17x Midas List VC Navin Chaddha on The 100x AI Opportunity

Navin Chaddha, Managing Partner of Mayfield, has guided more than 80 companies to positive outcomes. During his venture capital career, Navin has invested in over 60 companies, of which 18 have gone public and 27 have been acquired. Creating $120B+ in equity value and over 40,000 jobs. Navin has been named to the Forbes Midas List 17 times (Top 5 in 2020, 2022, 2023, 2024), becoming one of the most respected voices in venture capital. Mayfield has $3B+ in AUM, 120 IPOs, and 225+ acquisitions. In this episode of Sourcery, we cover: Why AI is a 100x opportunity vs. past tech shifts The collaborative intelligence stack from semiconductors to AI teammates The difference between real vs. vibe revenue Valuations, hype cycles, and Mayfield’s investment philosophy 5 Key Takeaways AI is a 100x wave – Unlike the PC, web, cloud, or mobile eras, AI combines conversational interfaces and reasoning/action, unlocking a truly global expansion of creators. Collaborative intelligence is the future – Humans + AI “teammates” will create a $3–6T market opportunity by augmenting knowledge workers Valuations are overheated – Billion-dollar seed rounds are unsustainable; Mayfield stays disciplined by aligning on founder–VC win-wins Revenue quality matters – Durable businesses need real customers, high margins, & repeatability; “vibe revenue” isn’t enough Entrepreneur traits beat ideas – Authenticity, teamwork, EQ, mission-orientation, & persistence are the most reliable signals for long-term success 1. Navin Chaddha: https://www.linkedin.com/in/navinchaddha/ 2. Molly O’Shea: ⁠https://x.com/MollySOShea⁠ https://x.com/MollySOShea%E2%81%A0 3. Sourcery: ⁠https://x.com/sourceryvc⁠ https://x.com/sourceryvc%E2%81%A0 Brought to you by: • Brex https://brex.com/sourcery—The modern finance platform, combining the world’s smartest corporate card with integrated expense management, banking, bill pay, & travel. As a Sourcery Listener you get: 75,000 points after spending $3,000 on Brex card(s), white-glove onboarding, $5,000 in AWS credits, $2,500 in OpenAI credits, & access to $180k+ in SaaS discounts. On top of $500 toward Brex travel, $300 in cashback, plus exclusive perks (like billboards..) visit → https://brex.com/sourcery • Turing https://turing.com/sourcery—Turing delivers top-tier talent, data, and tools to help AI labs improve model performance—and enables enterprises to turn those models into powerful, production-ready systems. Visit: https://turing.com/sourcery • Carta http://carta.com/sourcery—Carta connects founders, investors, and limited partners through software purpose-built for private capital. Trusted by 65,000+ companies in 160+ countries, Carta’s platform of software & services lays the groundwork so you can build, invest, and scale with confidence. Visit: https://carta.com/sourcery • Kalshi https://kalshi.com/sourcery—The largest prediction market and the only legal platform in the US where people can trade directly on the outcomes of future events: https://kalshi.com/sourcery Follow Sourcery for the latest updates! https://www.sourcery.vc/ Chapters: (00:00) Navin’s 17x Midas List Journey (02:06) What It Takes to Build a Winning Company (03:00) Why AI Is a 100x Opportunity (04:00) Conversational Interfaces & Machines That Act (06:35) The Rise of the “Vibe Era” (06:53) AI Supercycle: Early Days, High Valuations (09:23) Billion-Dollar Seed Rounds & Valuation Concerns (10:45) Mayfield’s Investment Philosophy & Win-Win Model (13:42) AI Premiums in Fundraising (Carta & NVCA Data) (18:06) Building the Collaborative Intelligence Stack (20:40) Where Value Accrues Across Hardware, Models, Apps (22:50) Business Models: Subscription → Consumption Based (24:19) The Race to $100M Revenue: Hardware, Labs, Agents (31:47) Real vs. Vibe Revenue (Margins, Repeatability) (39:08) Founder Traits: Authenticity, EQ, Team Orientation

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:00Molly O'Shea?

  You've been honored to be on the Midas list. Not once, not twice, not three times, but seventeen times.

• 0:06Speaker 01

  AI to me is democratization of intelligence. According to NVCA, sixty-seven percent of all dollars went into AI companies. So my advice to entrepreneurs is, you better adopt this technology and do something with it. When there are billion-dollar seed rounds, my head spins and I can't make head or tail sense of it. Companies come and they say, oh, I'm depressed. I said, what happened? Oh, my valuation is only three hundred million at the seed. I go, the spend on knowledge workers globally is thirty trillion. And AI will do ten to twenty percent of that. So three to six trillion-dollar opportunity over the next five to seven years. The companies won't go zero to hundred. In the first year, if they go one to ten, they're doing pretty well.

• 0:48Speaker 01

  If you only go one to three, maybe you're like median, average. For the first time in our lives, machines understand our language. So we don't need to learn program.

