Podcasts about a16z

Crypto News: Bitcoin and altcoins see upside in price as Terraform sues Jane Street and market manipulation gets exposed. Ethereum unveils new 'Strawmap' roadmap adding private ETH transactions, quantum-proof security, and massive L2 scaling. Tether invests $200 million in digital marketplace Whop to expand stablecoin payments.Brought to you by ✅ VeChain is a versatile enterprise-grade L1 smart contract platform https://www.vechain.org/ 

SummaryIn this conversation, George discusses TaxNova, an AI-powered platform that automates the R&D tax credit process for tech companies. He shares his personal journey as a founder, the role of AI in streamlining tax claims, and the challenges faced in the traditional claims process. George emphasizes the importance of efficiency and compliance, the significance of funding and accelerator experiences, and the market potential for TaxNova. He also addresses the collaboration with tax advisors and the unique advantages of being an outsider in the industry.TakeawaysTaxNova automates the R&D tax credit process for tech companies.The founder's journey is deeply personal and reflects their strengths.AI is transforming paperwork-heavy tasks in tax claims.The claims process is often inefficient and burdensome for companies.Efficiency and compliance are critical in tax claims.Funding from angels and operators is crucial at the pre-seed stage.The market for R&D tax credits is substantial and growing.Collaboration with tax advisors is essential for final submissions.Understanding the target audience is key to market positioning.Being an outsider can provide unique insights and advantages.Chapters00:00 Introduction to TaxNova and Its Purpose03:19 The Founder's Journey and Motivation06:09 The Role of AI in Tax Credit Claims08:56 Understanding the Claims Process12:02 Efficiency and Quality in Tax Claims15:06 Funding Journey and Accelerator Experience17:41 Milestones and Future Goals20:34 Market Positioning and Competition23:40 Collaboration with Tax Advisors26:22 Target Audience and Market Size29:26 Challenges and Unfair Advantages This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit uvcmedia.substack.com

Tickets for AIEi Miami and AIE Europe are live, with first wave speakers announced!From pioneering software-defined networking to backing many of the most aggressive AI model companies of this cycle, Martin Casado and Sarah Wang sit at the center of the capital, compute, and talent arms race reshaping the tech industry. As partners at a16z investing across infrastructure and growth, they've watched venture and growth blur, model labs turn dollars into capability at unprecedented speed, and startups raise nine-figure rounds before monetization.Martin and Sarah join us to unpack the new financing playbook for AI: why today's rounds are really compute contracts in disguise, how the “raise → train → ship → raise bigger” flywheel works, and whether foundation model companies can outspend the entire app ecosystem built on top of them. They also share what's underhyped (boring enterprise software), what's overheated (talent wars and compensation spirals), and the two radically different futures they see for AI's market structure.We discuss:* Martin's “two futures” fork: infinite fragmentation and new software categories vs. a small oligopoly of general models that consume everything above them* The capital flywheel: how model labs translate funding directly into capability gains, then into revenue growth measured in weeks, not years* Why venture and growth have merged: $100M–$1B hybrid rounds, strategic investors, compute negotiations, and complex deal structures* The AGI vs. product tension: allocating scarce GPUs between long-term research and near-term revenue flywheels* Whether frontier labs can out-raise and outspend the entire app ecosystem built on top of their APIs* Why today's talent wars ($10M+ comp packages, $B acqui-hires) are breaking early-stage founder math* Cursor as a case study: building up from the app layer while training down into your own models* Why “boring” enterprise software may be the most underinvested opportunity in the AI mania* Hardware and robotics: why the ChatGPT moment hasn't yet arrived for robots and what would need to change* World Labs and generative 3D: bringing the marginal cost of 3D scene creation down by orders of magnitude* Why public AI discourse is often wildly disconnected from boardroom reality and how founders should navigate the noiseShow Notes:* “Where Value Will Accrue in AI: Martin Casado & Sarah Wang” - a16z show* “Jack Altman & Martin