Former Intel CEO on What Went Wrong, What's Next + Lovable CEO on the Real Promise of Vibe Coding

(0:00) Former Intel CEO Pat Gelsinger joins Jason! (1:41) What Went Wrong at Intel (15:19) Why a Taiwan Blockade Would Cripple the US Economy (25:00) Lovable's Anton Osika: One Million New Apps a Week (33:38) How Lovable is Bringing Down Builder Costs Thanks to our partners for making this possible! Airwallex is a leading global payments and financial platform for modern businesses, offering trusted solutions to manage everything from business accounts, payments, treasury, and spend management to embedded finance. https://airwallex.com/allin PLAUD — If your work depends on conversations — meetings, deal flow, interviews, customer calls — Plaud helps you capture and organize everything with highly accurate AI-generated notes that are not just simple summaries, but also highlight pain points, key decisions, next steps, and customizable summary templates. Check out Plaud at https://www.plaud.ai/allin and use code ALLIN for 10% off! It is also available on Amazon: https://amzn.to/43URLff (Code: ALLIN10X) Follow Pat: https://x.com/PGelsinger Follow Anton: https://x.com/antonosika Follow the besties: https://x.com/chamath https://x.com/Jason https://x.com/DavidSacks https://x.com/friedberg Follow on X: https://x.com/theallinpod Follow on Instagram: https://www.instagram.com/theallinpod Follow on TikTok: https://www.tiktok.com/@allin Follow on LinkedIn: https://www.linkedin.com/company/allinpod Intro Music Credit: https://rb.gy/tppkzl https://x.com/yung_spielburg And a special thank you to Raise Summit for hosting us in Paris

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

• 0:00Jason Calacanis?

  Spent a long time at Intel.

• 0:02Speaker 01

  Yeah, only thirty-four years.

• 0:04Jason Calacanis?

  Thirty-four years.

• 0:05Speaker 01

  Yeah.

• 0:06Jason Calacanis?

  Probably one of the greatest American companies ever. And then absolutely went off the rails and got absolutely demolished by Nvidia, TSMC, and I guess Apple to a certain extent. So you had this incredible Intel Inside moment. We bought our computers based on, you know, hey, the Pentium and that sound.

• 0:33Speaker 01

  Intel Inside, baby.

• 0:34Jason Calacanis?

  Intel Inside.

• 0:35Speaker 01

  Dum dum dum.

• 0:36Jason Calacanis?

  You dum dum dum. And so let's talk about how things went wrong, what went right, and then how did it? And you were there for a long time. You took a break and then you came back. But there seem to be have been some critical mistakes that we can learn from. So let's just embrace it and go right into it. Tremendous success as an American company, coming back now, I think reasonably. But when you, when we look back on it and we do our postmortem, what were the mistakes and what would we change in terms of the direction of that company?

• 1:12Jason Calacanis?

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• 1:41Speaker 01

  Having spent so much of my life there, you know, I view it, I joined when I was eighteen. I went through puberty at Intel, right? I joke, right? You know, it was just like, you know, I am so early. Grove, Nois, Barrett, right? And, you know, they were the people I grew up at, right? You know, so on. They were my mentors. They were the people I adored for it. And they were deeply technical.

• 2:07Jason Calacanis?

  Andy Grove.

• 2:08Speaker 01

  Andy Grove, Gordon Moore, Bob Nois, you know, co-inventor. You know, these were deeply technical leaders. I remember when I joined the executive staff for the first time. There was, you know, probably fifteen of the twenty people that were in the room were PhDs. Right? You know, it was just that technical. And, you know, I view one of the things that went off the rail was when it started to be run by business people.

• 2:31Jason Calacanis?

  Yeah.

• 2:32Speaker 01

  Opposed to technical.

• 2:33Jason Calacanis?

  The bean counters, the finance people.

• 2:34Speaker 01

  Yeah. And, you know, when I became CEO in two thousand and one, that was the first technical leader in essentially fifteen years, right? You know, associated with it. You know, and if you have a business leader, who does he promote? Business leaders and, you know, right? You know, so I think one of the fundamental things is, and you know, as you look at the great technology companies today, you know, they're deeply technical.

• 2:59Jason Calacanis?

  And founder-led typically.

• 3:01Speaker 01

  Yeah. And even if they're not, you know, Satya's not a founder, right? You know, Sundar's not a founder as well, but they're deeply technical individuals. And when you're making these hardcore technical, you know, decisions that affect billions of dollars, you don't do that through a spreadsheet. That's a lousy investment, right? Unless the technology trends make it the right investment. And I think that's one of the fundamental things. And obviously, you know, in the five years, five, six years before I came back, you know, Intel gave a hundred billion dollars to shareholders.

• 3:36Jason Calacanis?

  Oh, the dividends and stock buybacks.

• 3:39Speaker 01

  Yeah, a hundred. What I wouldn't have done for another hundred billion dollars on the.

• 3:46Jason Calacanis?

  Well, I mean, what would you have done? You probably would have made chips for iPhone, which Intel passed on, yeah?

• 3:53Speaker 01

  Yeah, you know, but, you know, hadn't built a new factory in a decade when I got there. It's like, you know, how can you not be building? How could you not buy EUV machines? You know, there's just all of these things, you know, that you would only do as a technologist because the economics behind them by themselves were not good. So, you know, it was getting back to the core of technology to me that was, you know, the fundamental thing. You know, you make good decisions, you make bad decisions as leaders. Every business does that as they go along. But, you know, fundamentally, this is a technology business and you need technologists running technology that then hires technologists that are sitting at the staff, but then hire the best technologists, you know.

• 4:37Jason Calacanis?