• 0:59Molly O'Shea?

  Are you vibe coding?

• 1:00Speaker 01

  I am, actually, in a few ways. To me, knowledge, expertise is gonna get democratized. So my advice to every human, including myself, is consume this thing before it consumes you.

• 1:21Molly O'Shea?

  Levine, welcome to Sorcery.

• 1:23Speaker 01

  Thank you for having me.

• 1:24Molly O'Shea?

  Thank you for having me.

• 1:26Speaker 01

  It's great. We have been talking for a while. I'm glad, like, we're doing this together.

• 1:31Molly O'Shea?

  I know, this is so fun, and this is on the day of the Divit List.

• 1:35Speaker 01

  That's true.

• 1:36Molly O'Shea?

  The Mayfield Divit List.

• 1:37Speaker 01

  Divit List, yeah, yeah, yeah.

• 1:40Molly O'Shea?

  We have a lot to cover today, but to start, we have to address something.

• 1:46Speaker 01

  Let's do that.

• 1:47Molly O'Shea?

  You have been involved in some of the most, if not all of the most consequential shifts in technology. And you've been honored to be on the Midas list. Not once, not twice, not three times, but seventeen times.

• 2:02Speaker 01

  Yeah, just been lucky, working with amazing people.

• 2:06Molly O'Shea?

  What does it take to build a winning company?

• 2:09Speaker 01

  I think it Mayfield and my perspective always is, it always starts and ends with people. So we try to bet on the right people who are visionaries, very mission oriented, can go through any wall, are team players and have high EQ. Lot of people have IQ, but they really have high EQ and are secure in their skin and will want to win the right way along with their team at any cost. So it's always about the people, starts there, ends there. So as long as you pick the right people, it doesn't matter what their initial starting point is, they'll go win at the end. And I'm an optimist, pick great people, great things happen.

• 2:54Molly O'Shea?

  What does that mean for the AI industry today for early-stage companies?

• 3:00Speaker 01

  Yeah, I think it still remains the same, right? Old is gold. At the end, venture entrepreneurship is an apprenticeship-based business. And in the AI era, overall, it's a hundred X opportunity. I've been lucky to be involved in the web era, the mobile, the cloud, the social, the not-so-good eras. And then the AI, I think those eras were a ten X opportunity. This is a hundred X opportunity. So the kind of success that'll get created won't be just ten billion-dollar companies. There'll be many hundred-billion-dollar companies. But again, what will matter the most is the people who are creating these companies.

• 3:45Speaker 01

  That's not going to change, at least for Mayfield and me, at the stage we invest, which is inception and ideation stage primarily.

• 3:55Molly O'Shea?

  What makes us a hundred times opportunity?

• 3:58Speaker 01

  Yeah. So what I would say is, if I look at the PC era, it was creating an environment where it was a ten X disruption, where you brought computing to every desktop. You move it to the web, now we could consume information. You move to the cloud, it was a backend innovation. Mobile, a frontend innovation. With AI, the reason it is hundred X, there are two things which are happening. First, the interface in the way we interact with machines is becoming conversational. For the first time. In our lives, not only mine, but everybody's, including my parents,

• 4:42Speaker 01

  machines understand our language. So we don't need to learn programming. So it's an expansion, which is we can talk to machines and ask them to do things in our natural language. The second thing is with the cost of compute and the innovation in AI technology, GPUs, machines can now think, they can reason, they can plan, but what's difference is they can take action. And that's another 10x force. So if you combine the disruption on the front end, where machines understand human language, and you multiply that with what's possible on the backend,

• 5:25Speaker 01

  with intelligence getting democratized, it's 100x force. And as an example, there are 30 million developers in the world today who know how to program. Using AI, I think everybody, 8 billion people in the world will be programmers because they'll vibe code. That's why this is 100x opportunity. It's really 100x because 100x times 30 million is 3 billion. So there will be 3 billion creators in this world. And it's a very exciting time, a very, very exciting time.

• 5:59Molly O'Shea?

  Are you vibe coding?

• 6:00Speaker 01

  I am, actually, not, uh, in a few ways. One, trying to use vibe code with prompts, my daily work. And second, in the free time, if you're a VC, you have to eat your own dog food. So I'm creating fun apps, fun websites. And I started as a developer back in the mid 90s where I created my first company. So it's good. Now I had forgotten everything, now I can remember everything. You have to, right? Like you have to eat your own dog food to understand what's happening. And it's fun, it's fun.

• 6:35Molly O'Shea?

  It's called a vibe for a reason.

• 6:37Speaker 01

  Yeah, we're in the vibe era. Like I called it the vibe economy. Not only will be vibe coding, it will be vibe ops. It's really the vibe era. It's not the AI era. It's the vibe era.

• 6:48Molly O'Shea?

  Rebrand.

