Andrew Feldman on Building a Chip 58x Larger Than Nvidia's

Andrew Feldman, Co-Founder and CEO of Cerebras Systems, joins Molly O'Shea at the RAISE Summit in Paris. Recorded 2 months after Cerebras went public at a $56B valuation and popped to roughly $95B on its first day, this conversation covers the $20B+ OpenAI deal, why inference is the new battleground, the state of the AI data center build-out, and Feldman's take on the circular deals reshaping the industry. We also get into what it means to create 1,000 millionaires, how co-design between hardware and software actually works, data centers in space, and why Feldman thinks AI could mean the next generation never knows anyone who dies of cancer. Cerebras (Nasdaq: CBRS) builds the WSE-3, a single wafer-scale chip with 4 trillion transistors and 900,000 cores, and the CS-3 system it powers. Special thank you to Brex, MongoDB, & AssemblyAI for helping make this RAISE AI Summit mini-series in Paris, France happen. Chapters below. Sourcery covers the people building the future across AI, hardware, and the private and public markets, subscribe for more. Andre Feldman: https://x.com/andrewdfeldman Molly O’Shea: https://x.com/MollySOShea Sourcery: ⁠https://x.com/sourceryy 𝐄𝐏𝐈𝐒𝐎𝐃𝐄 𝐋𝐈𝐍𝐊 YouTube: ⁠https://youtu.be/k9UX2fVGhsI⁠ https://youtu.be/k9UX2fVGhsI 𝐒𝐏𝐎𝐍𝐒𝐎𝐑𝐒 • Brex https://brex.com/sourcery—The modern finance platform, combining the world’s smartest corporate card with integrated expense management, banking, bill pay, & travel. https://brex.com/sourcery • MongoDB https://mongodb.com/ai–Millions of developers and more than 65,200+ customers across industries, including ~75% of the Fortune 100, rely on MongoDB for their most important applications. With integrated capabilities for operational data, search, real-time analytics, & AI-powered data retrieval, MongoDB helps organizations everywhere move faster, innovate more efficiently, & simplify complex architectures. https://mongodb.com/ai • AssemblyAI http://assemblyai.com/sourcery–Millions of developers use AssemblyAI to power their voice ai applications and features. One API gives you access to best-in-class speech-to-text, voice agent, and speech understanding models for both pre-recorded and real-time audio. Granola, ClickUp & HeyGen are scaling with AssemblyAI - get $50 of free credits today at http://AssemblyAI.com/sourcery http://assemblyai.com/sourcery 𝐓𝐈𝐌𝐄𝐒𝐓𝐀𝐌𝐏𝐒 (00:00) Andrew Feldman, Co-Founder & CEO at Cerebras Systems (00:49) Why hardware suddenly became the coolest industry in tech (01:51) What changed at Raise AI Summit (03:01) Inside the $20 billion Cerebras - OpenAI deal (05:50) What actually changes two months after an IPO (06:32) Turning 1,000 employees into millionaires (07:52) Staying sane during an AI gold rush (10:44) Life after the IPO plateau (11:45) The truth about the global data center shortage (12:56) Why data centers are borrowing jet engines for power (14:44) Are data centers really headed to space? (15:37) The shift to designing chips and software together (17:39) The biggest misconception about co-designing chips and software (18:31) Inside SpaceX's multi-billion dollar AI deals (20:06) NVIDIA's playbook for locking out competitors (20:54) The hidden cost behind free tokens (22:52) Andrew's response to Karp's sovereign AI thesis (24:18) AI's biggest win might be curing cancer (26:50) Peptides and biohacking (28:00) How AI could finally fix the broken education problem (29:46) The mentors who shaped Andrew Feldman's career

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

• 0:00Speaker 00

  The demand for AI has outpaced everybody's expectation, everybody's forecast. And so, everybody's chasing, they're chasing chips, or they're chasing memory, or they're chasing data centers. OpenAI, we announced in January, a huge partnership, one of the biggest deals done in Silicon Valley history. We'll be doing more than $20 billion with hardware for them over the next several years. I'm concerned that there are ways frequently for Nvidia to exercise market strength. There are ways for Nvidia to use their balance sheet to limit competition. We have a chance for our children or the next generation, not only to not die from cancer, but to not know anybody who died from cancer.