  And take big swings at, you know, categories that could matter in the future, like skating to where the puck's going. If you look at Apple, they did the same thing for the past fifteen years, buying back the stock, tremendous amount of dividends, did the largest holder of capital of any company, I believe, to this date. And what if, what companies do they buy? They buy little tiny acquisitions on the margins. I think the largest ones was Beats because they wanted to get inroads into, you know, certain demographic segments like in the Android space that they couldn't get into. But my God, what a colossal waste of time. Like you said, they could have done so many amazing things. Tell me about Steve Jobs in two thousand and eight, two thousand and nine deciding,

• 5:21Jason Calacanis?

  I think we're going to make our own silicon and that impact. Because was that a covert product project? Did you guys know he was doing that? Did he inform you?

• 5:30Speaker 01

  Well.

• 5:31Jason Calacanis?

  That seemed to be another one of those forks in the road, yeah?

• 5:33Speaker 01

  You know, Steve was an incredible leader. You know, he was also a ruthless leader, right? You know, very difficult, you know, read Walter Isaacson's book on him as well. I had many, many conversations with Steve over the years, you know, for it. But, you know, when they moved to Intel and the Centrino chip, it was a big deal.

• 5:53Jason Calacanis?

  Yeah.

• 5:53Speaker 01

  Right? And they were putting extraordinary demands on Intel. You know, make the chip smaller, drive lower power. They're demanding a customer. And when he was no longer convinced that we could continue to do that, you know, he started the project, right? You know, and if you remember, was it, you know, you know, P semi, you know, they acquired some small companies, started to build some competency. But, you know, they did a few little chips internally. It wasn't a big deal. And then the little chips got a little bit bigger, you know, and Steve was a master of this. You know, just starting, you know, these small efforts to build core competence inside the company.

• 6:33Speaker 01

  I remember when we had the first conversation with Steve about porting the operating system to the Intel chip from the power chip that they were running on before they moved to Intel. And we were quite proud of the silicon software competencies that we had and compilers and operating systems. You know, so Steve, we'll help you port the operating system to the X86. And I remember that Steve said, I've been working on that for the last four releases. He had been preparing the core technologies inside of Apple for something that might happen in the future, you know? And he was already, you know, to me, I just remember, I was just shocked.

• 7:17Speaker 01

  I, you know, I ported the last four releases to the X86. I think we got this.

• 7:21Jason Calacanis?

  Yeah.

• 7:22Speaker 01

  Right? You know, it was that kind of thing. And that's how they got into the semiconductor, you know, doing their own semiconductor. Hmm, I'm not sure I can rely on Intel to be that much ahead of the industry. And I can start optimizing the system design with the silicon design as opposed to relying on one that's been somewhat optimized for a Windows environment versus an iOS environment, you know, in their operating system. And, you know, it was just, you know, you know, it was never that kind of thing that you sort of said, you know, you're right. You failed as a supplier. No, I can supply myself better.

• 7:56Jason Calacanis?

  Yeah. And Jensen decides, hey, he's going to go all in making these video cards and talk about just incredible serendipity that these happen to be also very applicable for cryptocurrency and running these AI jobs.

• 8:16Jason Calacanis?

  Was that luck or skill or a combination of both there?

• 8:20Speaker 01

  Well, you know, when you think about that progression, you know, Jensen, he was just building high-performance computers, you know, throughput machines. You know, when we were at the height of our strength on CPUs at Intel, we sort of scoffed at his machines.

• 8:36Jason Calacanis?

  Yeah.

• 8:36Speaker 01

  Right? You know, so like, oh, it's a graphic machine, you know? You know, there's some gamers who want to use that kind of stuff, right? You know, it was always the big CPU and those little GPUs. But when they started to build a real software stack.

• 8:49Jason Calacanis?

  Yes.

• 8:49Speaker 01

  With it, right? You know, sort of, okay, this CUDA thing and SIMD as a technology, you know, so, you know, multi-threading and so on. And it just sort of kept getting a little bit better and a little bit better. And it was a little bit Jobs-like in that way. You know, we're just making it better every release and it's becoming more robust. And all of a sudden, you know, the crazy, you know, Japanese HPC guy said, hey, we could take those graphics cards and maybe start using them in HPC. Right? You know, that was sort of defining moment where it wasn't just about doing graphics anymore. This was a more computationally dense platform to start attacking some of the world's most interesting workloads.

• 9:31Speaker 01

  And I think Jensen would agree that was a defining moment in them sort of saying, oh, these aren't just graphics cards anymore. You know, these are general-purpose computing devices that can start applying to these other workloads. And, you know, AI was, you know, had gone through, what? Its fifth nuclear winter by that point? Where it's like, man, you know, you know, this is never going to matter, right? We're never going to, you know, get the breakthroughs. But the community around it was continuing to develop.

• 9:59Jason Calacanis?

  Yeah.

• 10:00Speaker 01

  You know, for it. And the CUDA software kept getting better, generation by generation. And, you know, I had a project at Intel Larrabee, right? Where we were trying to take the X86 and essentially do the same thing, right? You know, for, and, you know, in my first departure from Intel, the project was killed a week after I left. And the world would have been so much different, right?

• 10:24Jason Calacanis?

  I mean, it really, I think it's illustrative of what continuous innovation, taking some risks and doing that fundamental research and the compounding power of technology. Because I think it was William Gibson who said, the street finds its own use for technology. Like. Nvidia did not predict that this Bitcoin project would take over and that this would be the best way to do those computations, nor did they anticipate, I think, you know, that AI would take off. But because it was the best solution, the hacker community could kind of figure that out. Well, as we wrap on the Intel portion of your career, um, okay, Apple

• 11:05Jason Calacanis?

  Silicon, that's one. Uh, and then you have Nvidia, and then you have this Taiwanese company, uh, that starts making, you know, really great at fabricating the, these chips, um, and Intel missed that as well. Yeah. And then maybe you talk a little bit about TSMC and their surging, and we can even get into a little bit of the, the politics of it now. And then we'll get into some of these AI chips and venture investing.