• 6:49Speaker 01

  Rebrand. That's what VCs and marketeers do well.

• 6:53Molly O'Shea?

  Some people call it also the AI super cycle. Where do you think we are in the evolution of this super cycle?

• 7:03Speaker 01

  Yeah, I would say we are still early on in the super cycle. But the valuations are really high in some of the spaces. And this is the standard hype curve. When new waves come, expectations are ahead of reality. But if I go out four, five, 10 years out, it'll be a reality. The same thing happened with the internet. Where things just astronomically were overvalued in three, four years. But the difference today is the reason it's going to be 100x bigger. Because when the internet happened, people didn't have connectivity.

• 7:45Speaker 01

  Today, 7 billion, 8 billion people are on the internet using mobile or their PCs. So you can have things grow to 100 million monthly active users in one month, in two months, in three months. It took 10 years for Amazon to get to that point. Versus when TikTok happened, people were talking about, hey, nine months, six months to get that. Now people talk about like a week to get there. So I think the reality is it's early days, but some of the things have already taken off. Whether it was with ChatGPT, but let's look at vibe coding. Companies are doing 100 million in revenue, 200 million in revenues.

• 8:30Speaker 01

  They're going to be doing 10 billion in revenues. We'll blink and that's what they will be. But on the other side, if I look at enterprises, still early. Lot of hype. But very few enterprises can actually do anything with this technology. And there are all kinds of reports. Some reports say it's working. Every enterprise, sixty percent of the enterprises are using this tech. And then the MIT report comes and says ninety-five percent of it fails. So you just don't know. There's like camps, there's the left wing, there's the right wing. We have to, but I think I'm centered in the middle. And I believe this is marathon, company building,

• 9:16Speaker 01

  deployment and adoption of technology. Yeah, maybe in round one right now. The best is yet to come. Besides valuations.

• 9:25Molly O'Shea?

  Besides valuations?

• 9:26Speaker 01

  They're overhyped in some of the spaces. But hey.

• 9:30Molly O'Shea?

  At what point is it concerning to you?

• 9:32Speaker 01

  It's concerning even today. Because I believe companies should be built with the right fundamentals. And valuations should increase as they make progress. When there are billion dollar seed rounds, my head spins and it's still spinning. I can't make head or tail sense of it, right? Like, how many billion dollar companies are there that have gone public in the last ten years? Right? Not that many. People are doing seed rounds. Now they tell me, companies come and they say, oh, I'm depressed. I said, what happened? Oh, my valuation is only three hundred million at the seed. I go like. I think it's like problem of riches. That's what these entrepreneurs have. So I think like, it's already high.

• 10:17Speaker 01

  I'm concerned. I'm concerned that everything may not stay up. So we could go from all these hyped up companies, some will keep growing. But maybe that will be one percent, two percent, three percent of the hyped companies. But a lot of them are making their lives really, really hard.

• 10:39Molly O'Shea?

  How do you and the team at Mayfield value companies? What's the strategy there?

• 10:45Speaker 01

  I would say at Mayfield, since we are investing at the ideation stage, we are looking for a win-win with the entrepreneur. Clearly, from where we were investing in the cloud era or the mobile era, valuations are dramatically up. But for us, a win-win with an entrepreneur is, hey, everybody needs to make money. We respect their business model. They need to respect our business model, which is VCs need to have margin in their business. So we need to have, with small checks, enough ownership for the risk we are taking. And luckily, to succeed, there are enough entrepreneurs who believe in that philosophy that we can still survive and thrive. So that's what we are trying to do. There's no science.

• 11:30Speaker 01

  It's really an art. You can't be on every cap table. We can't invest in every company. Every founder may not work with us, but can we find seven to eight inception stage companies a year where we have meaningful positions? And we can work with these entrepreneurs to help create leaders of tomorrow? They are hard. So we try to stay away from people who have unrealistic expectations. And why? Why get into business with people? And it's vice versa. My standard answer to people is if they ask for something, sorry, we don't have such a product, right? Like, I love In-N-Out, but I have their veggie burger.

• 12:14Speaker 01

  Now, people will say In-N-Out only sells one kind of burger. So what is this veggie burger? You throw the beef patty away and you have the rest of the stuff, right? So if you go to In-N-Out and say, I need a chicken burger, they don't have it. You come to Mayfield and say, at seed stage, I'm raising a billion dollars. Sorry, we don't serve that. So one needs to know, even as a venture capital firm, what's their North Star? What is their strategy? And stick to it. So that's what we try to do. And be happy with what you're doing.

• 12:44Molly O'Shea?

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• 13:27Molly O'Shea?

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• 13:46Molly O'Shea?

  So Karta has some data on this. AI-native companies have a much faster and easier time raising capital than non-AI companies. So much so that Series A, they now raised 2.5% faster. This has increased. And then also, AI companies are getting a premium.

• 14:09Speaker 01

  They are.

