Ironically, I think if you polled any of our founders and said, you know, do you regret the amount that the percentage ownership that you gave to Benchmark, I don't think you'd get a single one of them to say, no, we gave Benchmark too much. I think that's one of the really special things about the history of the partnership. It's my third week, so obviously I've contributed nothing. Nothing to that. I'm just speaking to the amazing work that all of our current and historical GPs have done for the platform. But I also do think that even when we get, and we still often do get really high ownership stakes, I don't think a single founder regrets that partnership ever.
- [41:11]
B
It seems, despite many years in venture, you still need a lesson from me, which is, regardless of what you did, it was all credit to you for the brilliance that happened before. Okay, it was me. Yeah, I remember doing ebay back in the day.
- [41:26]
C
Me and Pierre, we were hanging.
- [41:28]
B
We basically co founded the. The business together.
- [41:31]
A
So.
- [41:31]
B
Good.
- [41:32]
A
Yeah, Yeah, I do need to work on that.
- [41:34]
B
You said about, we can take this out if you want to. I pry and you can take out one of your old partners. Delian is quite vocal about Benchmark. I mean, it's kind of the popcorn gif, you know, it is. And you say about being best partner. I think if you can answer it, it's helpful because the dalliance doesn't help. Where he says, well, you just fire founders continuously. Is that not slightly incongruous, being the firm that fires founders and also your best partner?
- [42:04]
A
I'll start with Delian's media strategy. Delian. And, you know, love Delian. He's a close buddy of mine, so I don't think he'll mind me saying this because he certainly busts my balls more than. More than enough. Delian has always found an amazing kind of media and Twitter strategy, which is go find, you know, someone with like, you know, a stalwart brand or, like, go find the biggest person on the playground and go punch him in the face. People love it and it gets a lot of likes and it gets a lot of clicks and it helps raise your kind of profile and it almost like elevates you to their positioning. He's done it to Sequoia an immense amount. He's done it to Andreessen over the years and we have not been spared the clickbait Delian tweets either. No, I think, I mean, obviously every story has an immense amount of nuance and what happens between a board and a founder and a management team, there's just an immense amount that goes into every single one of those decision decisions. I think, you know, times also completely change, like in the 90s and early aughts. Like if you read about or hear about the Google investment, you know, Kleiner and Sequoia do the Google investment and immediately start searching for a professional CEO. So like it used to be, like, it used to be the absolute norm that it's like, it's not even like, oh, we're going to push the founders out. It's like, no, you invest and then you all together go look to recruit a CEO. 2025 is immensely different than 2000. It's immensely different than 2010. It's even immensely different than 2015. And just the relationship between boards and founders have changed. The relationships between venture firms and management teams and companies have changed a lot. I think it's for the better, obviously. I spent a fair amount of time of my career at Founders Fund. I love the idea of never firing founders and having them lead their companies from the moment you partner until the IPO and beyond. But at the end of the day, they're also like, I also am a believer in basic governance. I'm also a believer in, like, if you do end up investing in someone who breaks the law or someone that's, you know, cross ethical lines, it is your responsibility as a board member to also potentially take remediations and action on behalf of all of the shareholders, all of the employees and the company. Like, if you take a board seat like we do, and you do have governance, you ultimately do have at least basic ethical and moral responsibilities. And I think it's actually a convenience for Delian and some of the Founders Fund folks to absolve themselves of that weight and that responsibility just by being like, oh, it's not part of our, it's not part of our thing. But I think, you know, it's almost out of, out of laziness sometimes more than it is duty that they find to founders.
- [44:29]
B
You know, you said you give me some bangers, I also give myself spicy ones. But I think we're actually too kind on the flip side where we now do not adhere to our fiduciary responsibility because we do not want to lose NPS so much. I'm on a company now. I'M invested in where the board is deliberately obfuscating their fiduciary responsibility just to preserve founder NPS in case they say something bad. They are not looking after the cap table just because they do not want to piss the CEO off. That is a deliberate obfuscation from your responsibilities of protecting shareholders and doing what's best for them.
- [45:05]
A
100% I completely agree. And I also think the best founders, they don't want sycophants in the boardroom. Like they don't want GPT4O in the boardroom telling them that everything that they do, they walk on water and that they do nothing wrong. Like they actually want other adults in the room that are going to push them, that are going to spar with them and that are going to make the company better.
- [45:24]
B
Can I ask you, have you said about kind of multiple bytes at the Apple? When we look at Benchmark over the years, you know Phantom did airtable Series C. I think Nagako was series C. LangChain was a seed. To what extent will you push the partnership now to expand the boundaries of what we call an A and what benchmark does to do more broad bites.