Casado on the Future of Venture Capital”* World Labs—Martin Casado• LinkedIn: https://www.linkedin.com/in/martincasado/• X: https://x.com/martin_casadoSarah Wang• LinkedIn: https://www.linkedin.com/in/sarah-wang-59b96a7• X: https://x.com/sarahdingwanga16z• https://a16z.com/Timestamps00:00:00 – Intro: Live from a16z00:01:20 – The New AI Funding Model: Venture + Growth Collide00:03:19 – Circular Funding, Demand & “No Dark GPUs”00:05:24 – Infrastructure vs Apps: The Lines Blur00:06:24 – The Capital Flywheel: Raise → Train → Ship → Raise Bigger00:09:39 – Can Frontier Labs Outspend the Entire App Ecosystem?00:11:24 – Character AI & The AGI vs Product Dilemma00:14:39 – Talent Wars, $10M Engineers & Founder Anxiety00:17:33 – What's Underinvested? The Case for “Boring” Software00:19:29 – Robotics, Hardware & Why It's Hard to Win00:22:42 – Custom ASICs & The $1B Training Run Economics00:24:23 – American Dynamism, Geography & AI Power Centers00:26:48 – How AI Is Changing the Investor Workflow (Claude Cowork)00:29:12 – Two Futures of AI: Infinite Expansion or Oligopoly?00:32:48 – If You Can Raise More Than Your Ecosystem, You Win00:34:27 – Are All Tasks AGI-Complete? Coding as the Test Case00:38:55 – Cursor & The Power of the App Layer00:44:05 – World Labs, Spatial Intelligence & 3D Foundation Models00:47:20 – Thinking Machines, Founder Drama & Media Narratives00:52:30 – Where Long-Term Power Accrues in the AI StackTranscriptLatent.Space - Inside AI's $10B+ Capital Flywheel — Martin Casado & Sarah Wang of a16z[00:00:00] Welcome to Latent Space (Live from a16z) + Meet the Guests[00:00:00] Alessio: Hey everyone. Welcome to the Latent Space podcast, live from a 16 z. Uh, this is Alessio founder Kernel Lance, and I'm joined by Twix, editor of Latent Space.[00:00:08] swyx: Hey, hey, hey. Uh, and we're so glad to be on with you guys. Also a top AI podcast, uh, Martin Cado and Sarah Wang. Welcome, very[00:00:16] Martin Casado: happy to be here and welcome.[00:00:17] swyx: Yes, uh, we love this office. We love what you've done with the place. Uh, the new logo is everywhere now. It's, it's still getting, takes a while to get used to, but it reminds me of like sort of a callback to a more ambitious age, which I think is kind of[00:00:31] Martin Casado: definitely makes a statement.[00:00:33] swyx: Yeah.[00:00:34] Martin Casado: Not quite sure what that statement is, but it makes a statement.[00:00:37] swyx: Uh, Martin, I go back with you to Netlify.[00:00:40] Martin Casado: Yep.[00:00:40] swyx: Uh, and, uh, you know, you create a software defined networking and all, all that stuff people can read up on your background. Yep. Sarah, I'm newer to you. Uh, you, you sort of started working together on AI infrastructure stuff.[00:00:51] Sarah Wang: That's right. Yeah. Seven, seven years ago now.[00:00:53] Martin Casado: Best growth investor in the entire industry.[00:00:55] swyx: Oh, say[00:00:56] Martin Casado: more hands down there is, there is. [00:01:00] I mean, when it comes to AI companies, Sarah, I think has done the most kind of aggressive, um, investment thesis around AI models, right? So, worked for Nom Ja, Mira Ia, FEI Fey, and so just these frontier, kind of like large AI models.[00:01:15] I think, you know, Sarah's been the, the broadest investor. Is that fair?[00:01:20] Venture vs. Growth in the Frontier Model Era[00:01:20] Sarah Wang: No, I, well, I was gonna say, I think it's been a really interesting tag, tag team actually just ‘cause the, a lot of these big C deals, not only are they raising a lot of money, um, it's still a tech founder bet, which obviously is inherently early stage.[00:01:33] But the resources,[00:01:36] Martin Casado: so many, I[00:01:36] Sarah Wang: was gonna say the resources one, they just grow really quickly. But then two, the resources that they need day one are kind of growth scale. So I, the hybrid tag team that we have is. Quite effective, I think,[00:01:46] Martin Casado: what is growth these days? You know, you don't wake up if it's less than a billion or like, it's, it's actually, it's actually very like, like no, it's a very interesting time in investing because like, you know, take like the character around, right?[00:01:59] These tend to [00:02:00] be like pre monetization, but the dollars are large enough that you need to have a larger fund and the analysis. You know, because you've got lots of users. ‘cause this stuff has such high demand requires, you know, more of a number sophistication. And so most of these deals, whether it's US or other firms on these large model companies, are like this hybrid between venture growth.