• 14:09Molly O'Shea?

  So this valuation pump is really happening, and it's affecting seed to Series A, most significantly at the Series A. Companies in the first half of 2025 saw a 30.9% higher valuation and secured 33% more capital than any other companies. How do you think about that in the grand scheme of marketing?

• 14:35Speaker 01

  I think it's just the reality. If you're not going to be an AI-native company, like, where do you go? It's like saying, "I'm not a tech company." Every company in the world has to use tech. So AI, to me, is the great equalizer. It's democratization of intelligence. So that's what consumers want. That's what businesses want. I would say, go even further in the first half. According to NVCA, 67% of all dollars went into AI companies. I think it's going to be 90% in a year. And it's going to be really hard for companies. It won't be just thirty-three percent.

• 15:17Speaker 01

  Companies are going to take ten X the time to raise money if they are not an AI native company. So my advice to entrepreneurs is, right, like, figure out how, like, the way people build on clouds, how companies were mobile first, how do you use this technology and endorse it? You don't need to be a foundational model company that exists. You don't need to be in Nvidia. But if your customers are looking for intelligent applications, they want to drink and have the spill, which is called intelligence on demand, you need to integrate it in your products. It's not about cost cutting, that the big companies are figuring out, how do I use AI to improve productivity?

• 16:03Speaker 01

  You're a startup. You're supposed to be ten X ahead of where the incumbent and legacy vendors are. So you better adopt this technology and do something with it. So I think it's only going to get worse for non-AI companies.

• 16:17Molly O'Shea?

  If everybody's an AI company, then what, like, where's the value?

• 16:22Speaker 01

  I think the value...

• 16:23Molly O'Shea?

  How do you find the fake companies?

• 16:25Speaker 01

  There's going to be a lot of them, right? So I think to me, AI is just going to be an ingredient technology. It's going to be, I build a product. It's like saying, hey, I use electricity. But now the thing is, we consume electricity. Every company consume electricity. What do you do with it? So now, using AI as a commodity, as a utility, you have to go solve real problem for your end users, which can be consumers or they can be businesses. So you have to figure out, what do your customers care about? And provide them painkillers, not vitamins. If you do that

• 17:10Speaker 01

  and you can rise above the noise, they will buy your product. And if they buy your product, either they'll pay or some advertiser

• 17:20Speaker 01

  for those eyeballs will pay money to you. So I think to me, that's where the world will head once this infrastructure, what I call the cognitive plumbing layers of the hardware and the models settle.

• 17:37Speaker 01

  Applied AI companies are going to be on the rise. So that's what I mean, that you have to just take it as a given that your product needs to have AI as an ingredient in it and then build on top of it.

• 17:52Molly O'Shea?

  So let's talk about the full stack

• 17:54Speaker 01

  Yep.

• 17:54Molly O'Shea?

  of technology. You invest end to end semiconductors to applications and software. Could you lay out all of those layers and how do they work together?

• 18:06Speaker 01

  Absolutely. So first and foremost, I would say, as I mentioned earlier, this is the intelligence era. So our belief is humans and AI will work together and take us into this new era of collaborative intelligence. And in this era, AI will enable humans to get to super humans level. And what I mean by that is if AI can help augment me and free up time so that I can go do things which I really want to do. So they can amplify my capability. AI can amplify my capabilities, give me time to do creative things or do things I could never do.

• 18:50Speaker 01

  So to enable that, we believe there is a collaborative intelligence stack which has been created, which starts from the hardware layer, which is the semiconductors. The next layer up is the brain, which is the model companies. Once you have models and you have hardware, this gets packaged by a cloud service provider or by an inference company. You need to bring your own data, so the data layer becomes important. Once you have data on top of models, on top of hardware, now you need middleware and tooling to do something with this plumbing layer. Once you have that, you build intelligent applications.

• 19:36Speaker 01

  And then finally, the most exciting layer of this stack is what we call AI teammates, which are built on agentic technologies. And what are they? They're digital companions that work with humans to take us to super humans level. And that market is a massive market because the spend on knowledge workers globally is thirty trillion. And AI will do ten to twenty percent of the work. Of what humans do to offload them. That's a three to six trillion dollar opportunity over the next five to seven years. And that's what we are seeing with Vibe coding agents, with AI-enabled customer support reps that,

• 20:20Speaker 01

  hey, AI will be your digital companion. So this market is just expanding. The same way Airbnb, Uber, Lyft, DoorDash expanded markets. That's what AI is doing at this AI teammates layer and their opportunities up and down the stack in this era.

• 20:40Molly O'Shea?

  And that's where you think the most value will accrue?

• 20:43Speaker 01

  I think right now the value is at the infrastructure layers. So the hardware companies are and systems companies are the most valuable. So if you look at Nvidia for four and a half trillion dollars, then you have a company which most people don't know about called Broadcom, which makes all the networking chip and other chips along with AMD. It's a 1.6 trillion dollar company. Then you look at systems companies, Apple, hardware company. You look at cloud providers, Google, Microsoft, AWS, they're all two, three, four trillion dollar companies.