• 0:49Molly O'Shea?

  Andrew Felvin, welcome to Sorcery.

• 0:51Speaker 00

  Well, thank you so much for having me.

• 0:53Molly O'Shea?

  We are out here in Paris at Rais.

• 0:56Speaker 00

  Pretty okay, huh?

• 0:57Molly O'Shea?

  It's pretty okay. I also heard you're one of the most popular people here.

• 1:03Speaker 00

  That would be first in my life. So, it's nice to, nice of you to say.

• 1:09Molly O'Shea?

  A big theme, though, is, and we were, we were talking about this just off camera, is hardware is cool. Semiconductors are cool. Everything is in fashion now.

• 1:17Speaker 00

  We are in fashion, we're in demand, we're, we're hard to get.

• 1:22Speaker 00

  It's, uh, it's a big change. I think what's happened is the demand for AI has sort of outpaced everybody's expectation, everybody's forecast. And so, everybody's chasing. They're chasing chips, or they're chasing memory, or they're chasing data centers. There's an opportunity to invent new things, different architectures. It's really a time of sort of a Cambrian explosion of, of, of ideas. That's really fun.

• 1:51Molly O'Shea?

  So you were at Rais last year. I remember this because I think you had the biggest booth here. There was a fence around it.

• 1:57Speaker 00

  Yeah.

• 1:58Molly O'Shea?

  And a lot of people. What is the biggest difference between last year and this year?

• 2:03Speaker 00

  Well, I, I think last year was their first year, right? And I, I think, uh, there are more people here.

• 2:11Speaker 00

  There are more participants, so there are more attendees, the more companies participating. I think people are participating in a bigger way. I think the dinner last night at the

• 2:22Molly O'Shea?

  Secret location?

• 2:23Speaker 00

  A secret location called Versailles was sort of awesome. You know, we spent a lot of time in the digital world and the people, we talk about AI. To go look at something that illiterate masons made 400 years ago, right? Is and to sit in it and to enjoy the grandeur is extraordinary, right? This wasn't AI, this wasn't EDA design or CAD or these guys with pen and paper communicating with, you know, masons and other tradesmen who couldn't read. And they built something unbelievably beautiful and that was really fun.

• 3:02Molly O'Shea?

  And so you're going to be on stage this year. What are you mainly going to talk about?

• 3:05Speaker 00

  I'm on stage with Sachin from OpenAI. You know, we announced in January a huge partnership, one of the biggest deals done in Silicon Valley history. We'll be doing more than $20 billion of hardware for them over the next several years. We'll talk a little bit about deploying hardware and fast AI and how important fast inference is in the emerging inference AI landscape.

• 3:34Molly O'Shea?

  Inference is a hot topic. Everyone loves inference.

• 3:36Speaker 00

  Yeah, we make AI with training, right? And we use AI with inference. And so as the models and as the AI we made becomes useful, everybody wants to use it. And inference is the mechanism through which we use it. And so now we have smart, smart AI, people want to use it. And when they want to use it, they want to use it and they want it to be fast. And that's sort of where we come in and where the fast is not by a little bit, but by 20x. And so everybody's using their AI, they're trying new things, they're deploying, you know, GPT or Claude Code or one of these supermodels and

• 4:20Speaker 00

  It's sort of an explosion of building, of trying new things, of a new way to work. It's pretty fun.

• 4:28Molly O'Shea?

  So we're nearly two months after your IPO. And there was one post that I thought was really cool. You posted that you had a very large chip on your shoulder.

• 4:43Molly O'Shea?

  And it was quite literal and physical.

• 4:46Speaker 00

  I hoped that, you know, now that we're running a public company, that I wouldn't lose sort of the self-deprecating humor, whatever that I enjoy, that sort of tone in my social posts. And so we put a giant chip. We put this sort of on my shoulder like this. And we built a harness for it.

• 5:12Speaker 00

  Yeah, that was a fun one.