[00:02:18] Sarah Wang: Yeah. Total. And I think, you know, stuff like BD for example, you wouldn't usually need BD when you were seed stage trying to get market biz Devrel. Biz Devrel, exactly. Okay. But like now, sorry, I'm,[00:02:27] swyx: I'm not familiar. What, what, what does biz Devrel mean for a venture fund? Because I know what biz Devrel means for a company.[00:02:31] Sarah Wang: Yeah.[00:02:32] Compute Deals, Strategics, and the ‘Circular Funding' Question[00:02:32] Sarah Wang: You know, so a, a good example is, I mean, we talk about buying compute, but there's a huge negotiation involved there in terms of, okay, do you get equity for the compute? What, what sort of partner are you looking at? Is there a go-to market arm to that? Um, and these are just things on this scale, hundreds of millions, you know, maybe.[00:02:50] Six months into the inception of a company, you just wouldn't have to negotiate these deals before.[00:02:54] Martin Casado: Yeah. These large rounds are very complex now. Like in the past, if you did a series A [00:03:00] or a series B, like whatever, you're writing a 20 to a $60 million check and you call it a day. Now you normally have financial investors and strategic investors, and then the strategic portion always still goes with like these kind of large compute contracts, which can take months to do.[00:03:13] And so it's, it's very different ties. I've been doing this for 10 years. It's the, I've never seen anything like this.[00:03:19] swyx: Yeah. Do you have worries about the circular funding from so disease strategics?[00:03:24] Martin Casado: I mean, listen, as long as the demand is there, like the demand is there. Like the problem with the internet is the demand wasn't there.[00:03:29] swyx: Exactly. All right. This, this is like the, the whole pyramid scheme bubble thing, where like, as long as you mark to market on like the notional value of like, these deals, fine, but like once it starts to chip away, it really Well[00:03:41] Martin Casado: no, like as, as, as, as long as there's demand. I mean, you know, this, this is like a lot of these sound bites have already become kind of cliches, but they're worth saying it.[00:03:47] Right? Like during the internet days, like we were. Um, raising money to put fiber in the ground that wasn't used. And that's a problem, right? Because now you actually have a supply overhang.[00:03:58] swyx: Mm-hmm.[00:03:59] Martin Casado: And even in the, [00:04:00] the time of the, the internet, like the supply and, and bandwidth overhang, even as massive as it was in, as massive as the crash was only lasted about four years.[00:04:09] But we don't have a supply overhang. Like there's no dark GPUs, right? I mean, and so, you know, circular or not, I mean, you know, if, if someone invests in a company that, um. You know, they'll actually use the GPUs. And on the other side of it is the, is the ask for customer. So I I, I think it's a different time.[00:04:25] Sarah Wang: I think the other piece, maybe just to add onto this, and I'm gonna quote Martine in front of him, but this is probably also a unique time in that. For the first time, you can actually trace dollars to outcomes. Yeah, right. Provided that scaling laws are, are holding, um, and capabilities are actually moving forward.[00:04:40] Because if you can put translate dollars into capabilities, uh, a capability improvement, there's demand there to martine's point. But if that somehow breaks, you know, obviously that's an important assumption in this whole thing to make it work. But you know, instead of investing dollars into sales and marketing, you're, you're investing into r and d to get to the capability, um, you know, increase.[00:04:59] And [00:05:00] that's sort of been the demand driver because. Once there's an unlock there, people are willing to pay for it.[00:05:05] Alessio: Yeah.[00:05:06] Blurring Lines: Models as Infra + Apps, and the New Fundraising Flywheel[00:05:06] Alessio: Is there any difference in how you built the portfolio now that some of your growth companies are, like the infrastructure of the early stage companies, like, you know, OpenAI is now the same size as some of the cloud providers were early on.[00:05:16] Like what does that look like? Like how much information can you feed off each other between the, the two?[00:05:24] Martin Casado: There's so many lines that are being crossed right now, or blurred. Right. So we already talked about venture and growth. Another one that's being blurred is between infrastructure and apps, right? So like what is a model company?