• 21:24Speaker 01

  And then there is Meta, which is a consumer company, but most of the value right now is in hardware and systems companies or cloud providers. Next layer up, models is where the value is accretive. You have a 500 billion dollar company in OpenAI. You have a 170 billion dollar company in Anthropic and many 10 billion dollar companies. So that's where the value today is. But looking forward, the value will move up. It always happens. The roads are built first, the infrastructure, the plumbing layers. But then cars come. That's where these teammates and intelligent apps will be.

• 22:07Speaker 01

  So today, for the next five years, that's where the spend will be. People are just building roads. Once the roads are built, you have to do something with it. So that's where these AI teammates and intelligent app companies are going to get created. And that's how you're going to consume all this infrastructure which is getting built, right?

• 22:29Speaker 01

  So the equivalent of chat G P T or the equivalent of cursor is going to be created for every consumer intent and every business user. So we're just at the start of that, just at the start. But today, value for the next three, four years is at the infrastructure layer. If I take 10 years out, this will be built, value will go up the stack.

• 22:50Molly O'Shea?

  How are business models different in this era versus the SaaS era?

• 22:55Speaker 01

  So I would say at the applications and at the teammates layer, SaaS took us from the era of perpetual license, which was enterprise software to subscription, where you charge per user per month.

• 23:15Speaker 01

  Now we are moving into an era of consumption-based pricing or outcome-based pricing. I don't pay you per month, I pay you for what I use. And that's where this era is going, where I don't charge per user per month. I charge for the activity I do for you. I charge for the task I complete for you. So that's where the business model is changing. And that's a very important component of these A I native companies. They have to move from subscription to consumption-based pricing models.

• 23:52Molly O'Shea?

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• 24:28Molly O'Shea?

  The race to 100 Hundred million, I was gonna say billion, because we're just throwing out big numbers left and right, it could be a trillion.

• 24:35Speaker 01

  It could be a trillion too.

• 24:36Molly O'Shea?

  But the race to a hundred million in revenue has become a new benchmark. Somehow, some way, it's how fast can we get to a hundred million in revenue? I think one thing that could be interesting to to break this down is the different types of companies that are reaching that hundred million in revenue, because they're very specific.

• 24:53Speaker 01

  Yes.

• 24:54Molly O'Shea?

  Could you explain the different types of companies that are doing that? It's like AI research labs, but then it's also lovable. So like, what is the difference there?

• 25:01Speaker 01

  So I think there are, actually, let's decipher it based on the stack. So there are companies in the hardware layer, which are going zero to billion, not even hundred, and I have a few in my portfolio.

• 25:14Molly O'Shea?

  Okay.

• 25:15Speaker 01

  Which hasn't even announced they exist. So I have a company which is in the optical interconnect space. If you have GPUs, you need to connect them, not on copper, but on optics. This company went, remains in stealth. It's fourteen months old, from zero to three billion dollars. Because the spend is massive, massive, right? And they only have a small portion of the market. Their competitors in China, just the top two players are worth, one is worth seventy billion, the other is worth fifty billion. And when they get this contract, maybe they have ten percent of the order, five percent of the order.

• 25:58Speaker 01

  So hardware companies, what we are seeing with Nvidia, if you hit a jackpot, don't compete with Nvidia. But everything around it, power, cooling, networking, you can ramp even faster, because the orders are big, the hyperscaler are your customers. The second area is the AI research labs, which have also scaled, not to hundred, billions of dollars in revenue. I think the third area where the revenue ramp is happening is coding agents, which is cursor and lovable. I can tell you, everything else is slow. Which is to get to zero to hundred, it ain't happening in one year. So it's hardware, models, and these coding ones are the killer apps.

• 26:44Speaker 01

  The rest of the stuff goes, uh, and these are like, I don't know what the word for these are, like, these are like imaginative creatures. They never existed. They're not unicorns. You now have to come up today with a new name. I don't know what it is, but we'll figure it out. Or we'll figure it out in the comments, right? Like, uh, but the remaining companies are, I would say, going from one to ten. In the past, SaaS companies, if you did one to three million, you used to feel good. That's it. Now people say that's it. So I think

• 27:22Speaker 01

  teammate companies and application companies will go like one to ten, not one to hundred. But there could be categories, the equivalent of cursor and lovable, which have a product let go strategy, more a bottoms up strategy. Maybe it will happen in I T ops, maybe it's happening in legal, where it's like chat G P T or lovable individuals can use it. The moment you go top down and there is a human involved on the other side who has to write the check, you know what happens, right? Like basically it's slow.