• 5:16Speaker 00

  You know, I think that people assume that as a CEO or of any size or an entrepreneur, that it's sort of always peaches and cream. And it's just not the case. There's an enormous amount of hard work. There's sacrifice that you make and that your family makes. They see you less. And it's not for a little bit. It's not like a weekend or two weeks in a row. You work hard. It's for years. And so sharing that a little bit is something I thought would be well received.

• 5:50Molly O'Shea?

  So what's been the biggest difference for you post-IPO?

• 5:54Speaker 00

  The number of people who want something.

• 5:57Molly O'Shea?

  Really?

• 5:57Speaker 00

  Yeah, has exploded of one form or another. And we get a little better at triaging those

• 6:08Speaker 00

  between my executive assistant and chief of staff. And just if you get 80 emails a day of different people asking you for something, that's not work. That's just sort of this range of people who want something of one form or another to meet you, your time, for you to present, for you to donate to their cause, for you to... Whoa. That was a little unexpected.

• 6:32Molly O'Shea?

  Your last company, you helped create 100 millionaires. This company, you have, I don't know, countless more.

• 6:42Speaker 00

  Maybe a thousand.

• 6:43Molly O'Shea?

  Maybe a thousand?

• 6:44Speaker 00

  Maybe a thousand.

• 6:44Molly O'Shea?

  Maybe in the future, a thousand? Right?

• 6:48Speaker 00

  At IPO, it was more, it was about a thousand.

• 6:51Molly O'Shea?

  Would that be investors and employees?

• 6:54Speaker 00

  Employees.

• 6:55Molly O'Shea?

  Really?

• 6:55Speaker 00

  Current and former.

• 6:56Molly O'Shea?

  Okay, wow. And so what lesson do you learn from that as a CEO? Like, what is in your mind?

• 7:03Speaker 00

  I think a couple of things. I think to do the job, you gotta love to build. I think making money is really great and making money for people you care about is really, really great. And when you get a chance to deliver for people who bet on you, who bet chunks of their career, right, your investors, it's great to deliver for them. They bet on you, but they're diversified. They bet on you and 20 other companies. When someone bets five or seven years of their career, and a career is 30 years, right? They're betting a sixth of their professional career.

• 7:40Speaker 00

  And when you get to deliver for them and they get to achieve the financial goals that they wanted to, that's a great feeling and what I'm proud of every day.

• 7:52Molly O'Shea?

  It's a very selfless position on that. I mean, it's really interesting because today, I mean, in the backdrop, we are in a hyper, super cycle, whatever you want to call it, of AI. And so these companies that are coming up, whether they're in semiconductors or they're in, I don't know, models or, you know, coding agents, there's a lot of companies that are rising up really fast and hitting that billion-dollar mark. Some are having liquidity events like OpenAI and Anthropic to come. But others are getting that paper markup and they're seeing that kind of wealth creation event. How do you maintain a healthy mindset around that?

• 8:32Speaker 00

  I think you bring it. It's not a change, right? You, for the type of people I love working with, they like building stuff and they like building hard stuff when it paid a little, when it was out of fashion, you know? When hardware was uncool, they were still building hardware because that's what they like to build. And now that it's in fashion, they like to build hardware. And they're sort of even keeled about that, that their passion is the building. And I think in Silicon Valley, which sort of is what I know, that chasing money is not the path to money.

• 9:13Speaker 00

  The path to happiness is working on projects you like with colleagues that are interesting for people with integrity. And if you do that, the money will come. But even more importantly, you work on things you like. And you'll work with people you learn a little something from, and you can teach a little something from. And if that's the way you said about pursuing your career, I think when things are really bad, you're on even keel. And when things are really good, you're on even keel, because you're enjoying what you're doing.

• 9:45Molly O'Shea?

  This episode is brought to you by Brex, my favorite. You become what you spend on, and I refuse to spend my time on work that shouldn't exist. Expense reports, receipt chasing, and manual closes. The companies building what's next, from Vercel, OpenAI, Anthropic, Granola, and Deepgram, all made the same call. They all run on Brex. Brex is the intelligent finance platform that combines cards, expenses, and banking into a single stack with agentic finance built in. AI agents that handle expenses automatically, enforce policy before spend happens, and close your books in minutes. That's why sorcery runs on Brex, so I can spend time on building and not busy work. It's time

• 10:30Molly O'Shea?

  to get Brex AF. Learn more at brex.com/sorcery. That's B-R-E-X dot com slash S-O-U-R-C-E-R-Y. Bye. So, looking forward, I'm sure this is also just a mark in your journey, because you're a builder. So what are you most looking forward to over the next couple of months, as we set across this year?