- [45:47]
A
At the Cherry or Apple Historically again, going back to those North Stars that we talk about, when you think about the benchmark investment strategy, it's helpful to marry the North Stars that we talked about. In terms of every investment needs to be potentially absolutely astronomical money on money returns for LPs and we want to be the most meaningful partner to our founders. There's a lot of different ways to do that. And so you marry those North Stars with the personal investing style of each of the GPS. Like each of us is 25% of benchmark and we work really well together and we're a super tight knit team but each of us has our own styles. And so even if Eric tends to love getting in right at inception and be the first check in and be, you know, really, really in the primordial soup phase of a startup, it doesn't mean that myself or Chetan or Peter are always going to operate exactly at that stage. We all have our particular preferences. Peter does an amazing job following his founder conviction. He doesn't think about stages like when he finds a Howie, when he finds a Brett, when he finds any of these founders, that is what he lets him, that's what guides him and he's like I'm going to find a way to become the most meaningful partner to this founder and I'm going to find a way for the investment to make them A lot of money for our LPs. That is the mindset that we all have. And historically, I've done more growth, like I focused more on Series B and beyond than I focused on early stage. So will I do more kind of Series A, B or whatever we call it these days than Inception seed investing? Especially at first, probably. But again, we're guided by those North Stars and finding founders that we really resonate with. And then typically we're able to find ways to make it work on the back end and for our investments to generate exceptional returns and all those things. So unlike, you know, a huge mega fund that is like, we have our Series A partners, we have our Series B partners, we have our Series C partners. They do fintech, they do healthcare, they do blah, blah, blah. Like, we don't think about those things at all. We really just think about our North Stars realizing more and more that there's just so many different ways that you can have 10x20x30x returns.
- [47:44]
B
I spoke to one of your former colleagues and they said EV is a phenomenal growth investor, but he's a growth investor. And when I think about what matters at different stages, you know, for me, in the early stages it's people and in the later stages it's market actually sizing depth and just how big something can be. You know, we recently did our Wallix late at 4 billion.
- [48:05]
A
Incredible.
- [48:05]
B
Why? Incredible? But why? Because like, dude, fucking B2B payments. It's a big market. We got a lot more room to run. How do you think about that shift earlier? Are you nervous about making it and what changes in what matters in your mind?
- [48:20]
A
Yeah, I'll be vulnerable with you, Harry, and say that. This was when I was talking, this was a dinner I was having with Eric the Shreya on our team. And I was having a moment of insecurity when I was talking to him about the role of being a GPA benchmark and saying, hey, I've mostly done growth. And he was like, dude, Bill Gurley was a public markets analyst before, before he came to Benchmark. Like, you certainly are not going to be the most, you know, the most off the wall hire that Benchmark has made. That's actually more par for the course for Benchmark. And I think also when you look at, like, who do you think are the amazing investors today? I think they transcend stage. Like, if you look at Pat Grady, does Pat Grady think of himself as a growth investor or does Pat Grady think of himself as just an amazing investor? Maybe he's too Humble. He's a pretty humble guy. So maybe he doesn't think about himself as an amazing investor at all. But I look at what Pat does and I'm like, he finds incredible founders and investments that he thinks have an immense amount of upside and he goes and partners with those founders. And so I wouldn't say that I'm an amazing investor yet. I don't have the track record yet to say that I am. But like, that is my North Star and that is my goal and I'm going to work my ass off to do that where I'm just going to find. I think I've been able to tune my intuition and even though I've used it to execute on growth stage investing, I think if you look at a lot of, even the people that we think are growth stage investor, they're doing earlier stage companies now and doing a lot of different stages at the same time.
- [49:39]
B
I thought Pat just did the deals his wife did. I'm just kidding.
- [49:45]
A
Harvey was. He said. He said it, not me.
- [49:47]
B
Pat, he said it, dude, I've known him for 10 years.
- [49:51]
A
I've said this shit. You can get away.
- [49:53]
B
I've said it for years. And this is why I think he's just like, I've never met him, Harry, no idea. A thing that does change, obviously is price. And it does matter at different stages. How do you think about your own relationship to price?
- [50:06]
A
I think almost by starting my career as a growth investor, it actually really helps me. The first investment that I did at Kleiner Perkins when, when I came back in 2022 was SpaceX at $150 billion. And at the time it's like, oh my God, like $150 billion entry price, like the absolute number numbers. Can we really make a good return on this investment? And having to go through the process of saying, hey, let's not focus on just some large absolute figure. Like let's look at the tam, let's look at their competitive position in their market, let's look at what happens if this goes right and let's look at the probability of it going right and who could potentially knock them off their perch to make it not go right. And when you actually zoomed back and said, hey, let's just like take a few zeros off of every single number. The tam, the valuation, the revenue, everything. If you were to like look at it as a vanilla widget company and just reduce, like, you know, took two orders of magnitude off of every number, you'd be like, this is an absolute no brainer investment with a 10x upside case. Doing later stage investing can actually really help you think about price even at the earlier stage, because it really makes you think about, okay, like I'm going to ignore what feels like a large entry price relative to market. Like if you're in a market where everyone's like, oh, the series A market's 100 posts. And like if you do something at 200 posts you're an idiot because that's like 2x more expensive, then you miss rippling at 250. You know the famous Series A that Mamoon did where everyone's like, this guy's out of his mind. He just paid 250 for a series A company that barely has any revenue. And obviously you miss Parker's excellence. You miss the TAM that he's going after, you miss the product sequencing, the differentiation that he's going to build and you miss the exceptional team that he had built. And so I think if you can always try to isolate, like, hey, I'm not going to care about what's going on in the market. I'm going to care about what matters for an investment and how much upside I think there is in a vacuum. I think that matters a lot more. And it's something that you can actually get if you start your career in growth.
- [51:51]
B
Do you remember when Andrew Reed did Figma and they were 4 million in ARR and he did it at 400 and everyone was like, this guy is 100x. What nuts. Now I'm like one of the first.