• 28:04Speaker 01

  So that's why it's not that the market isn't there. The bottom leg will be humans. When you go to an enterprise company and say, buy my product, the security person raises their hand, this is wrong with this thing. Governance people wake up, privacy people wake up, then procurement people wake up. So there you can't ramp. So it's these bottom up companies at the app layer which can ramp. So could there be more? Could there be a teammate for accountants where accountants individually buy? A teammate for tax preparers, a teammate for salespeople. So if you can have a bottoms up motion, then you can go one to hundred.

• 28:45Speaker 01

  But if you have to go sell to a buyer, this friction, this paperwork, to sign documents, even though they're in the cloud doc you sign, but still humans are signed. So the companies won't go zero to hundred. In the first year, if they go one to ten, they're doing pretty well. If you only go one, two, three,

• 29:09Speaker 01

  maybe you're like median, average. One, two, three used to be right in the metrics. You're a great company, one, three, 10. I think now it's one, 10, 50. For even the normal companies, the equivalent of SaaS, that's expected of you. But if you hit a category like lovable or like cursor, yeah, one to 100 is expected of you. And if you're a hardware company, you have to think in two, three year in billions. And I think probably most of the people haven't figured that out. That's what is happening in hardware companies. They're ramping even faster than lovable and cursors.

• 29:47Molly O'Shea?

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• 30:32Molly O'Shea?

  So, Hamaan just went viral on X with his interview with Harry Stebbings of 20VC because he thinks that the triple, triple, double is over. And we now have an entirely new pace, similar to the numbers that you're speaking about. It's become a much faster pace, a higher velocity of companies. But this post, like this clip went viral because a lot of people didn't like to hear that. They, they, they really like, there was a lot of backlash against it. And they're like, no, I've been running my business for like 10 years and I've gone to X amount of revenue. That doesn't mean you're a failure.

• 31:13Speaker 01

  You're not a failure at all. Yeah, it's just different. It depends upon what problem you're solving. And that's my point with AI. If you get product market fit.

• 31:25Speaker 01

  This is, by the way, the metrics I'm giving you are for top decile companies.

• 31:30Molly O'Shea?

  Yeah.

• 31:30Speaker 01

  They're not for everybody. Like, if you can build a durable, sustainable business, it's an amazing thing. But if you are an AI-native company and if you hit product-market fit, that's the kind of growth you're getting. That's the kind of growth you're getting.

• 31:47Molly O'Shea?

  How do you decipher real revenue versus experimental or vibe revenue, as some people are calling it?

• 31:54Speaker 01

  Yeah, I would say this is where one needs to go deeper than the 30-second elevator pitches. So what I would say is, real revenue to me means it's real customers, not startups selling to other startups. And startups of an incubator selling to startups of that incubator, right? So your customers have to be around. Second, these contracts need to be real and recurring in nature.

• 32:26Speaker 01

  They can't be like, hey, conditional, I'll give you $20 million. Okay, but when? When, right? So I would say that's where, in my mind, real revenue and durability matters. And there's one more point, even though I mentioned earlier we are entering, or we are in the era of like vibe era or vibe economy, there is a problem with vibe revenue, that your gross margins are very low. So to build SaaS companies have 70, 80, 90% gross margin.

• 33:04Speaker 01

  But a lot of these coding companies, they have either negative margins, which has been reported, or 15, 20% gross margin. That's a problem. So to me, when I say you have to have durable revenue, it has to be from real customers who are going to be around. Second, it needs to have high margin. And third, it has to be repeatable and not conditional on 50 things. And I prefer the real revenue companies, even if they have slower growth, than these vibe companies which will never make money.

• 33:42Speaker 01

  And that's where I think it's a healthy balance. But if you're claiming you're an AI native company, you're an AI first company, then the market is allowing you to have that kind of growth, but this hundred million is a fiction. Right. But I think one, ten, fifty is doable in this new era. Very different than what the market opportunity was for entrepreneurs who started a decade back. It's just different timing.

• 34:10Molly O'Shea?

  For those that don't know much about these coding companies, could you explain why their negative margins?

• 34:16Speaker 01

  Yeah, I think they are built on top of the AI model companies. And the cost of inference today is very, very high. So whatever I charge, I'm charging as a coding company, a certain amount of price so that I can expand the market, so that it's affordable. There is a difference in SaaS companies.

• 34:47Speaker 01

  The more AI companies succeed, the more they get used. And your meter is on from the AI model companies. So if you create a great company, actually your best customers you lose money on. So my advice to them is come up with variable pricing. Don't say in twenty dollars you can code everything, or in fifty dollars you can code everything. That's where what I mentioned earlier, consumption based pricing, outcome based pricing is happening. So it's happening because of two things. You don't have your own model. You're dependent upon somebody else's model. They're charging you for tokens used. Costs are not at the point where inferencing is cheap. It will be.

• 35:32Speaker 01

  But then your most successful customers are the ones making you unprofitable. Because they are on a fixed fee plan and they're consuming hundred x the resources of what they should be consuming. So that's what is happening, why the margins are low.