[00:05:35] Mm-hmm. Like, it's clearly infrastructure, right? Because it's like, you know, it's doing kind of core r and d. It's a horizontal platform, but it's also an app because it's um, uh, touches the users directly. And then of course. You know, the, the, the growth of these is just so high. And so I actually think you're just starting to see a, a, a new financing strategy emerge and, you know, we've had to adapt as a result of that.[00:05:59] And [00:06:00] so there's been a lot of changes. Um, you're right that these companies become platform companies very quickly. You've got ecosystem build out. So none of this is necessarily new, but the timescales of which it's happened is pretty phenomenal. And the way we'd normally cut lines before is blurred a little bit, but.[00:06:16] But that, that, that said, I mean, a lot of it also just does feel like things that we've seen in the past, like cloud build out the internet build out as well.[00:06:24] Sarah Wang: Yeah. Um, yeah, I think it's interesting, uh, I don't know if you guys would agree with this, but it feels like the emerging strategy is, and this builds off of your other question, um.[00:06:33] You raise money for compute, you pour that or you, you pour the money into compute, you get some sort of breakthrough. You funnel the breakthrough into your vertically integrated application. That could be chat GBT, that could be cloud code, you know, whatever it is. You massively gain share and get users.[00:06:49] Maybe you're even subsidizing at that point. Um, depending on your strategy. You raise money at the peak momentum and then you repeat, rinse and repeat. Um, and so. And that wasn't [00:07:00] true even two years ago, I think. Mm-hmm. And so it's sort of to your, just tying it to fundraising strategy, right? There's a, and hiring strategy.[00:07:07] All of these are tied, I think the lines are blurring even more today where everyone is, and they, but of course these companies all have API businesses and so they're these, these frenemy lines that are getting blurred in that a lot of, I mean, they have billions of dollars of API revenue, right? And so there are customers there.[00:07:23] But they're competing on the app layer.[00:07:24] Martin Casado: Yeah. So this is a really, really important point. So I, I would say for sure, venture and growth, that line is blurry app and infrastructure. That line is blurry. Um, but I don't think that that changes our practice so much. But like where the very open questions are like, does this layer in the same way.[00:07:43] Compute traditionally has like during the cloud is like, you know, like whatever, somebody wins one layer, but then another whole set of companies wins another layer. But that might not, might not be the case here. It may be the case that you actually can't verticalize on the token string. Like you can't build an app like it, it necessarily goes down just because there are no [00:08:00] abstractions.[00:08:00] So those are kinda the bigger existential questions we ask. Another thing that is very different this time than in the history of computer sciences is. In the past, if you raised money, then you basically had to wait for engineering to catch up. Which famously doesn't scale like the mythical mammoth. It take a very long time.[00:08:18] But like that's not the case here. Like a model company can raise money and drop a model in a, in a year, and it's better, right? And, and it does it with a team of 20 people or 10 people. So this type of like money entering a company and then producing something that has demand and growth right away and using that to raise more money is a very different capital flywheel than we've ever seen before.[00:08:39] And I think everybody's trying to understand what the consequences are. So I think it's less about like. Big companies and growth and this, and more about these more systemic questions that we actually don't have answers to.[00:08:49] Alessio: Yeah, like at Kernel Labs, one of our ideas is like if you had unlimited money to spend productively to turn tokens into products, like the whole early stage [00:09:00] market is very different because today you're investing X amount of capital to win a deal because of price structure and whatnot, and you're kind of pot committing.[00:09:07] Yeah. To a certain strategy for a certain amount of time. Yeah. But if you could like iteratively spin out companies and products and just throw, I, I wanna spend a million dollar of inference today and get a product out tomorrow.[00:09:18] swyx: Yeah.