• 11:31Speaker 01

  The, you know, the thing with TSMC was they started with a vision of foundry, right? You know, they were going to become the factory for the industry. And again, these factories are so expensive, 20 billion, 30 billion, and, uh, the engineering and the continuous investment required to do it. And, you know, it was a stunning, you know, vision, uh, at that point in time. Intel was IDM, as we called it, the Integrated Design and Manufacturing. You know, we never worked to make our process and our factories available for third parties. Hmm. Right? You know, it was always this thing, hey, it's, you know, we do enough CPUs

• 12:11Speaker 01

  ourself, you know, we reuse it for chipsets and some of the other things that we're doing, but it was never standardized in a way that it could be made available for a broad ecosystem, you know, using PDKs and all the design tools. You know, we did a lot of our own EDA tools ourself. You know, one of the projects that I started earlier in my career was the foundations of EDA, right? Uh, as well, the first place and route, you know, the first standard cells, the first high level description language, you know, it was so proprietary and TSMC basically cut that in half and says, I don't care whose chip it is. I don't care what you're designing. I'll be your manufacturing partner. And at the time, that was such a trivial piece

• 12:54Speaker 01

  of the business. Intel didn't even care. Hmm. Right? You know, so on. And then over steady progress over a long period of time, and Apple as a customer, driving them to be good, become really meaningful, you know, obviously the world changed. And when I came back to Intel in 2001, TSMC was producing 5X the wafers of Intel.

• 13:18Jason Calacanis?

  Wow.

• 13:19Speaker 01

  Right? Not 10% more, 5X.

• 13:22Jason Calacanis?

  Yeah.

• 13:23Speaker 01

  And all of a sudden, that model of foundry became the model of the semiconductor industry with two exceptions, Intel and memory. You know, memory DIs, design and manufacture, right? For, you know, that is uniquely different. And obviously, you know, we're seeing them, you know, three trillion dollar memory companies, just extraordinary.

• 13:43Jason Calacanis?

  Yeah.

• 13:44Speaker 01

  You know, and, you know, trillion dollar foundry company, uh, in TSMC. You know, the industry has said, I want a lot of wafers. I want a lot of innovation of different designs. I have a layer of standardization and EDA tools and the world changed. And obviously, as I came back to Intel, that was one of the core thesis of the new strategy.

• 14:02Jason Calacanis?

  Yeah.

• 14:03Speaker 01

  We must become a foundry as well. Five to one. And now it's more like seven to one in terms of wafers, you know, to TSMC, to Intel.

• 14:11Jason Calacanis?

  Are we going to be able to ensure that? Obviously, we had the CHIPS Act and just give us broad strokes, what you think's going to happen here in terms of, obviously, Taiwan is in play. Some people in the administration believe, um, it's going to happen the year after Trump's out unless he takes his third term. Other people believe like it was going to happen as early as 27, uh, or maybe going into 28. So are we going to be able to replicate that here in America in a reasonable amount of time? Or is this like truly could be a cataclysmic event if, you know, God forbid, China decides, hey, we're going to blockade, um, Taiwan and then the Taiwanese decide, yeah, we're going to burn the fabs and we're

• 14:55Jason Calacanis?

  going to fly out all of the engineers and ship them to America.

• 15:00Speaker 01

  Well, there's a lot in that question.

• 15:02Jason Calacanis?

  Yeah.

• 15:03Speaker 01

  You know, do we have an hour to talk about this?

• 15:04Jason Calacanis?

  Well, I mean, we have six minutes, but.

• 15:06Speaker 01

  Oh, okay.

• 15:07Jason Calacanis?

  Yeah. Do the best you can.

• 15:09Speaker 01

  Okay.

• 15:10Jason Calacanis?

  I want to talk also about the AI bubble.

• 15:13Speaker 01

  So super, you know, three things about this super quick. You know, one is the CHIPS Act is having benefit.

• 15:17Jason Calacanis?

  Yeah.

• 15:18Speaker 01

  Right? You know, when we started the CHIPS Act in, you know, when 2001, when I came back, the US was building about 12% of leading edge. Today, that number is more like 18%. Okay. You know, we're making progress. It's not 50%. We have a long way to go, right? You know, Intel is starting to be a real foundry. Okay, that's real progress. Uh, and TSMC's factories are up and operating at scale, right? We have Samsung and, you know, uh, as well. But, you know, I'd say the Intel and the TSMC progress, okay, that's meaningful. Now, let's make it ugly for a second. Uh, the island of Taiwan has less than three weeks, a big article in the Wall Street Journal two weeks ago on this, less than three weeks of energy reserves.

• 16:02Jason Calacanis?

  Wow.

• 16:04Speaker 01

  Okay. That should just put a chill in everybody's spine, right? Because the blockade, after three weeks, the island browns out. When you turn off a fab, it doesn't come back on for 90 days, right? The economic impact of a brownout of Taiwan is greater than the Great Depression, right? Uh, in the world. Never do you need to do anything, a shot to be fired. You just need to say, great, no energy for three weeks.

• 16:33Jason Calacanis?

  No oil.

• 16:34Speaker 01

  Right? No LNG, right? You know, that's how the island run. That is scary. You know, to me, we need more resilient supply chains, uh, associated, you know, with it. And I don't think this is an alternative for the world, because if it really does become a risk, you know, and I'm, you know, I, you know, I don't sit in the situation room and get all the data and so on. But let's remind each other that I think China has blockaded the Taiwan Straits seven times over the last four years.

• 17:01Jason Calacanis?

  Yep.

• 17:02Speaker 01

  This isn't a theory.