• 10:56Speaker 00

  Look, getting to an IPO is not the end of a journey. It's sort of a plateau. It's sort of the arrival at corporate adulthood. It is the achieving one plateau so that you can climb others. And our opportunity has gotten bigger. We have more resources. We have, we're better recognized. We can reach more people. And we can sort of prosecute our vision and our ambitions with more fuel. And so that's what we're excited about every day. You know, building more chips, building more data centers, inventing technology that moves the industry forward.

• 11:41Speaker 00

  That's what drives us and gets us out of bed every day.

• 11:45Molly O'Shea?

  I think I was listening to a Harry Stebbings episode that you did and talking about data centers and the demand for them and how we're actually not trying to meet future demand. We're actually just really behind.

• 11:58Speaker 00

  We are behind.

• 11:59Molly O'Shea?

  On where we are. So could you explain where we are with the data center build out?

• 12:04Speaker 00

  Right, so what happened is is data centers had historically moved at sort of the speed of real estate, right? Somebody would decide to build a building and two years later, after permits and they poured concrete and the building would go up. And two years ago, nobody cared about AI.

• 12:23Speaker 00

  Two years ago, we were at the beginning of this and the AI explosions happen so quickly. There's so much demand for compute. We've outstripped the demand for for compute, for memory. And where do these things go? They go to these buildings and we haven't made them fast enough. And so people are chasing data centers around the around the world. And that's what's happening. And so it is a major limitation for for everybody right now.

• 12:56Molly O'Shea?

  We just had Tony Kim on and we were talking about the new architecture of data centers. So how are you working with other companies, whether it's through your build outs, creating the right stack and architecture?

• 13:10Speaker 00

  Sure. So, you know, the interesting about, you know, data centers hadn't changed a lot in 20 years and a lot of the infrastructure in them hadn't changed. I mean, the the generators that we use for backup have been unchanged for about 20 years. The type of batteries we use for backup, the the chillers and the the CDUs and the and suddenly there's this sort of intense demand and and sort of people are looking to innovate and they're using fuel cells and guys are using jet engines like boom to to generate power for these data centers and. The turbines are being rethought of.

• 13:51Speaker 00

  And so there's sort of an innovative push in the data center. For us, while we build this sort of super big chip, the chip that's like fifty-eight times larger than any other chip, it goes in a server. It goes in a metal enclosure. It's about the size of a fridge for a dorm room. A little fridge. And we put a couple of those in a standard rack. And so the physical requirements weren't very different from if you're going to deploy a competitor's product. What Tony's really talking about is sort of, these buildings were sort of unimproved for a generation.

• 14:34Speaker 00

  And now they're part of a factory that makes AI. And people are trying to optimize every part of that factory.

• 14:44Molly O'Shea?

  Yeah, and now they're also putting them in space.

• 14:47Speaker 00

  Yeah, well, they're talking about putting them in space.

• 14:51Speaker 00

  I think like a lot of technology, you talk about it for a long time before it happens.

• 14:55Molly O'Shea?

  Do you have plans?

• 14:57Speaker 00

  You know, I'm, we are really good for space because one of the hardest problems in space is getting all these little chips to talk to each other. And because we're a big chip, we don't have that problem. I don't think we're in danger in the near term of having a data center in space. I think it's more than five years away.

• 15:19Molly O'Shea?

  Five years?

• 15:20Speaker 00

  Five years.

• 15:21Molly O'Shea?

  Okay.

• 15:21Speaker 00

  And that's a long time in our world, right? I mean, three years ago, nobody was using AI. Right? And so I think we got a lot of work in building data centers on Earth before we actually have big production data centers in space.

• 15:37Molly O'Shea?

  I'd love to talk about how chip design has changed.

• 15:42Speaker 00

  Sure.

• 15:43Molly O'Shea?