[00:09:19] Alessio: Like, we should get to the point where like the friction of like token to product is so low that you can do this and then you can change the Right, the early stage venture model to be much more iterative.[00:09:30] And then every round is like either 100 k of inference or like a hundred million from a 16 Z. There's no, there's no like $8 million C round anymore. Right.[00:09:38] When Frontier Labs Outspend the Entire App Ecosystem[00:09:38] Martin Casado: But, but, but, but there's a, there's a, the, an industry structural question that we don't know the answer to, which involves the frontier models, which is, let's take.[00:09:48] Anthropic it. Let's say Anthropic has a state-of-the-art model that has some large percentage of market share. And let's say that, uh, uh, uh, you know, uh, a company's building smaller models [00:10:00] that, you know, use the bigger model in the background, open 4.5, but they add value on top of that. Now, if Anthropic can raise three times more.[00:10:10] Every subsequent round, they probably can raise more money than the entire app ecosystem that's built on top of it. And if that's the case, they can expand beyond everything built on top of it. It's like imagine like a star that's just kind of expanding, so there could be a systemic. There could be a, a systemic situation where the soda models can raise so much money that they can out pay anybody that bills on top of ‘em, which would be something I don't think we've ever seen before just because we were so bottlenecked in engineering, and this is a very open question.[00:10:41] swyx: Yeah. It's, it is almost like bitter lesson applied to the startup industry.[00:10:45] Martin Casado: Yeah, a hundred percent. It literally becomes an issue of like raise capital, turn that directly into growth. Use that to raise three times more. Exactly. And if you can keep doing that, you literally can outspend any company that's built the, not any company.[00:10:57] You can outspend the aggregate of companies on top of [00:11:00] you and therefore you'll necessarily take their share, which is crazy.[00:11:02] swyx: Would you say that kind of happens in character? Is that the, the sort of postmortem on. What happened?[00:11:10] Sarah Wang: Um,[00:11:10] Martin Casado: no.[00:11:12] Sarah Wang: Yeah, because I think so,[00:11:13] swyx: I mean the actual postmortem is, he wanted to go back to Google.[00:11:15] Exactly. But like[00:11:18] Martin Casado: that's another difference that[00:11:19] Sarah Wang: you said[00:11:21] Martin Casado: it. We should talk, we should actually talk about that.[00:11:22] swyx: Yeah,[00:11:22] Sarah Wang: that's[00:11:23] swyx: Go for it. Take it. Take,[00:11:23] Sarah Wang: yeah.[00:11:24] Character.AI, Founder Goals (AGI vs Product), and GPU Allocation Tradeoffs[00:11:24] Sarah Wang: I was gonna say, I think, um. The, the, the character thing raises actually a different issue, which actually the Frontier Labs will face as well. So we'll see how they handle it.[00:11:34] But, um, so we invest in character in January, 2023, which feels like eons ago, I mean, three years ago. Feels like lifetimes ago. But, um, and then they, uh, did the IP licensing deal with Google in August, 2020. Uh, four. And so, um, you know, at the time, no, you know, he's talked publicly about this, right? He wanted to Google wouldn't let him put out products in the world.[00:11:56] That's obviously changed drastically. But, um, he went to go do [00:12:00] that. Um, but he had a product attached. The goal was, I mean, it's Nome Shair, he wanted to get to a GI. That was always his personal goal. But, you know, I think through collecting data, right, and this sort of very human use case, that the character product.[00:12:13] Originally was and still is, um, was one of the vehicles to do that. Um, I think the real reason that, you know. I if you think about the, the stress that any company feels before, um, you ultimately going one way or the other is sort of this a GI versus product. Um, and I think a lot of the big, I think, you know, opening eyes, feeling that, um, anthropic if they haven't started, you know, felt it, certainly given the success of their products, they may start to feel that soon.[00:12:39] And the real. I think there's real trade-offs, right? It's like how many, when you think about GPUs, that's a limited resource. Where do you allocate the GPUs? Is it toward the product? Is it toward new re research? Right? Is it, or long-term research, is it toward, um, n you know, near to midterm research? And so, um, in a case where you're resource constrained, um, [00:13:00] of course there's this fundraising game you can play, right?