• 17:03Jason Calacanis?

  No, no, they're running exercises. They're being pernicious and.

• 17:07Speaker 01

  Right.

• 17:08Jason Calacanis?

  Pretty provocative in terms of.

• 17:10Speaker 01

  Is that 2027? Is that 2030? Is that 2035? Their intentions have been clear over a sustained period of time. We need more resilient, uh, supply chains, you know, for it. So something, you know, I put a lot of my time and energy into, and we're making progress, but we need to go faster, need to go more meaningful.

• 17:27Jason Calacanis?

  Yeah. And let's talk a little bit about the AI buildout. I mean, you watched the PC revolution, servers, the internet. These were all extraordinary buildouts. And then this is the buildout to end all buildouts. So the amount of data centers, the amount of chips, the amount of inference needed. Do you think it's a bubble? I think I've heard you say like, it's, it's obviously a bubble, but what, what's the risk factor here that we build too much, uh, or that the technology doesn't solve enough problems and we are swimming in tokens? What, what worries you about what you're seeing now? The valuations of these companies has gotten quite extraordinary. And, you know, if they build too much and

• 18:11Jason Calacanis?

  they spend too much money and they don't make enough money, well, based on your experience with running a company, a public one, that's a lot of tension on it. When you don't make as much money as you're spending, people tend to fall out of love with these stocks. Yeah.

• 18:28Speaker 01

  Well, I do think there, you know, there, there is a silver lining here that guarantees we don't get too far ahead of ourself in terms of bubble. You know, and that is energy capacity.

• 18:41Jason Calacanis?

  Right.

• 18:42Speaker 01

  Right? You know, energy capacity in the world is expanding four, 5%. You know, in the US, we had a decade at 1%, right? You know, I mean, it's just hideous what we did to our energy grid, you know, over about a decade and a half. But now that's getting built out. But essentially, nobody's going to build and buy GPUs and build data centers if they don't have energy. So essentially, you have an upper bound on how aggressive and how hyped and bubbled that we get. So I take a lot of solace in that.

• 19:10Jason Calacanis?

  Yeah.

• 19:11Speaker 01

  Right? You know, for it, because what then is the incremental value of a token? And if it's a measure of intelligence, it's somewhat infinite, right? You know, in the sense, if I have more intelligence, I will do, you know, better supply chain. I will do better finance. I will do more, you know, efficient logistics. I will, you know, all of those things. So to me, the, the potential value that we unleash in a token economic world is somewhat infinite, right? And particularly with labor shortages and so on that we see, right, in, uh, developed countries. I am an optimist, you know, that we're in a couple of decade buildout.

• 19:50Jason Calacanis?

  Wow.

• 19:51Speaker 01

  Right? Not a couple of years, a couple of decades. One of the big objectives I've said is that I have to make AI 10,000x better, right? You know, it's way too expensive today. You know, we want to drop, you know, by five orders of magnitude, the cost per token, you know, the energy, you know, per token, so that we really do have Jevon's Law, that we just explode the access to AI, right, in much more economic ways.

• 20:17Jason Calacanis?

  Which it does seem like Jevon's, uh, paradox has been at play over the last year. Like, oh my Lord, these tokens are so cheap and the tools are getting so good. Yeah, I'm just gonna start using these tools all day long until the bill comes in and you're like, okay, yeah, maybe I need to get some ROI out of this. But you do have these incredible companies, Cerebrus, Grok, et cetera, making inference.

• 20:37Speaker 01

  Dematrix.

• 20:38Jason Calacanis?

  Yeah, just.

• 20:39Speaker 01

  Silicon and so, you know, and, you know, if we accomplish, right? You know, these orders of magnitude improving in token economics, availability, reduction in energy costs associated with it. You know, we just have a fantastic couple of decades in front of us. There has not been a time in human history where it's been better to be a technologist than the one we're in right now. We will solve chemistry, we will solve language, we will, you know, invent new materials, you know, new forms of, you know, uh, interaction. You know, uh, killing cancer, right, lifting people out of poverty. There is not a better time to be alive than the one that we're in right now. And as technologists, we get to sit in the driver's seat of it.

• 21:20Jason Calacanis?

  Pretty amazing, and you're investing, uh, and that's your passion now. What do you think of these valuations? It's quite seems, you know, if you live through the dot com bubble, we did see a disconnect there. These companies slightly different, we just have 11 labs up, 600 million in revenue, lovable. I think they're at five or 600 million, so that's quite different than the dot com speculation, yeah?

• 21:45Speaker 01

  Yeah, well fundamentally, we have real revenues, you know, real margins coming out of these businesses as well. You know, that said, anytime the multiples get too high, okay, some corrections. You know, and to me, periodic corrections that keep the multiple, you know, earnings multiples and you know, so on, and reasonable things is good. Because this will not be a smooth curve. You know, I'm predicting two decades of goodness, and there's going to be lots of disruptions along the way. It's not going to be a smooth curve, and every time we have one of those corrections, say thank you, right? We're not letting the bubble get ahead of itself, right? You know, hey, we have the SaaS apocalypse, there's going to be other apocalypses on that journey. When, when industries get impacted by the capabilities that will be unleashed.

• 22:28Speaker 01

  And that's even before it gets exciting, and what I call the Trinity of computing. Classical computing, AI computing, and quantum computing. And when those three come together, okay, that's when things get really exciting.

• 22:41Jason Calacanis?

  Hey, quantum's been about five years away for 25 years. Um, when is it actually going to do anything?

• 22:48Speaker 01

  This decade.

• 22:49Jason Calacanis?

  This decade, so by 2030?

• 22:51Speaker 01

  Yep.

• 22:52Jason Calacanis?

  It'll be meaningful, what should we expect in terms of its impact in 2030?