- [52:03]
A
100X deals I think in SaaS and people are like 100x ARR, what the hell? Obviously it ended up being 30, 40x. Unbelievable investment.
- [52:10]
B
Do you outcome scenario plan though? Because you said there about market analysis and trying to do top down versus bottoms up.
- [52:17]
C
How do you think about that?
- [52:18]
B
And do you not worry that it can mislead you in the wrong direction?
- [52:21]
A
This is a lesson I think I learned from Mary mostly. It's one of my most important frameworks. You should understand what the base case or the base rate future of the company looks like. So if you are an equity analyst and this was your hundredth company that you were doing like a little forward model for and you weren't paying that much attention and you're just like, okay, just triple, tripled. So it's going to double, double, double or like whatever. If you just said like, hey, this is what the market thinks is sort of like the baseline of what this company should do, it's actually extremely helpful to lay that all out and visualize that. So I don't say like, oh, this is the bull case, this is the base case and this is the bear case. But I lay out like, what are people underwriting to? Because let's say at the growth stage, people are underwriting, do like a 3 to 5x. What does that look like on paper? And then how does that jive with my mental framing of how important this company is going to be for its customers, for its market, for the US Economy? In some cases, when you have a really, really strong intuition about a company in the middle of an inflection that's about to absolutely explode, you look at the numbers that people are underwriting to, to get to their 3-5x and you say, this company's going to absolutely smoke these projections. It happens very rarely, but it's really, really nice because it really gives you the amount of conviction when you look and say, oh, this is just like everyone's going to underestimate this thing. And I think the other reason why models are not useful beyond that simple framing is that every successful investment, you just feel stupid. Like if you were to model Figma's growth, you know, everyone would make fun of you. You'd be like, dude, come on. Like you're just trying to get this deal done. You know, why would you model it growing for this fast, for this long, this profitably, like it's never happened in SaaS. Like you're crazy or you're just like doing the IC a disservice. And so I think beyond being like a yardstick to test your conviction, models aren't that useful. But for that they're really, really good.
- [54:03]
B
I always remember Ernie from carvart and coming on and being like the amount of investors, that would be like the biggest car Showroom is like $300 million market cap. So like, this is a bad business. And I always think, like market comps is such a dangerous one to rotate your mind around when investing 100% or.
- [54:22]
A
You know, Figma with designers. And I think David George, maybe it was on this show or another, you know, talked about how he, you know, under, under misunderstood and understated the tam of Figma because he was, you know, he went back to the team and said, well, look at how many designers there are in the world. If you just do the P times Q, the price time, the quantity of designers, you don't get that big of a business. And obviously Figma then ended up penetrating a lot more different roles within a company beyond designers, people, product Market Rank.
- [54:47]
B
1 through 3 in order of priority for you.
- [54:50]
A
The way you said it honestly, people, product and market, the people define everything else. They are the upstream engine that makes everything go. They're the most important piece. Two, I think the product that the people build just tell you so much about. Also the people, like it's, it's the greatest evidence of the quality of the people is the product that they build and then market. Third, obviously I am a believer that like the market you're in ends up defining the size and then the founder, you know, determines how, how like what percent of that size you can, you can get in your exit. But I just think it's the most fungible. Like I don't think you can turn a non exceptional person into an exceptional person. I don't think you can take a team that can't build a good product and make them a team that can build a good product. But you can change markets, especially early on in a company's life, like most of the amazing companies and exit stories had some pivot along the road whether you're talking about Slack or any of these others. So I truly think that because it's the most fungible market is the least important of those three things you said.
- [55:49]
B
They're the change of markets. It was on this show where Doug Leone said venture capital has transitioned from a high margin boutique community to a low margin commoditized industry. Do you agree with him in that statement?
- [56:05]
A
I think Doug might have gotten that idea from me. I'm half kidding, but I wrote this piece back in 2021. I think it's the reason why we first DM'd. It was called Playing Different Games. Ostensibly the piece was about the rise of Tiger, but what the piece was really about was the rise of a firm level strategy that surrounded itself around increasing investment velocity as the core strategy. And so the idea being that you could make more money as a firm and as a GP if you invested a lot more money per year, even if you thought the forward returns were going to be lower on average per investment. And the idea was like Tiger was really the first one to take this idea and really, really run with it and make it, you know, they raised $15 billion or whatever they did in 2021. John Curtis basically deployed it all over that 18 month period. And at the very bottom, this is the ironic part of that piece, at the very bottom I said venture capital is going to bifurcate and on one end you're going to have the Tiger model, which is high capital Velocity a lot of money out of the door every single year. Low Touch, good prices, like giving, giving founders really good prices. And on the other end, who did I have? I had Benchmark ironically. And like that is going to be like the craft that is going to be High Touch. It's going to be the best signal that you can get if you're a founder. And they're going to be very, very involved. And then in the middle I was like, we have the J.C. penney funds, which is like the dead zone. And I think like the crazy thing to me is like what ha. What's happened over the last four years, Harry? How many firms have moved towards the Tiger side of the spectrum? Like Tiger died and we got six or seven more Tigers out of like in the last four years. And obviously a lot of these firms are running different strategies. You know, Thrive and Founders Fund doing extremely concentrated investments in really high quality companies. You have the mega funds like Lightspeed and GC doing their thing. It's a lot of different, you know, flavors of Capital Velocity as a North Star. But there are six to eight firms now doing Capital Velocity, Investment Velocity as their North Star. And that was one of the reasons why I was really confident in High Conviction in joining Benchmark. Because if you look how many of those tier one brands have moved more towards the benchmark side of the scale, there's basically none.