[00:13:01] But the fund, the market was very different back in 2023 too. Um. I think the best researchers in the world have this dilemma of, okay, I wanna go all in on a GI, but it's the product usage revenue flywheel that keeps the revenue in the house to power all the GPUs to get to a GI. And so it does make, um, you know, I think it sets up an interesting dilemma for any startup that has trouble raising up until that level, right?[00:13:27] And certainly if you don't have that progress, you can't continue this fly, you know, fundraising flywheel.[00:13:32] Martin Casado: I would say that because, ‘cause we're keeping track of all of the things that are different, right? Like, you know, venture growth and uh, app infra and one of the ones is definitely the personalities of the founders.[00:13:45] It's just very different this time I've been. Been doing this for a decade and I've been doing startups for 20 years. And so, um, I mean a lot of people start this to do a GI and we've never had like a unified North star that I recall in the same [00:14:00] way. Like people built companies to start companies in the past.[00:14:02] Like that was what it was. Like I would create an internet company, I would create infrastructure company, like it's kind of more engineering builders and this is kind of a different. You know, mentality. And some companies have harnessed that incredibly well because their direction is so obviously on the path to what somebody would consider a GI, but others have not.[00:14:20] And so like there is always this tension with personnel. And so I think we're seeing more kind of founder movement.[00:14:27] Sarah Wang: Yeah.[00:14:27] Martin Casado: You know, as a fraction of founders than we've ever seen. I mean, maybe since like, I don't know the time of like Shockly and the trade DUR aid or something like that. Way back in the beginning of the industry, I, it's a very, very.[00:14:38] Unusual time of personnel.[00:14:39] Sarah Wang: Totally.[00:14:40] Talent Wars, Mega-Comp, and the Rise of Acquihire M&A[00:14:40] Sarah Wang: And it, I think it's exacerbated by the fact that talent wars, I mean, every industry has talent wars, but not at this magnitude, right? No. Yeah. Very rarely can you see someone get poached for $5 billion. That's hard to compete with. And then secondly, if you're a founder in ai, you could fart and it would be on the front page of, you know, the information these days.[00:14:59] And so there's [00:15:00] sort of this fishbowl effect that I think adds to the deep anxiety that, that these AI founders are feeling.[00:15:06] Martin Casado: Hmm.[00:15:06] swyx: Uh, yes. I mean, just on, uh, briefly comment on the founder, uh, the sort of. Talent wars thing. I feel like 2025 was just like a blip. Like I, I don't know if we'll see that again.[00:15:17] ‘cause meta built the team. Like, I don't know if, I think, I think they're kind of done and like, who's gonna pay more than meta? I, I don't know.[00:15:23] Martin Casado: I, I agree. So it feels so, it feel, it feels this way to me too. It's like, it is like, basically Zuckerberg kind of came out swinging and then now he's kind of back to building.[00:15:30] Yeah,[00:15:31] swyx: yeah. You know, you gotta like pay up to like assemble team to rush the job, whatever. But then now, now you like you, you made your choices and now they got a ship.[00:15:38] Martin Casado: I mean, the, the o other side of that is like, you know, like we're, we're actually in the job hiring market. We've got 600 people here. I hire all the time.[00:15:44] I've got three open recs if anybody's interested, that's listening to this for investor. Yeah, on, on the team, like on the investing side of the team, like, and, um, a lot of the people we talk to have acting, you know, active, um, offers for 10 million a year or something like that. And like, you know, and we pay really, [00:16:00] really well.[00:16:00] And just to see what's out on the market is really, is really remarkable. And so I would just say it's actually, so you're right, like the really flashy one, like I will get someone for, you know, a billion dollars, but like the inflated, um, uh, trickles down. Yeah, it is still very active today. I mean,[00:16:18] Sarah Wang: yeah, you could be an L five and get an offer in the tens of millions.[00:16:22] Okay. Yeah. Easily. Yeah. It's so I think you're right that it felt like a blip. I hope you're right. Um, but I think it's been, the steady state is now, I think got pulled up. Yeah. Yeah. I'll pull up for[00:16:31] Martin Casado: sure. Yeah.