• 22:57Speaker 01

  You know, you're going to be able to start doing things that cannot be computed today. You know, chemistry, you know, biology, there will be things that can't be computed today. You know, some of the easy things will be some of like the logistics, where I will compute the best answer to get this thing to you, right?

• 23:13Jason Calacanis?

  Traveling salesman problem?

• 23:15Speaker 01

  Right, you know, all of a sudden, all of those problems. Uh, obviously, it's probably going to be, you know, 2020, 2032, 2033, when we solve, you know, things like encryption, right? You know, where, you know, he'll have the fundamental Q day, you know, kind of implications. But this decade, we will see quantum supremacy to, uh, results across multiple industries. You know, we know how to build qubits, we know how to error correct qubits, we now have algorithmics, right, against, uh, quantum. And, you know, now it's just about engineering scale.

• 23:46Jason Calacanis?

  Who's going to win?

• 23:47Speaker 01

  Well, obviously, I'm a side quantum guy, right, since that's one of our portfolio companies. But the thing that you're seeing is that you now have like four, five, six modalities of quantum that are demonstrating pretty good results, right? You know, across trapped ions, across, you know, photonic approaches, spin approaches. So you now say modality is not an issue, error correction's been proven, uh, across them. And, you know, I think the race will be on, and my prediction is meaningful results before 2030.

• 24:20Jason Calacanis?

  Wow, you realize that's about 40 months from now?

• 24:22Speaker 01

  Yeah.

• 24:23Jason Calacanis?

  Okay, meaningful results, thanks so much, Pat, for sharing all this incredible, uh, information and knowledge, great to see you.

• 24:30Speaker 01

  Very good.

• 24:33Jason Calacanis?

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• 25:00Jason Calacanis?

  Oseka is one of my favorite founders, he's the founder of lovable. Why do I love this founder? Uh, well, he's built a product that people are addicted to, primarily, Anton, the people who work for me. And I love talking to you because as a founder, you have a North Star, you're incredibly laser focused on enabling anyone to build great software. Yeah, it's the mission of the company, I'm paraphrasing here, but essentially, that's the mission of lovable.

• 25:30Speaker 02

  Mission, I talk about empowering humans.

• 25:32Jason Calacanis?

  Empowering humans.

• 25:33Speaker 02

  And the first gap is to build a product. The second gap is to build a business around that product.

• 25:38Jason Calacanis?

  Right.

• 25:39Speaker 02

  And now we're at, everyone at lovable, we're, we're working on both of these two gaps.

• 25:43Jason Calacanis?

  Right.

• 25:43Speaker 02

  The first one, we've gotten very, very far, we're seeing a million new products built every single week on the platform.

• 25:49Jason Calacanis?

  Incredible.

• 25:50Speaker 02

  And on the, on the second one, we're investing a lot in making it easier to run your business and to get people to care, people to discover what you build and the entire business of what you're, whatever you're doing as a small business. As if you're a large business, we're also getting a lot of traction. Um, and, uh, we're, we're actually seeing as a proof of that, more than 700 million visits to the applications every month. So every month, there's, um, extreme growth in, in the surface area of, of the entire, uh, more than 50 million apps built on the platform today.

• 26:24Jason Calacanis?

  How many years has lovable been in market, or how many months now?

• 26:27Speaker 02

  20 months.

• 26:29Jason Calacanis?

  20 months?

• 26:29Speaker 02

  Yeah, and, and again, we're, we're seeing people who are first time founders. We're seeing enterprise leaders move much faster together with their teams on this platform that has a lot of opinionated pieces in how you should, uh, create software and how to operate that software and how the different applications in your company connect to each other over time. So that's why we're seeing so much, uh, growth also on the enterprise side, which where we're actually growing fastest right now.

• 26:57Jason Calacanis?

  This is really interesting because 10 years ago, uh, people were doing Wizywig software. Um, what was the name for it? Before vibe coding? No code, low code, yes. And when I saw that 10 years ago in my incubator, you know, every 20th company, somebody would come in who was an MBA or not a developer, and they had vibe coded something. And, um, not vibe coded, they had no coded. And they were using these different software platforms and eh, the software didn't look good, it didn't work perfectly well, it was slow. But the promise was there. And I guess it took L L Ms and this new intelligence to make actually good software.

• 27:41Jason Calacanis?

  So maybe you could talk a little bit about

• 27:46Jason Calacanis?

  who is the customer? Because developers, uh, do developers use lovable? Or is it the other 95% of society that are your customers? How do you think about who your ideal customer profile is?

• 27:59Speaker 02

  Yeah, we're seeing people use lovable, both with a technical background. That's about 20% are, are technical or some type of engineer. And they, they love that we're quite opinionated, we put all the best practices into how the software is architected. And we make it seamless to, um, we want from get payment set up in a very secure way and do things like run security scans after every change, even now in the background, monitoring the projects. So it's actually quite, uh, appreciated by the engineers and the technical community. Um, also because it's a great bridge from the non-technical people, which is four out of five are, are non-technical. Uh, and they're building, uh, often first to figure out what is the right thing to build,

• 28:44Speaker 02

  which is where lovable has always been exceptionally good. And, uh, now what we're seeing is that people are running, uh, businesses, making more than a million dollars of revenue on the, on this platform. And so it's, it's this, we're building for everyone, it's this entire spectrum. And what's, what's exciting to see is often that if someone who discovers lovable from their colleagues at a large company, they go out and then run a side hustle. And some of those, those side hustles really work, they make hundreds of thousands of dollars, and then they become a founder after that. So there's this cross pollination from both.

• 29:17Jason Calacanis?