- [58:05]
B
Can I just push you? Do you think they are doing Capital Velocity as their North Star? I think Josh would ardently push back on that from Thrive and I don't even think you could apply it to LightSpeed and GC. I think they're solving for large checks, which is why they have to be in these mega companies because they need to deploy 500 million in some cases.
- [58:23]
C
But I don't feel like they're solving.
- [58:25]
B
For Velocity in the same way that Tiger were.
- [58:27]
A
I would push back. Well, there's two things. So I think obviously there's different sub segments of this. Now let's take the actual mega fund. The people that I think are most following this strategy. If you were to say, well our GC or LightSpeed or some of these mega funds is the strategy Investment Velocity as a North Star. To answer that question, I would have you go talk to the principals, the junior partners and the associates at those firms. You interview 10 of those people and you tell me that Capital Velocity is not the North Star of those firms, I will cede victory to you, Harry. I think when you actually look at what's going on at the ground floor, it doesn't matter what Ravi Herman are saying. When you actually look at what's going on at the people actually going and doing these investments, they feel it. They feel that they need to get money out that door and that's the only way that they're getting promoted up those organizations. So I think it's very, very real. On the Thrive side, I agree with you. I think that Josh would resent that characterization and it was probably too blunt of a characterization. But again, I think subconsciously still as a firm, it's hard to care about something that's not your main product. And when you're writing billion dollar checks, that is your main product, like it's, that's what's going to make you all the money. If you put $3 billion in OpenAI and it's going to turn into $12 billion, it just subconsciously, whether it's conscious or not, it is unbelievably hard to then go and be like, we're also going to be the best series A firm and we care just as much about series A because why would you. Because 99 or not, like 95% of the profit that you're going to make and the money in your pocket is going to come from the billion dollars you put in DataBricks or the $3 billion you put in OpenAI or any of those things that have ended up being your main product. You just can't focus on everything and give it your all. And I think so, even though it's less conscious for those firms like founders run Thrive, it has become their main product and their main focus.
- [60:06]
B
Subconsciously, if we accept that people then often move to the and they're going to do worse. Ha ha ha. Like, you know, we accept a lower rate of return because they have, you know, the Norwegian Tree pension fund wants 4% a year and so that's what they're going for.
- [60:21]
C
And then you actually look at outcome.
- [60:23]
B
Scenarios and outcome sizes of, you know, OpenAI, which will be a trillion dollar company company next year, Anthropic, which will definitely be a 600, $700 billion company cursor, which hits a billion in error insanely fast. Outcomes are so much larger than we ever anticipated.
- [60:40]
C
I think they will make a huge.
- [60:41]
B
Amount of money because the outcome sizes have continuously expanded. Do you agree?
- [60:47]
A
Oh yeah. They're all going to make an immense amount of money. But again, let's change the framework from absolute dollars to what you're giving each stakeholder of the three legs of the, of the venture stool. So Venture has three stakeholders. You have your LPs, you have your founders, and you have each other as gps within a firm. I don't think as Ravi or Hamont or even Ben and Mark at this point. I don't think that they can go to LPs, one of those legs of the stool and say, hey, this, this basket of funds that we're making you invest pari passu across, we're going to get you 5x net on that. I don't think they can say that or they at least can't say that with a straight face. And if you look at the recent return data, I think it suggests that. So I think they'll be able to make an immense amount of money on an absolute basis. But I think a lot of these LPs are in the business to make, to make high money on money returns. Like they have PE for the low return stuff and they probably get better liquidity from pe. They're here for the high money on money returns. And this is one of the reasons why I'm extremely excited about Benchmark's competitive position in today's market. Because we can go to LPs, we can say, hey, we're shooting for higher than 5x net. We have the historical track record to back it up and we have the fund sizes to back it up as well. I mean, you had miles from Carnegie Mellon come on here and do the awesome math and the very clear math of hey, do you know how hard it is to return forex net on $8 billion, $10 billion? It is immensely hard and it defies the laws of physics. So I think there's a difference between are they going to make a ton of money and are they going to produce the returns that LPs really want this asset class to produce? Two very, very different things. But for now, the rubber won't meet the road because as you mentioned, there's just so much global demand from LPs for exposure to private technology and they are happy to take lower returns. And so I don't think there's any end in sight. But I think on a relative basis between all of these different constituents and all these different gps, there's a huge, huge delta and a huge differentiation between who can actually produce ventral like returns.
- [62:35]
B
Tiger. I think Tiger will do much better than anyone anticipated. When you look at their positions in scale OpenAI and the protection that they're going to get from a load of lick prefs that they do actually have, meaning a lot of them will get 1x plus a little bit maybe. Do you think I'm wrong in being too optimistic or do you think actually the whole ecosystem shit on them a little bit too early?