[00:16:32] Alessio: Yeah. And I think that's breaking the early stage founder math too. I think before a lot of people would be like, well, maybe I should just go be a founder instead of like getting paid.[00:16:39] Yeah. 800 KA million at Google. But if I'm getting paid. Five, 6 million. That's different but[00:16:45] Martin Casado: on. But on the other hand, there's more strategic money than we've ever seen historically, right? Mm-hmm. And so, yep. The economics, the, the, the, the calculus on the economics is very different in a number of ways. And, uh, it's crazy.[00:16:58] It's cra it's causing like a, [00:17:00] a, a, a ton of change in confusion in the market. Some very positive, sub negative, like, so for example, the other side of the, um. The co-founder, like, um, acquisition, you know, mark Zuckerberg poaching someone for a lot of money is like, we were actually seeing historic amount of m and a for basically acquihires, right?[00:17:20] That you like, you know, really good outcomes from a venture perspective that are effective acquihires, right? So I would say it's probably net positive from the investment standpoint, even though it seems from the headlines to be very disruptive in a negative way.[00:17:33] Alessio: Yeah.[00:17:33] What's Underfunded: Boring Software, Robotics Skepticism, and Custom Silicon Economics[00:17:33] Alessio: Um, let's talk maybe about what's not being invested in, like maybe some interesting ideas that you would see more people build or it, it seems in a way, you know, as ycs getting more popular, it's like access getting more popular.[00:17:47] There's a startup school path that a lot of founders take and they know what's hot in the VC circles and they know what gets funded. Uh, and there's maybe not as much risk appetite for. Things outside of that. Um, I'm curious if you feel [00:18:00] like that's true and what are maybe, uh, some of the areas, uh, that you think are under discussed?[00:18:06] Martin Casado: I mean, I actually think that we've taken our eye off the ball in a lot of like, just traditional, you know, software companies. Um, so like, I mean. You know, I think right now there's almost a barbell, like you're like the hot thing on X, you're deep tech.[00:18:21] swyx: Mm-hmm.[00:18:22] Martin Casado: Right. But I, you know, I feel like there's just kind of a long, you know, list of like good.[00:18:28] Good companies that will be around for a long time in very large markets. Say you're building a database, you know, say you're building, um, you know, kind of monitoring or logging or tooling or whatever. There's some good companies out there right now, but like, they have a really hard time getting, um, the attention of investors.[00:18:43] And it's almost become a meme, right? Which is like, if you're not basically growing from zero to a hundred in a year, you're not interesting, which is just, is the silliest thing to say. I mean, think of yourself as like an introvert person, like, like your personal money, right? Mm-hmm. So. Your personal money, will you put it in the stock market at 7% or you put it in this company growing five x in a very large [00:19:00] market?[00:19:00] Of course you can put it in the company five x. So it's just like we say these stupid things, like if you're not going from zero to a hundred, but like those, like who knows what the margins of those are mean. Clearly these are good investments. True for anybody, right? True. Like our LPs want whatever.[00:19:12] Three x net over, you know, the life cycle of a fund, right? So a, a company in a big market growing five X is a great investment. We'd, everybody would be happy with these returns, but we've got this kind of mania on these, these strong growths. And so I would say that that's probably the most underinvested sector.[00:19:28] Right now.[00:19:29] swyx: Boring software, boring enterprise software.[00:19:31] Martin Casado: Traditional. Really good company.[00:19:33] swyx: No, no AI here.[00:19:34] Martin Casado: No. Like boring. Well, well, the AI of course is pulling them into use cases. Yeah, but that's not what they're, they're not on the token path, right? Yeah. Let's just say that like they're software, but they're not on the token path.[00:19:41] Like these are like they're great investments from any definition except for like random VC on Twitter saying VC on x, saying like, it's not growing fast enough. What do you[00:19:52] Sarah Wang: think? Yeah, maybe I'll answer a slightly different. Question, but adjacent to what you asked, um, which is maybe an area that we're not, uh, investing [00:20:00] right now that I think is a question and we're spending a lot of time in regardless of whether we pull the trigger or not.