  Yeah, and this is like the really interesting thing about vibe coding. If we were sitting here last year, people would look at it and say, it's a great way to make a mock-up. Like you said, a great way to think about product and maybe create wireframes or a workable prototype. All of that's out the window now. The whole concept of building wireframes and building a mock-up, well, you could just go right to building the product in a day or two days. And what people I think don't appreciate about what you're doing at lovable is after you've made a product that you're proud of and that has some product market fit, there are many more steps that are required.

• 29:58Jason Calacanis?

  You mentioned payments, you mentioned security, uh, making sure that the data isn't lost or that it's not leaked.

• 30:06Jason Calacanis?

  That's changed dramatically over the last 12 months.

• 30:09Speaker 02

  Very much so. So I would say many engineers, they don't look at the code. They don't write code anymore. And that means that you don't need to be an engineer to create software. Right. But the thing that Lovable does for anyone, also the non-technical people, is that it creates a structure for the architecture of the software that you build. And it makes sure that you don't go off a cliff. And that things like setting up payments, emails, things like getting discovered by other AI chat engines and by Google search. Those things are kind of taken care of. You don't have to know how all these things work in the details.

• 30:51Speaker 02

  You can trust the platform to take care of data security, connecting to other tools that you might be using in a secure way. And that's really where us being opinionated from day one and being focused on making this for the 99%. It's a vast market, right? From day one is what made us very successful.

• 31:12Jason Calacanis?

  Yeah, and I can tell you internally, I gave my team all the different tools they could possibly want to use. And somebody had started with Lovable. I think I told you this story when you were on This Week in Startups a year ago. And they made some interesting websites and they were trying to make an Intranet. They couldn't quite get it done. Then I had some people who started using Cursor or Claude Code. They started vibe coding stuff, but they couldn't finish the product. And then people tried to solve some problems with CoWork. I really like Perplexity Computer. And then my team came to me. And for one of our projects, I was talking to you about Founder University, our pre-accelerator, they wanted to make an Intranet.

• 31:56Jason Calacanis?

  Now, this is something I would have never okayed because it would have cost $500,000 10 years ago to make it. And we don't have that kind of budget. You know, we would rather put that towards the founders in the program and getting more people into the program. And in four to eight hours, they made the whole Intranet. And they made a bunch of things I hadn't asked for. And it was the person running this Founder University who made it. And she did it on her own without permission in Lovable. I said, whoa, how did you build this? She said, Lovable. I was like, oh, we still have Lovable? And she's like, I just put it on my corporate card, to your point. She made it.

• 32:38Jason Calacanis?

  Now that software is driving the program. And the reason people do the program in their country, we have it in Saudi and in Japan, is because it has economic impact. So I said, hey, I have an idea. Can you make for me an economic impact of the 50 companies that are in the program? She asked Lovable to do it. I gave her some prompting, human prompting, boss to. Now it has the economic impact in there. And it considered with our prompting, well, how many people work at each company? What are they paying taxes? How much do they rent their home for? What is their average salary?

• 33:21Jason Calacanis?

  And it built something that I would have never been able to afford to build. And Lovable is 50 bucks a month, I think. I don't know how much you charge, but it's far too little. Like $50 a month, I think?

• 33:33Speaker 02

  Yeah, that's if you're on a business plan. It starts at 25.

• 33:37Jason Calacanis?

  Yeah, so the economic impact of what you're building is I would equate for what you built to us, it would have cost me $500,000 two years ago. It was built in four hours by an employee, which if you just put employees at 50, 60, whatever, $70, plus the cost of your software, it got made for less than $2,000 in a year. It's extraordinary.

• 34:02Speaker 02

  I'd love to hear more about the progress of the Intranet. Anything that you ask for that you want to forward directly to me?

• 34:10Jason Calacanis?

  Well, right now, you know, my concern was security and making sure that data didn't leak. And they talked to your team and they went through it and it's secure. So we feel good about it.

• 34:22Speaker 02

  Look, I'm now asking people who do penetration testing to say, I want you to compare all the tools and make sure that there's all the work that we're doing that's not visible on security and trust. There's a lot of things where we invest and spend money that also free users get a lot of security scanning, running in the background, that that actually translates to something that security experts can see.

• 34:53Jason Calacanis?

  A year ago, we were at mockups. Now we're at functionality and secure and super viable for deployment. Where will you be in a year?

• 35:03Speaker 02

  Yeah, so what we're seeing is that there's a gap in being able to build a product, right? And you built an entire Intranet on the platform. That's great. What we've done since then is to have a new product line, basically, the hosting part, which is both the AI and all the normal hosting. And that product line has been going faster than the building thing.

• 35:24Jason Calacanis?

  AWS competitor.

• 35:26Speaker 02

  It lets you run all your software. And then we're working with companies like AWS under the hood as well. But what you also want to have is to use Lovable, we're seeing by our customers, as an AI co-founder, a partner that you talk to about everything in your business. And if you're running your apps, your tools are on the platform, then just talking to Lovable has access to all the data that you might want to know about your company, how it's doing. So we're working with some of our customers in pre-release to give them access to a co-founder that works for you even when you're sleeping. And comes back to you in the morning and says, like,

• 36:09Speaker 02

  here are some strategic directions you could go. Here are some optimizations you can go in terms of growing your business faster, serving your customers better, faster. And that's that evolution towards operation and intelligence towards driving towards outcome in your business.

• 36:29Jason Calacanis?

  So you come to build the software, but you stay to build the business?

• 36:33Speaker 02

  Yes, to operate your business. And what we're already doing, I've been doing for a very long time, is to compound from everything we're learning. Every time Lovable makes a mistake, it goes to a gigantic system with our engineers in it, improving it. That compounding intelligence is of course applicable to our customers, our users running their business on our platform as well.

• 36:56Jason Calacanis?