- [62:58]
A
I completely agree. I think Tiger's going to end up much better than anyone thought they were going to end up. I jokingly texted some of my friends and I was like justice for John Curtis. I actually think everyone put him as kind of this like pariah of like the personification of the, of the excesses of 2021. But again like his strategy might have proven prudent and the correct strategy all along because they got really big stakes in databricks. They invested in OpenAI very, very early. I think they have a large position in OpenAI. They actually have large positions in a lot of these amazing companies that could continue to compound 5x more. They'll probably, you know, benefit from the liquidation preference and the beauty of having, you know, preferred stock for a lot of the things that don't work in the fullness of time. I mean I'm sure it's not going to be the best portfolio that any LPs ever gotten, but I definitely don't think it's going to be like a money incinerating fund by any means. And I actually think it might end up being pretty okay if you know, once DataBricks is a 400 $500 billion company and OpenAI is a multi trillion dollar company. It is hilarious. I do think people gave them too much of a hard time and I do think they might end up being okay.
- [64:00]
B
I love that hashtag. I'm sure John will listen to this and be like yes. Thanks guys. When we were chatting about multi stage funds before and going back and forth on email, you said about how it sucks to be in a mega fund. Why does it suck to be in a mega fund? Ev because from the outside it looks from like building a firm, the idea of having mega fees, mega offices, Fiji water in unlimited supply and more EAs than you have investors, it seems pretty good. Can you help me out here, dude?
- [64:33]
A
Okay, so yeah, maybe I should caveat by saying all on a relative basis. These people definitely aren't going to the coal mines and laboring all day under the hot sun or something. But yeah, I think, and I know I have so many friends at these funds and some of them are probably going to kill me for this part of the conversation. But something that I always tell I've mentored a lot of people that are either coming out of private equity or thinking about moving firms in venture growth. And one of the first things I say to them, I just think about the day to day that I know exists in a lot of these mega funds. And if you think about it, if there's 50 investors, if you come in and you're like the 23rd partner at like, I don't know, like iconic or like one of these places, what companies do you get to cover? That's the first problem is like, you end up getting like a very small sliver of the overall market because so many people have already like laid claim and are the point person on the very best companies with the very best founders. And so you end up like being focused on this local maxima where you're like, okay, I have like 30 pretty good companies that I am the point person on the relationship. I also really need to do investments because that's how people get promoted here. I really need to like get a couple of these in the portfolio. And to me, sometimes it just feels like a little bit of like, it just feels like a different job than like the craft of venture capital where you're almost playing the lottery, where you're like, okay, I have these 30 names that I own. I'm going to try to do two of them and then if one of them hits and is a huge success, then I'm going to get like tenure and I'll like get to be a GP and then I'll get more coverage and then everything will be okay. You know, it feels almost like a little bit more like investment banking or like a large private equity firm than it does like what people think of when they think of like being at a venture capital firm, which is like, meet really interesting founders, build genuine relationships with them, and only do the very, very best investments in partnerships. And I just think it's really gotten away with that and I think it's inevitable. And it's again to that Conway's law point of venture capital firms. It's just based on the fund sizes and the team structures of these places.
- [66:24]
B
And if they get fed up of the private chefs and the Aesop soap in the bathrooms, then they can always go and build their own fund and toil away and do the painful hard yards. In which case I wish them well. Exactly. I have to say I do agree with you there. I do have to ask you, you mentioned there about kind of doing those two deals out of the 30. The first deal is really hard, dude. How do you think about your first deal at benchmark? You can fall on two sides. Just get it out. It may not be your Best. But it's kind of like the first shack. Just get it done.
- [66:59]
A
You promised me spicy, Harry, and you delivered. You delivered.
- [67:03]
B
Or it's like, you know what? I'm gonna wait until I find the perfect company and only when I find the perfect company am I gonna commit to it. Which side do you sit on?
- [67:15]
A
I won't lie to you, Harry. The weight of being a benchmark GP exists. Like, I definitely feel it. Like, it's. You're like, wow. Like you know the people that have walked these halls. Bill Gurley, Mitch Laski, Matt Kohler. Incredible people with incredible track records. And you feel a lot of pressure to like live up to the history of this place and the history of the brand. I think I got really, really good advice. I won't name the partner so no one can trace back to what company they're talking about. But one of the partners coming in was like, look, there's going to be nothing better for you than if your first investment sucks. Because once you do one and it fails and you realize it's not the end of the world and like life goes on and like LP still love us and like you're not fired, then you feel really comfortable and you start getting into a really, really good rhythm. Whereas like, if your first one's like pretty good or like looks really good, you can then feel even more pressure on the second one. So there is something beautiful in having your first be a failure that. It doesn't mean that I'm going to be looking for a failure out of my first investment, but it was really relieving and it was amazing advice to get that. Look, it's all okay. And if anything failing actually can help you feel more relaxed as you go up to bat the next time.
- [68:23]
B
Just do one of Delian's then.
- [68:26]
A
Exactly. Yeah, I'll do like a, I'll do like a, like a Swedish satellite antenna company or something that Delian did and then, then I'll be guaranteed for, for a zero.
- [68:35]
B
Having said that, obviously. Dalian, I'm joking. Delian's track is pretty fucking good. Like you look at Vought, I mean, I don't think he gets enough credit for the investor that he is as well. And like Sword in Portugal, where you're like, really? That's a non obvious pick. And like, wow, what a business.