  Co-design has become an important part of, how do you create that kind of platform for the next three years? Because you're building for the next three years. So how do you think about that? And how do you go about chip design?

• 15:55Speaker 00

  Well, I think historically, you made chips and you ran software on them. And

• 16:04Speaker 00

  There wasn't surprisingly a close interaction. Because there was a layer called an operating system that lived between the chip and the software. And so, you know, Intel and AMD made chips and people wrote software for the operating system or for the chip. AI has gotten so large and speed is so important that what they're doing is they're thinking about sort of the design together. What changes could we make in software that would advantage the hardware or as we're designing the hardware, what changes could we make that would make the software easier to run?

• 16:48Speaker 00

  And so they're being designed sort of at the same time. And like anything, when you sort of design things together, the advantages are enormous. And so this is something that's really taken shape right now. And one of the advantages of our relationship with OpenAI is we get to see exactly where the frontier is going and we get a chance to roll that into our designs. One of the advantages Google has is their TPU can be designed in collaboration with the team building Gemini or the team at DeepMind. And so they can, they can inform their choices back and forth.

• 17:32Speaker 00

  And that's an enormously powerful thing that is surprisingly relatively new in our space.

• 17:39Molly O'Shea?

  What do you think that the biggest misconception with that process is and the challenges are?

• 17:44Speaker 00

  Well, I think that the misconception is that it's easy and all you need to do is get in a room. It's a, it's a very hard problem. You know, the software guys think one way. The hardware guys think a slightly different way. You know, anything you do to make it easier to write the software makes it harder to do the hardware. Right? And these are really hard trade-offs. And so bringing them together and means these sort of compromises where it will be harder here to make it easier here. And that means somebody's schedule is going to be impacted. Somebody's got to add resources.

• 18:28Speaker 00

  Those discussions are enormously difficult.

• 18:31Molly O'Shea?

  I'm really curious because I come from an outside perspective. You have an inside perspective. There's a lot of big deals that are being thrown around left and right. And I don't know what's actually under the headlines. So when SpaceX comes out and they say they now have multi-billion dollar deals with Google and also with Reflection. Like, what does that actually mean? Like, what are they selling them?

• 18:54Speaker 00

  Tough to tell.

• 18:56Speaker 00

  No, it's tough to tell inside as well.

• 18:58Molly O'Shea?

  Really?

• 18:58Speaker 00

  Yeah, I think there have been announced some sort of deals that didn't have teeth.

• 19:07Speaker 00

  Deals that could have teeth later.

• 19:11Speaker 00

  I think

• 19:15Speaker 00

  X

• 19:17Speaker 00

  had available capacity. And you gotta ask why they had available. They had available capacity because their Grok model wasn't used very much.

• 19:28Speaker 00

  So they had these GPUs that were sitting around, and that's a bad idea. And so they sold a whole block of them, or leased a whole block of Anthropic. And they looked up and said, whoa, that's a pretty good idea. Right, we had all these GPUs. Our model wasn't a success, but whoa, we can have a great business by sort of stepping into what is a constrained market. Very hard to get lots of GPUs and lease these. And then they looked around and said, well, what else can we, who else can we lease to? And so that's how it started. Now, the specifics of those deals, I'm not super familiar with.

• 20:06Molly O'Shea?

  Are you concerned at all about the circular deals that are going on?

• 20:12Speaker 00

  I'm concerned that there are ways frequently for Nvidia to exercise market strength. Right, there are ways for Nvidia to

• 20:28Speaker 00

  To use their balance sheet to limit competition. Right, that if they invest in a NeoCloud, right, the NeoCloud is less likely to use a non-Nvidia chip. If they invest in a model builder, there's pressure not to use other people's chips. That's what I'm more worried about.

• 20:54Molly O'Shea?

  Yeah, this is happening in the token world with all the free tokens that are being offered to the startups.

• 20:59Speaker 00

  I, that's exactly right. I think these are, these are drug pushers. Here's a little girl, try a little bit, just a little bit. And I think what the startups should do is, you know, they should take it and then never be dependent. Take some from AMD and come to us and see if we can get you some as well and avoid dependence. That never ends.

• 21:26Molly O'Shea?

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• 22:08Molly O'Shea?