• 35:50Molly O'Shea?

  It's crazy.

• 35:52Molly O'Shea?

  We talked about revenue metrics, but I'm curious. One of our sponsors is, I was gonna say sorcery, but one of our sponsors is Brex. And Brex is all about spending smarter, moving faster, performance. Their performance-driven modern finance stack. I'm curious, from your standpoint, apart from these revenue metrics, what are the other metrics that you use to measure company's success? When you invest in them at the inception and then also follow on?

• 36:21Speaker 01

  So I think at the inception stage, the most important point is you have to identify a customer segment, what is called the ICP. You have to find the right persona within that customer segment and make sure your product is a painkiller, not a vitamin. And initially, the revenues won't matter that much. What matter is, do your customers love you? Are you a daily habit? Are you an hourly habit? Are you a minutely habit? Or whatever the right word is. How often are people using you, right?

• 37:05Speaker 01

  They have to be in love with your product. So that's what we look for when we give somebody a seed financing is, can they do these things? If they can establish an ICP where they have product market fit and signs that they are creating value for their customers, that's when they say easy. And then the meter turns on, whether you're 1310, whether you're 11050. It's not for every company. It depends on which market you're going after. You can't grow faster than the market needs you. So I don't think we can come up with a rule. Every company needs to be 1100. How? If the end customers are not moving at that pace,

• 37:47Speaker 01

  that's why the MIT report says 95% of these AI experiments don't work. The customers are not ready.

• 37:55Speaker 01

  Right? So I would say the other metrics besides, so I would look at, these are not even revenue metrics. Then the other thing you try to look at is, do they have a long-term viable economic model? When the internet happened, e-commerce was taking off. You sell a thing for a dollar. It used to cost you $3. Of course, everybody will buy. So you can't do that, that you're selling something at a dollar and to serve it, it costs you five dollars. Can't happen. So durable business models are very, very important. And then, once you get into the revenue stage, repeatability becomes very, very important.

• 38:39Speaker 01

  And then, once you start growing into follow-on round, all the SaaS metrics of magic numbers, all the KPIs will get modified and there'll be new laws which will be put out, some by VCs, some by the industry pundits. That hasn't happened because these spaces are only like a year, 18 months old. That's coming. We are also thinking about it. Everybody is.

• 39:04Molly O'Shea?

  Can't wait for the next VC report on telling us what the metrics are.

• 39:08Speaker 01

  There'll not be one. There'll be tens, twenties, thirties of them.

• 39:12Molly O'Shea?

  I want to go back to one of your initial things that you look for and that's investing in people. So what are the key traits that you look for in founders?

• 39:21Speaker 01

  It's like going to Coca-Cola and saying, how do you make Coke? So that when Pepsi listens to it, they say, now I know. No jokes apart, right? Like, I think first and foremost, we're looking for authentic people. We don't want to work with people who are like faking it. Second thing I would say is company building is a team sport. So we look for people, how many times do they use the word V versus I? So if they use the word too much of an I, then they're an individual player, then they should go play tennis. They shouldn't play

• 40:00Speaker 01

  football. Unfortunately, company building, 99% of the time will be a team sport, like American football, like basketball. But there is a lot of memes also on Twitter, X, that then will be the single company which will be a billion dollar company. And again, that'll be rare. Right? So start with people who are authentic. They're team players. They need to be very mission oriented.

• 40:31Speaker 01

  They can't be in it for a quick buck. They need to have high level of emotional intelligence. They need to be very secure in their skin. Because insecurity will make you do things that are just not good. That are just not good. And they are always willing to put others, company first, team second, themselves third. Which very few people do. Those are the people who create loyalty. They are the people who create movements and end up creating these iconic companies. And then finally, right, like they have the hunger.

• 41:15Speaker 01

  To go through any wall, including Mayfield's office, including my home. They just don't take no for an answer. They'll just drive through. Because that's what entrepreneurship is. It's about persistence and perseverance. They'll just go through any wall. So that's what you have to spot, right? Like, are these people like that? Because the all odds when you're an entrepreneur are against you. Everything is against you. Because at the stage we invest, it's a paper and pencil idea.

• 41:43Speaker 01

  Everything is against you. So they have to be crazy but authentic and very values oriented. And putting this people gene is very important.

• 41:55Molly O'Shea?

  Who's an entrepreneur that you admire?

• 41:57Speaker 01

  Many of them. And it'll be unfair to say, right, like one versus the other. But I can give a few examples, right? Like John Zimmer of Lyft. Amazing person. Lyft ended up creating a community where they essentially pioneered ride sharing. Where normal humans drove other humans and created a fun community. Another one is Manish from Poshmark. Where basically their aim was, it's all about love. And they created a community of women selling to other women fashion.