- [68:53]
A
The thing I always give Delian crap for is that he does have an incredible track, but a lot of it is software. And so he loves to like, he loves to shit on software companies and people that invest in Software and all these things. And I'm like, dude, you sourced the seed of Ramp. Khosla owns an ungodly amount of Sword Health, which is an amazing company and like, yes, you know, obviously Incubated Vardo, which is a great company as well, and all these things. But I'm like, a lot of your track record is in software, but no, honestly, I think a lot of people at Founders Fund have very underrated track records. I think Matthias van Tiernen, I think he's the most underrated venture capitalist that exists today. He's so quiet. He's never online boasting about himself or anything. But Dalar App, Trade Republic.
- [69:30]
B
Why? I met him when he was in London and we had dinner and he was doing the Trade Republic deal. Then why do you say he's the most underrated?
- [69:38]
A
I don't think a lot of people know about him. You know, he's not online.
- [69:41]
B
Once he got to his name though, Trade Republic.
- [69:43]
A
So Trade Republic Dolar app, which I'm sure, you know, enter down in Latin America. He's an instrumental. You know, the growth team over there is quite small. You know, you got Napoleon, you got Matthias, and you got a few other like Amin and a few other people. And he's just, he's just played a pretty big role in a lot of the, the really good growth investments as well. So I just think, like, for someone who also is ostensibly a growth investor, he's done a ton of really good.
- [70:04]
B
Early stage things and he's humble and nice. He's like one of those perfect kids at school.
- [70:08]
A
You're like, oh, God, I don't know about nice. Some people don't think he's very nice, but he's a sweetie at heart.
- [70:15]
B
Ouch. Do you know what? I spoke to Henry from Stored before and he said, you got to ask, what's the most ridiculous story you remember from the 2021 times?
- [70:26]
A
Oh my gosh. I mean, there were so many, just absolutely absurd ones. Again, I was at Founders Fund, so we were spending a fair amount of time in Miami. I remember distinctly, I think it might have been like the third Miami Tech week or something. And I think it was like December of 21 or maybe January of 22, when it was pretty clear that like the bubble was bursting from COVID and like equity valuations were starting to get slashed, like 30, 40% in public markets. And we were just doing like these. There's like, we had some like, very, very decadent party. I think like Vanilla Ice was performing or something and like, like we're in Miami. There's all these crypto people. I was just like, oh my God. And I was sitting around and I was like, this reminds me exactly of the scene in the Dark Knight Rises where like, Anne Hathaway is dancing with Bruce Wayne and they're at this, like, fancy party and she's like, I don't know how you could think that you guys could, you know, do this glamorous, like, decadent stuff while like, Gotham is burning. And I was like, wow, we are at that party today. Like, Gotham is burning. Like it's about to come to us. But for this time, you know, this is like the last decadent thing that we're going to be doing. And I just feel like 2020, it was all like that. There was just so many just ridiculous things where I look back and it's like, why did we ever think either one, this investment was a good idea or two, why were we doing these very decadent things in Miami? It just seems ridiculous in hindsight.
- [71:37]
B
I am so here for a Dark Knight reference, by the way, so I love that scene. Well done, dude. Love it. Final one before we do a quick fire, which is just like, you can think that Gotham is burning today, actually in a lot of ways. But when you look at the state of the world and you can also look and go, we're so early in the adoption and inflection of AI that this is just the start. And I hold these two opposing thoughts in my mind and I'm kind of stuck which one to adopt. How do you feel?
- [72:07]
A
I feel the same. I think today, relative to call it the dot com boom and bust. I think if you really think deep down about what happened in that era, let's say you did the Amazon Series A, there was a point in time four years later where it had IPO'd and then it was down 80% from IPO. But if you had held to today, you know, you. And I forget if the Amazon A was, you know, 40 posts or whatever it was, but you went from 40 posts to, you know, multiple trillions of dollars in value. You know, today is very similar in that there's going to be a ton of companies that are pump fakes that do end up going to zero or that go 90 down 90%. But I think it's really important to position yourself so that you can survive the inevitable crash on the other side. And if you end up in these really incredible companies that end up still enduring and defining the next 20 to the 30 years of technology, you're going to be paid so many, like, in, in, like in so many multiples of what you would get in a normal cycle. And so I think we think. And we stay up all night thinking, thinking about like, well, what is going to be the Amazon and the Google and the Microsoft of this era. And then also I think it goes to our strategy where, like, let's constrain our fund sizes, let's be careful about what we do so that we don't get too over our skis where we can easily weather a crash and LPs aren't going to go fleeing once there's a crash because we've, we've been very careful with our capital and we haven't incinerated billions of dollars or something like that.
- [73:27]
B
I think Benchmark could invest in Elizabeth Holmes doing Theranos take two and you'd still get LPs queuing out the door thinking that Fenton has seen something that no one else has seen.
- [73:39]
A
Maybe we should. Maybe we should. She's still in jail, but whenever she comes out. Maybe we should.
- [73:44]
B
It's about being contrarian and. Right. The terrifying thing is she has like, quote tweeted me, agreeing with me more times than I like. And I'm always like, this is a bad sign.
- [73:54]
A
You're like waiting on a good. Apparently that's not her. Or at least I saw something on Twitter where someone's impersonating her is what. Is what I saw. Apparently she doesn't actually have, have, have access. So maybe it's one of your superfans.
- [74:04]
B
Reassuring. If so, because I'm not. I'm. I'm always like, shit, delete, tweet, delete, tweet. I could talk to you all day. I want to do a quick fire round. So I say a short statement, you give me your immediate thoughts. What have you changed your mind on most in the last 12 months?