  Is software going to become 100% bespoke, even like the internal tools? I was looking at Slack. And our bill for Slack, even on the highest version, is maybe $10,000 a year. It's not a lot of money. It's well worth it. But I was starting to think, well, maybe I should vibe code my own Slack so it's integrated into everything we do at a deeper level. So what do you think the future will look like in terms of some of these foundational pieces of software that every startup, every enterprise uses? Salesforce, HubSpot, Slack, the Google Suite, Microsoft Office.

• 37:40Jason Calacanis?

  Will bespoke software start to replace those, do you believe?

• 37:46Speaker 02

  I like this question. Let me answer it, but I'll just give you a story about someone I recently heard who's going on this journey. They're quite advanced. So Nenad, he works at a pretty large company in the US, NERSA. And he came to our platform because he wanted to build out the new product lines. NERSA study for educating more nurses. And he built out all the admin tools for the program, the scheduling for the nurses getting their licenses and their certification management. And he was able to build that into a product and to take it to market because they have had all that access to nurses wanting their certification. What he also did was he took it into their back office internally.

• 38:30Speaker 02

  And they've now replaced more than 10 tools that they had, bespoke applications. And in terms of your question, you can do that for multiple reasons. In their case, they're saving more than a million dollars per year. So that's huge, right? But it's also the case that in some cases, you have specific requirements where the tools that you've been using to date, they aren't suited for those requirements exactly. And in those cases, I think, yes, you will have more bespoke solutions. But I also expect us to see that Lovable continues to interoperate with all of those tools. And I'm not sure if you've tried this.

• 39:13Speaker 02

  If you ask for connecting to anything in the Google Suite or anything in the Microsoft Suite or Slack, Lovable guides you through all the steps to do that in a way where you can get a very good overview of exactly how the data flows, which is of course very important, that you don't give access to the wrong person, to the wrong data. And you can continue to use Salesforce, HubSpot and all the tools that you kind of like to use under the hood, but with a bespoke interface on top of it.

• 39:40Jason Calacanis?

  How have these new frontier models? They're in some ways competitive, but in some ways, you can use them to power Lovable. So how do you think about the competition with them? Open source and the future of Lovable? Because people have announced that Lovable's dead every six months since you started. And then every six months, you go from 100 to 200 to 300. I think you're at 400 million in revenue, something crazy?

• 40:09Speaker 02

  We reached 500 in May.

• 40:11Jason Calacanis?

  Okay.

• 40:12Speaker 02

  Growth is phenomenal.

• 40:13Jason Calacanis?

  So you're dying again by another 100 million in annual revenue. So but underneath the hood, you're using some of these.

• 40:22Speaker 02

  Yeah, let me explain. Yeah, so we've always had this strategy that we do whatever is best for our customers. And in terms of intelligence, that means that we're using multiple models. And so if you ask Lovable now, it's actually routed to the model that's most suitable to whatever you want to do. And that's both the commercial frontier models from multiple vendors. And increasingly, it's open weight models. Where our team, whenever it gets routed to our own model, that model becomes more intelligent for our agent harness, especially on the mistakes that it might be making in some cases on which tool to call, which integration to create

• 41:06Speaker 02

  and how to guide you through success for your business.

• 41:09Jason Calacanis?

  Right, so you're all in on open source. You believe that's the future of Lovable? I'm reading into it.

• 41:16Speaker 02

  So we have multiple partnerships and we're investing heavily to be close with those partners. And it's the big labs. And it's also to make sure that. We get the fastest performance at the lowest cost for our customers when we know that we can do that with our own models.

• 41:33Jason Calacanis?

  Right.

• 41:34Speaker 02

  And we have a really, really strong research team up in Stockholm, who is working on what's called post-training.

• 41:40Jason Calacanis?

  Sure.

• 41:41Speaker 02

  And we're applying all the best practices to do that and scaling up that team quite significantly, since we also believe it's a part of the European ecosystem to have that capability in Europe specifically.

• 41:53Jason Calacanis?

  Are you doing or are you using any of the data labeling, data training companies to help you understand the most common businesses and build that proprietary data?

• 42:05Speaker 02

  So what we're doing is that we're looking at the mistakes that any of the models do right now. And then we prioritize them by what drives most impact for our customers. And then we make the models, we create data sets, we do something called reinforcement learning, specifically for the problems where the frontier models are making mistakes for us right now. And we have this enormous token distribution, right? From a million new projects being built every, every single week.

• 42:34Jason Calacanis?

  Yeah, you're burning a lot of tokens.

• 42:36Speaker 02

  We are, yes.

• 42:37Jason Calacanis?

  Yeah.

• 42:37Speaker 02

  And that's, and that's a lot of signals for making the system, both the agent harness and what we've been refining over the last two years, which is the skills, we have this like internal type of skills that the agent knows when to remember the facts from our software engineers that know how to build really, really good software.

• 42:57Jason Calacanis?

  Someone told me.

• 42:58Speaker 02

  And we're modifying both of those on every, every single week.

• 43:01Jason Calacanis?

  Makes total sense. And somebody told me some companies are doing token dumping. They're, you know, selling a hundred dollars worth of tokens for fifty dollars.

• 43:12Jason Calacanis?

  You know, basically they become token resellers in some ways and they're money-losing businesses. You have to, you're money, you're profitable, I believe now or close to it?

• 43:22Speaker 02

  We, we always monitor our margins, but again, we're doing what's best for our customers. And that means, that often is more intelligence. So we're not, we're not looking at, oh, let's use it. We've never had the decision to say, let's use a cheaper model here.

• 43:36Jason Calacanis?

  Right.

• 43:37Speaker 02

  If it's measurably worse for our customers.

• 43:39Jason Calacanis?

  Got it.

• 43:40Speaker 02

  And we can measure that, what's best for our customers.

• 43:42Jason Calacanis?

  Is it unlimited for the fifty or you have caps now?