• 42:36Speaker 01

  And they created many, many jobs. Another one was Mitch and Armon from Hashi Corp, which had a Tao of Hashi Corp. Again, their values on which they built a company and always put people ahead of themselves. They never wanted to be VP of Hinge, never wanted to be a CEO. Said, you're going to build a company. We're first time founders, never worked anywhere. Help us, help us. So they knew their weaknesses and were secure in their skin. So that's what I've seen with some of these people. But everybody I've worked with, I just love working with them and enjoy working with them. Everybody is different.

• 43:21Speaker 01

  So it's unfair to only give those three. But hey, they were the unicorns, decacorns, so they came to mind. They came to mind.

• 43:30Molly O'Shea?

  So one of the themes that we've covered throughout many of the questions and your answers is what happens when we get superintelligence? There's lots of opportunity. But what does that actually mean for people at their jobs? And when do you think we're, when do you think we're going to get AGI?

• 43:48Speaker 01

  Yeah, I think AGI to me is like far away. But far doesn't mean fifteen, twenty years, but it's not one, two years. I would say already we are seeing with machines, they can do certain tasks at the same level as humans or even better than that. But humans, I believe, are not dinosaurs. Technologies come and go, they adapt themselves. And that's what is going to happen here. AI is going to be a tool where humans are the jockeys. They'll use this horse to adapt themselves, to endorse this, adopt it,

• 44:31Speaker 01

  and do things that they should be doing. And this is the same level, right? Like when you're an exec in a company. You have a team. You don't do everything. Similarly, if you're an employee, you don't write by hand, you just type. Now you'll be able to verbally see it. So what does this do? First, intelligence is going to get democratized. Knowledge is going to get democratized. Expertise is going to get democratized. So why should only a technologist or an engineer be able to start a company? So I think the number of creators or number of entrepreneurs is going up by ten to twenty X. It's going up by ten to twenty X.

• 45:15Speaker 01

  Because now, using vibe coding, using AI as a tool, you'll be able to create something. You don't even need to know marketing, AI can do it for you. So to me, knowledge, expertise is going to get democratized and humans will do things that we only dreamt about. Using AI as a tool, using AI as a horse, and I think sky is the limit. Sky is the limit. So my advice to every human, including myself, is consume this thing before it consumes you. Right? So we'll be doing new things that we were never doing before.

• 45:55Speaker 01

  And these machines and us will be teammates and they'll do certain things better than us, we'll do certain things better than them. At the end, we control what we use it for. So that's why it's a technology, right? And like any other technology wave that has happened, there was always fear, cloud happened, PC happened, the people who were typewriters, sitting in law firms, they'll go away. Actually, it expanded. Number of CPAs expanded, number of doctors expanded. Now, instead of thirty million developers, we'll have a billion developers. So that's what normal people will be able to do things.

• 46:38Speaker 01

  For example, I used to write a blog every six to eight weeks. Now I'm writing weekly.

• 46:47Speaker 01

  It's amazing. Similarly, no product ever gets finished.

• 46:53Speaker 01

  And every time the PM and the engineers are fighting how many features can get in. But now using AI, you'll be doing more. So, Apple, for example, changed the consumer electronics industry, where new products come out every year. With AI, maybe they'll be coming out every six months. Maybe they'll be coming out every three months. That's what is going to happen. Innovation is going to get democratized. And humans are smart. They will figure out. And it's hard, as a VC, to know what exactly people will do. Because then, if it was so easy, why do entrepreneurs exist? We don't know what the world will look like.

• 47:37Speaker 01

  But it'll be different, where humans are going to do things that we haven't been able to do before. And it will be an era of democratization of knowledge, expertise and intelligence. But many, many, many people, where there is shortage of doctors, lawyers, nurses, will be able to do those things with AI assisting them. AI will be an assistant.

• 48:05Molly O'Shea?

  Very optimistic.

• 48:06Speaker 01

  Always have to be. Otherwise, I'm in the wrong business.

• 48:09Molly O'Shea?

  That's true. Optimistic and expansive. It's good. What are you most looking forward to in the next 12 months?

• 48:16Speaker 01

  Just working with great entrepreneurs, from whom I can learn and who are going to go create companies which are going to change the way humans work, live and play.

• 48:27Molly O'Shea?

  Amazing.

• 48:28Speaker 01

  That's what you have to dream for every day when you wake up, that entrepreneurs and humans will make the world a better place and change the way we work, live and play.

• 48:38Molly O'Shea?

  Levine, it was a pleasure to have you on. Thank you so much.

• 48:41Speaker 01

  No, it was great. I really had fun. Thank you.

• 48:45Molly O'Shea?

  Hey, it's Molly. If you enjoy our interviews, check out our newsletter, sorcery.vc, where we deliver a once a week top deals and tech headlines email and also go deeper on our podcast interviews. Subscribe to Sorcery today. And don't forget to subscribe to the podcast on YouTube, Spotify, Apple or wherever you listen. Link in description to sign up.