- [74:19]
A
I think honestly, the, the quality of the AI cloud business model. Again, I was very negative. It negative on it when, like Core Weave was first coming up, I was like, oh, this is reselling a commodity. I actually think there's a lot of interesting things that people are doing and the demand for AI inference is just so astronomical that at least for now and for the next few years, I think it's going to overcome all business quality and business equation concerns. I think at some point Core Weave and all these things will probably go down like 70%. But obviously I thought that back when it was raising at $3 billion and now it's a $60 billion public company. Where the investors have been able to get liquidity. So I was definitely wrong.
- [74:53]
B
Which pumped company today will have the steepest fall, do you think?
- [74:58]
A
Pumped company as in like super hyped? Yeah, I mean we're investors in cursor. I am not a believer in some of the companies that have raised a ton of money and have not released a product or like I'm a huge believer in like you got to get developers hands on the product. So I think there's a couple companies that have raised like billions of dollars and they're like, oh, we're going to build the best thing ever. But they don't actually have products that are lot of developers are using. That is going to be a rude awakening because you have like AI products get better via usage oftentimes if you have the right environments. It's like cloud code Codex Kersher. The companies in the apps with the highest amounts of usage are going to improve the fastest and leave everybody in the dust.
- [75:34]
B
Tell me you've got Bond, you've got Founders Fund, you've got kp, all fantastic firms, but one firm where you've got to put your money for the highest cash on cash. Which one do you go?
- [75:45]
A
Maybe Founders Fund. Just because they have a very unique ability to incubate companies. And so I think when you think about like Anduril, like the fund that Anduril is in, it's just going to be like such an ungodly return on that capital. And so I think it's become a really, really competitive market. And the only way that you can like fend off how hard it is to buy equity is to sell equity or produce equity. And the way you produce equity is by incubating companies. And every few funds or every five to 10 years, they've incubated an unbelievable company. Obviously Scott Nolan over there is the most recent to do it and so I think that's just a way to get differentiated returns that are hard to produce from anyone else.
- [76:20]
B
Phenomenal. And when you look back, just no one has so reliably had such good performing funds at scale them and index. Crazy. Yeah, unbelievable there. Okay, totally get you. Can you take me to the moment where you said in your head, yeah, I'm going to do benchmark? Was it a dinner? Was it a coffee? Was it a. When did you go yeah, I think.
- [76:40]
A
I said yeah to benchmark when I was 22. Entering the industry, honestly, you know, like you enter the industry. You read Eboys, I'm reading all of Bill Gurley's blog Posts like, it is a mythical place and it is one that it's one like, you enter the industry as, like a young investor and you think, if I really work my ass off and I get pretty lucky, maybe one day I'll be able to compete for a seat there. So when it comes true and they, you know, give you the envelope with the offer on it, I don't know, it's almost like a childhood fantasy of joining the Yankees or something. It's super surreal. So obviously the people matter most, and that was really important during the recruiting process was I felt unbelievable alignment and just really a level of closeness with Peter, Eric and Chathan. But beyond that, I think the firm itself, it's just one of these mythical seats that you dream about from the day that you enter the asset class.
- [77:26]
B
Is that Real Madrid and going to the Bernabeu?
- [77:29]
A
You tell me I played FIFA in high school, but I don't. Yeah, like playing for real, like, you know, yeah, it's watching Ronaldo and you're like, oh, my God, like, I could go play for real one day.
- [77:37]
B
And it's like, we all chat shit that I'm so happy at Chelsea. I love being at Man U. And then Ronaldo gets the Real Madrid.
- [77:43]
C
Offer and you're like, yeah, Old Trafford's not so great.
- [77:46]
B
Not so great, is it?
- [77:47]
A
Not as. Not as sunny as Madrid.
- [77:50]
B
Tell me, what's the biggest miss for you, dude? And how did that change your mindset?
- [77:54]
A
Biggest miss has to be OpenAI at 32, it was kind of a hard to fill around, I think, like, obviously they did it, but it was. It was very non obvious at the time. And it was just one of those ones that is just so unbelievably painful because you missed the forest for the trees. You let these, like, the structure thing and the dilution thing trick you out of investing in what is maybe going to be the largest tech company of all time. And also just like being in that ecosystem, like, it's just such an unbelievable group of people that I think even if it was just an okay return, you'd still want to be involved with Brad and Sam and all the people over there that have liked to find a lot of what the AI industry is today. And, yeah, so that one hurts to this day.
- [78:31]
B
What do you think the biggest threat is to benchmark being successful in the next five years?
- [78:37]
A
I think the thing that is most dangerous and the biggest risk to benchmark not being successful over the next two decades is stasis. We need to be dynamic. We need to always be evolving with the asset class while staying true to our North Stars. I am very much a believer that we don't have to leave our North Stars or bastardize our true north in order to continue to be involved with the very, very best companies. But at the end of the day, being involved with the very, very best companies is the currency by which we all live in this asset class. And that has to be the most important thing. And if there's ever a situation where we're letting our North Stars or we're letting something else wag the tail, wag the dog and the dog being getting involved with the very, very best founders building the best companies, that's when we need to re evaluate our strategy and what we're doing.
- [79:23]
B
Penultimate one, are you ready to lose all of your friends in your new partnership? Who's the best picker in Benchmark?