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• 22:51Molly O'Shea?

  I mean, this is actually a good transition into something that Karp said not too long ago on CNBC. He was pretty much talking about sovereign AI and how every company should own the full stack. And so whether it's their data for their products and everything in between and models too, because you don't want to sell that, then the models will recreate it and then pump out a new Figma. How do you feel about sovereign AI and this like this shift over to owning the full stack?

• 23:20Speaker 00

  Well, I think the notion of not being dependent. I mean, you shouldn't be dependent on Nvidia. You shouldn't be dependent on one model maker. I think that rarely works out well. Right? What you'd like to be as a nation or as a big company is you'd like to have choices. And I don't know if you need to own all the stack, but you like choices at each layer of the stack. I think a different way to think about what Alex said is, you know, you want to think about where your advantage is, right? If you're really, you

• 24:01Speaker 00

  have unique data, be sure you don't give that away. Right? Be sure you have multiple choices in different parts of the stack, but you get the credit for your data. And it doesn't help make somebody else's model better.

• 24:16Molly O'Shea?

  As we look forward, I guess more on the macro lens, the proliferation of AI and everything that we're be able, we're able to now create and build and do, what are you excited about on the externalities that come with all of this?

• 24:33Speaker 00

  Okay, I think that we have a chance for our children or the next generation, not only to not die from cancer, but to not know anybody who died from cancer.

• 24:50Speaker 00

  I think that is a real achievable goal in 25 years. Wouldn't that be something? You know, when we think about what AI can do, writing better code is cool. And there's a huge market for that. But I think what it can do to better humanity is rid us of the number one killer of adults. And I think, you know, that's when I think of what we're all doing this for. It's an outcome like that. You know, pancreatic cancer had a huge breakthrough recently.

• 25:31Speaker 00

  I think the opportunity for breakthroughs right now has never been better. And AI is an extraordinary tool in pursuit of knocking down major, major human killers. Right? I mean, if you think, if you took out cancer and you took out automobile accidents, you're taking out huge numbers of deaths here. And you say to yourself, well, that's a lot of good that we did. And I think, you know, self-driving, humans are terrible drivers. Horrible. Horrible drivers. Horrible. It's not just when we're 16 or 18, or when we're not paying attention, or our parents

• 26:16Speaker 00

  in their 80s, or, you know, it's, we don't pay attention. We're on the phone, we're talking to our wife, we're worried about work. That's even before people drink or do all sorts of things that are obviously bad. But we're just not good drivers. And machines can drive better than we can today. And so that's the number one killer of people, whatever, 15 to 40 is car accidents. You take that out through self-driving, you take out a major killer like cancer, you're going, whoa, that's a pretty good 20-year run of technology.

• 26:49Molly O'Shea?

  Are you a peptide fan?

• 26:50Speaker 00

  I'm a peptide fan.

• 26:51Molly O'Shea?

  You are?

• 26:52Speaker 00

  Yeah. I think, not in the specifics of there is a peptide, but rather in that our opportunity to advance our knowledge about the biology of our bodies and how to achieve performance and how to achieve longevity.

• 27:13Speaker 00

  We're just beginning.

• 27:14Molly O'Shea?

  Yeah.

• 27:14Speaker 00

  And we're going to make some big strides, whether it's with peptides or something else, or, you know, the next GLP-1 inhibitor, whatever. We're going to make giant strides.

• 27:25Molly O'Shea?

  Yeah, it's been really cool to see all the new drug discoveries and new drug discovery companies. Brian Armstrong just came out with this company called New Limit. That's one of them. I think their goal is to eradicate all diseases.

• 27:38Speaker 00

  Yeah.

• 27:39Molly O'Shea?

  It's a good one.

• 27:39Speaker 00

  Right, I mean, even if that's a little hubris, I mean, it wasn't even hubris that was thinkable a decade ago.

• 27:47Molly O'Shea?

  Yeah.

• 27:47Speaker 00

  Right? I mean, we're now in a realm where, wow, that is sort of crazy big, but not insane. Right? I mean, how cool is that?

• 27:57Molly O'Shea?