• 43:44Speaker 02

  We have caps.

• 43:45Jason Calacanis?

  Yeah, you have to have over justing caps. Are people starting to hit them?

• 43:49Speaker 02

  Yeah, our customers definitely hit caps and then you can top up, you can have a, we have multiple subscription tiers.

• 43:56Jason Calacanis?

  What number, I'm just curious, like what percentage of people need to top up? They're so addicted to it that they're blowing past the.

• 44:02Speaker 02

  So from the lowest subscription tier.

• 44:05Jason Calacanis?

  Yeah.

• 44:05Speaker 02

  Um, I, I think it's, um, uh, my, it's something like sixty percent of our customers.

• 44:12Jason Calacanis?

  Yeah. I'm hearing that more and more often, that people are willing to pay the overages because they're getting so much value. And I think that's the future of the businesses. People are looking at it going like I am. Well, if I'm paying six hundred dollars and if you token max to six thousand a year, but this is a five hundred thousand dollar piece of software, I don't care. I'm still paying somewhere between point one percent and one percent of what I would have paid three years ago. Who cares? Go for it.

• 44:45Jason Calacanis?

  So.

• 44:45Speaker 02

  Yeah, what we're seeing is everything is about moving, moving fast.

• 44:49Jason Calacanis?

  Yeah.

• 44:49Speaker 02

  And, and they, more AI usually lets you move much faster. So this spend is usually worth it.

• 44:55Jason Calacanis?

  Do your customers, a final question for you, because I'm starting to see this now, where multiple people in the organization try to solve the same software problem and they're competing with each other. So like this Intranet I'm talking about, we built one for Japan.

• 45:11Speaker 02

  Yeah.

• 45:11Jason Calacanis?

  But somebody built the US one. So now I have two pieces of software. So I said to the two different people, do we have, did you guys fork each other's code? Or they're like, no, we just built two different lovable projects. And I'm like, is that the right thing to do? Because you went faster and I had two swings at bat, two different intelligent, brilliant people making their version of the software. But you would never have done that in the previous way of building software. You would have one track of software and you would be building Frank it's software where you'd be trying to get all the needs into it from the two different groups.

• 45:49Speaker 02

  Uh, yeah, I'm actually a huge fan of very rapid experimentation.

• 45:54Jason Calacanis?

  Yeah.

• 45:54Speaker 02

  And I, I have a story where for a while I worked at a place called CERN where they do particle physics. It's pretty here in Central Europe, right? Uh, and that's where I was introduced to this concept of co-opetition, where they have two actually quite isolated teams working on the same particle accelerator, but different places on it. And then they don't share their results until they publish. And that way they, uh, they can kind of over time learn what's working best in the different organizations.

• 46:25Jason Calacanis?

  Yes.

• 46:25Speaker 02

  But you don't get stuck in a local minimum. And it's, you know, free markets work extremely well because of competition and they, they do that in academia as well. And now since the engineering is less of the bottleneck, it's more the question of what is the right thing to build? I think it's a great thing to have, if you have the sufficiently many humans, right? To do, to try to attempt the solving the same problem in different ways. And then if you do that on lovable, what I like to do is I, I bring up a new project or one of the projects and I, I say, hey, can you go and check out this other one and take this, these three things that I really like and bring them, bring them over here and maybe even run a split test, run an experiment to see.

• 47:04Jason Calacanis?

  Love it.

• 47:04Speaker 02

  If it's improved, improving the metrics for, for our customers we're trying to serve.

• 47:08Jason Calacanis?

  Did you see somebody used Fable to build Fortnite? And.

• 47:12Speaker 02

  I've seen this 3D, some of the 3D games, yeah.

• 47:14Jason Calacanis?

  Yeah. What is your take on, you know, this latest version from Anthropic Fable? I know they're a part, or I assume they're a partner, I don't know that.

• 47:22Speaker 02

  Yeah, we use Fable as well as one of the models, yeah, in lovable.

• 47:25Jason Calacanis?

  What do you think of it in terms of compared to the last generation? Faster, better, both? Yeah. Is it a massive step function? Yeah.

• 47:35Speaker 02

  What I've seen is that it can, in the first attempt, create very sophisticated things that look really good. Then as you're evolving, right? It's, it's still the same thing where you as a human, you have to think, you have to often be planning together with your agent about what is the right thing to do. And, and that's more, that's again, more of the bottleneck. Whereas more intelligence is on some tasks, it's great.

• 48:01Jason Calacanis?

  Yeah.

• 48:01Speaker 02

  Like it creates really beautiful things, 3D games, for example. But on figuring what to, what to build, figuring, figuring out what are the right strategic directions or experiments you should run to improve the outcomes for your business? That's, uh, that's not changing as fast. It's the humans knowing how to use the tool to get the, and to plug in all the right data to be able to take the right decisions for taking your product forward and to take your business forward.

• 48:27Jason Calacanis?

  Listen, I love the product, but even more than I love the product and you as a founder, I love the outcome. The outcome for business is extraordinary. So anybody who's listening, lovable is absolutely worth your time. Don't wait, just put it on your corporate card and start building. That's my message. Just start building with lovable. It's an incredible product and congratulations on being reborn six times. Cause every six months you had a hundred million in revenue, it seems. And then everybody says lovable is dead because the new foundation model is so good. But you keep studying your customer and you keep somehow surviving and thriving. So congratulations as an entrepreneur.

• 49:10Speaker 02

  Thank you so much, Jason. I enjoyed that chat. I hope you enjoy the rest of your stay here in Paris.

• 49:15Jason Calacanis?

  It's pretty great. And the Palace of Versailles is so impressive, huh? Someday we'll be building this with lovable and Optimus Robots.

• 49:22Speaker 02

  I'm looking forward to it.