- [79:31]
A
I think the I'll do a data driven one which I think like, I think just Peter's. I mean honestly I think Eric is the most underrated picker. I think when you look at just some of the like he's just done some like really low key things that have ended up being like unbelievable. Like he'll have Cerebras which you know, will IPO at some point in the future. That's going to be an unbelievable. He has a lot of these sneaky absolute bangers. But I think if you go back and look at just like okay percent of series A's that ended up being generational companies, I mean Peter also has the advantage of being in the game for 20 plus years, but it's gotta be Peter.
- [80:00]
B
I also think Peter is possibly the greatest salesman I've ever met. His ability to manipulate language to sell his position is really beautiful.
- [80:09]
A
I went in my first pitch with him my first week and like my jaw was on the floor more than the founder. I was like, I have so much to learn from this guy. I'm like, I've never seen someone with a like that practices the craft of like infinite EQ and hospitality and just wordcraft like he does. It's unbelievable to witness.
- [80:27]
B
You weren't like, wait a minute, this is just like being in a room with Delian's more of a blunt instrument. I would say, dude, he's gonna fucking either hate me or love me for this show. I have no idea.
- [80:40]
A
Probably mix of both.
- [80:41]
B
Final one for you. I like optimism. What are you most excited about for the next 10 years?
- [80:46]
A
I think over the next 10 years the only thing that's ever made me less of a capitalist than I am, is realizing that capitalism is really, really good at optimizing things and making them more efficient. And when the laser beam of capitalism moved from cars and TVs and electric goods and making them cheaper and moved to the minds of people, I think it actually has had a lot of negative consequences. When social media had its rise, the thing it was optimizing for was how do we get people to glue their faces to the screen for as long as possible. That's been actually like a, like a significant negative and probably the only negative that technology's had on society thus far. But I think, like, when we look at what's happening in AI and the way that it's going to be able to, like Peter Thiel always talks about how the most important thing to keeping our society harmonious and functional is growth. Because as soon as this pie stops growing, things get a lot worse and people get a lot worse to each other because it's zero sum. I think, unfortunately you're seeing a fair amount of that over where you live, Harry. And I think when you think about the determinants of GDP growth being basically population and then GDP per capita and how much the birth rate is slowing, I think AI is going to be unbelievably good at continuing GDP growth. And I think continuing GDP growth and just growth of the economy and continuing growing the pie and having the middle class grow and having just everyone feel more and more prosperous over time is the most single important variable in continuing a harmonious, functional society. And I think it's going to do that in spades over the next 10 years.
- [82:10]
B
You know, Ev, honestly, I love doing the show, but I've done it for 10, 11 years. Not every show is as brilliant as this by any means. And it's shows like this which make me go like this is why I still love doing what I do. And so thank you for being so brilliant. Seriously, this was so much fun and I just couldn't be more thrilled with this show.
- [82:30]
A
Thank you, Harry. It's been, it's been so awesome just, just to hang with you and next time we'll do a pint in London next time I'm out there.
- [82:37]
C
But before we leave you today, are you drowning in AI tools? ChatGPT for writing, notion for docs, Gmail for email, Slack for comms, and you're constantly copy pasting between them all, losing context and losing time. This is the a AI productivity tax and it's killing your output at 20 VC. We're all about speed of execution and Superhuman is the AI productivity suite that gives you superpowers everywhere you work. With the intelligence of Grammarly, mail and coda built in, you can get things done faster and collaborate seamlessly. Finally, AI that works where you work, however you work. Superhuman gets you From D Day 1 with zero learning curve and it's personalized to sound like you at your best, not like everyone else using generic AI. Get AI that works where you work. Unlock your Superhuman potential. Learn more@superhuman.com podcast that's superhuman.com podcast and speaking of tools that give you an edge, that's exactly what AlphaSense does for decision making. As an investor, I'm always on the lookout for tools that really transform how I work. Tools that don't just save time, but fundamentally change how I uncover insights. That's exactly what AlphaSense does. With the acquisition of Tagus, AlphaSense is now the ultimate research platform built for professionals who need insights they can trust fast. I've used Teagus before for company deep dives right here on the podcast. It's been an incredible resource for expert insights, but now with AlphaSense leading the way, it combines those insights with premium content, top broker research and cutting edge generative AI. The result applies platform that works like a supercharged junior analyst, delivering trusted insights and analysis on demand. AlphaSense has completely reimagined fundamental research, helping you uncover opportunities from perspectives you didn't even know how they existed. It's faster, it's smarter, and it's built to give you the edge in every decision you make to any VC listeners. Don't miss your chance to try AlphaSense for free. Visit AlphaSense.com 20 to unlock your trial. That's AlphaSense.com forward/20 and if Alpha Sense helps you spot the winners, Angellist helps you hire them. If you're listening to 20 VC, you know we have a really freaking high bar. Well, Angellist is the modern platform used by the best in class venture funds where over 40% of top endowments and banks LPs. Their customers include a top five venture firm, 20VC and they now have, check this out, a $171 billion of assets on the platform. They combine an all in one software platform with a dedicated service team that moves as fast as you do. One manager said this awesome quote angellist feels like an extension of my fund. Another said angellist gives me total peace of mind. The attention to detail, lightning fast response time and just real sense of ownership from the team are exactly what I need to stop worrying about back office ops. So if you're starting a new fund, don't be a mortgage moron. Just use Angelist. They're incredible. Head over to angellist.com 2zerovc to learn more.