  Yeah, I mean, well, a lot of people like to talk about the doomerism of AI, but I think we're entering a new mix of talking about the actual outcomes with it. And so to your point of what you're talking about, whether it's with AVs or drug discovery, it's really good.

• 28:14Speaker 00

  I think the problem with the doomers is they're only looking at one side of the ledger. Right? I think to look at this with clear eyes, you've got to look at both sides of the ledger. You've got to say, look, we're going to use a lot of power. It's true. And AI has some real risks. It's true. And on the other side of the ledger, here's some things it can do really differently. And here's some things it can do that... Take education, right? We've known for 2,000 years the right way to educate children, and we never do it.

• 28:45Speaker 00

  Ever. I mean, we knew that the right way to educate Alexander the Great was to have a tutor. And the smartest tutor Aristotle was. And that you teach each child differently. And you think about their way of learning. And we never do that. You throw them in a classroom. You teach to some sort of middle level. Each child does not get sort of any different teaching for their different way of learning. With AI, we can do that. We can get you a tutor that's right for you. And what's more, the tutor can be running in the background saying, look, 3% of students make this type of error. And the best way to teach them to overcome this weakness is with this approach. Right? How cool is that?

• 29:28Speaker 00

  I mean, we've been screwing this up for 2,000 years. And now we can bring it to every child. Right? You can put it on the positive side ledger. And look at clear eyes at both the negative and the positive and see if we're doing right by society.

• 29:45Molly O'Shea?

  So one of our sponsors is Brex. And I bring this up because our questions around performance. They are all about spending smarter, moving faster. But performance in terms of like for your finances, I ask this question in terms of your personal side of things. I do believe that performance for individuals is kind of who you surround yourself with or who you're inspired by or mentored by. You know, you've had a great run at building companies and have had great success. So I'm really curious who those people are for you.

• 30:16Speaker 00

  There was, there are a couple mentors. There's, there was a venture capitalist named Pierre Lamont. And he's now in his 90s. He invested in us at, at Cereberus when he was in the ripe age of 84.

• 30:29Molly O'Shea?

  Oh, my gosh.

• 30:30Speaker 00

  And was on our board. And he's forgotten more about making chips than I'll ever know.

• 30:38Speaker 00

  There was, there's a CEO, former CEO named Mark Leslie. He was CEO of Veritas. They invented the file system. And these were sort of wise people. And they had extraordinarily high standards and they.

• 30:59Speaker 00

  They taught me a lot about being a leader.

• 31:03Speaker 00

  About demanding a great deal from myself and from others. They were people who were exceptional. I think, sort of on a day-to-day basis, sort of my co-founders, there are five of us. Five is, in almost every case, too many founders.

• 31:22Speaker 00

  They all worked, we all worked together at my last company. I've learned an enormous amount from them. They challenged me and I'm excited to think with them.

• 31:39Speaker 00

  And that's an okay way to go into work every day.

• 31:42Molly O'Shea?

  It's amazing. Well, thank you so much, Andrew. It's a pleasure to have time. I know we covered a lot of ground with this conversation.

• 31:50Speaker 00

  We covered a lot of ground.

• 31:50Molly O'Shea?

  So many topics. I didn't think we were going to get to peptides, I'm going to be honest. I just had to ask.

• 31:57Speaker 00

  Well, thank you for having me on your show. I really appreciate it.

• 31:59Molly O'Shea?

  Thank you. Huge thank you to the entire Raze team for an incredible event. And thank you to Brex, MongoDB, and Assembly AI for making this trip and series possible. If you enjoyed this conversation, you're going to love the rest of the Raze series with Tony Kim from BlackRock, Scott Wu from Cognition, Andrew Feldman from Cerebras, Rodrigo Yang from Saama Nova, Michael Hurlston from Lumentum, CJ Desai from MongoDB, and many, many more, like our hot takes that we did at a secret location that you can find on X, YouTube, and Instagram. Subscribe to Sorcery on YouTube for more conversations with the people shaping AI and join the free newsletter, you can also do paid, at sorcery.vc for weekly insights

• 32:43Molly O'Shea?

  on AI, robotics, enterprise software, consumer, semiconductors, did I say AI? AI again, and everything that's coming next, like funding announcements and all big things in tech. Thank you, bye.