[00:20:05] Um, and it would probably be on the hardware side, actually. Robotics, right? And the robotics side. Robotics. Right. Which is, it's, I don't wanna say that it's not getting funding ‘cause it's clearly, uh, it's, it's sort of non-consensus to almost not invest in robotics at this point. But, um, we spent a lot of time in that space and I think for us, we just haven't seen the chat GPT moment.[00:20:22] Happen on the hardware side. Um, and the funding going into it feels like it's already. Taking that for granted.[00:20:30] Martin Casado: Yeah. Yeah. But we also went through the drone, you know, um, there's a zip line right, right out there. What's that? Oh yeah, there's a zip line. Yeah. What the drone, what the av And like one of the takeaways is when it comes to hardware, um, most companies will end up verticalizing.[00:20:46] Like if you're. If you're investing in a robot company for an A for agriculture, you're investing in an ag company. ‘cause that's the competition and that's surprising. And that's supply chain. And if you're doing it for mining, that's mining. And so the ad team does a lot of that type of stuff ‘cause they actually set up to [00:21:00] diligence that type of work.[00:21:01] But for like horizontal technology investing, there's very little when it comes to robots just because it's so fit for, for purpose. And so we kinda like to look at software. Solutions or horizontal solutions like applied intuition. Clearly from the AV wave deep map, clearly from the AV wave, I would say scale AI was actually a horizontal one for That's fair, you know, for robotics early on.[00:21:23] And so that sort of thing we're very, very interested. But the actual like robot interacting with the world is probably better for different team. Agree.[00:21:30] Alessio: Yeah, I'm curious who these teams are supposed to be that invest in them. I feel like everybody's like, yeah, robotics, it's important and like people should invest in it.[00:21:38] But then when you look at like the numbers, like the capital requirements early on versus like the moment of, okay, this is actually gonna work. Let's keep investing. That seems really hard to predict in a way that is not,[00:21:49] Martin Casado: I think co, CO two, kla, gc, I mean these are all invested in in Harvard companies. He just, you know, and [00:22:00] listen, I mean, it could work this time for sure.[00:22:01] Right? I mean if Elon's doing it, he's like, right. Just, just the fact that Elon's doing it means that there's gonna be a lot of capital and a lot of attempts for a long period of time. So that alone maybe suggests that we should just be investing in robotics just ‘cause you have this North star who's Elon with a humanoid and that's gonna like basically willing into being an industry.[00:22:17] Um, but we've just historically found like. We're a huge believer that this is gonna happen. We just don't feel like we're in a good position to diligence these things. ‘cause again, robotics companies tend to be vertical. You really have to understand the market they're being sold into. Like that's like that competitive equilibrium with a human being is what's important.[00:22:34] It's not like the core tech and like we're kind of more horizontal core tech type investors. And this is Sarah and I. Yeah, the ad team is different. They can actually do these types of things.[00:22:42] swyx: Uh, just to clarify, AD stands for[00:22:44] Martin Casado: American Dynamism.[00:22:45] swyx: Alright. Okay. Yeah, yeah, yeah. Uh, I actually, I do have a related question that, first of all, I wanna acknowledge also just on the, on the chip side.[00:22:51] Yeah. I, I recall a podcast that where you were on, i, I, I think it was the a CC podcast, uh, about two or three years ago where you, where you suddenly said [00:23:00] something, which really stuck in my head about how at some point, at some point kind of scale it makes sense to. Build a custom aic Yes. For per run.[00:23:07] Martin Casado: Yes.[00:23:07] It's crazy. Yeah.[00:23:09] swyx: We're here and I think you, you estimated 500 billion, uh, something.[00:23:12] Martin Casado: No, no, no. A billion, a billion dollar training run of $1 billion training run. It makes sense to actually do a custom meic if you can do it in time. The question now is timelines. Yeah, but not money because just, just, just rough math.[00:23:22] If it's a billion dollar training. Then the inference for that model has to be over a billion, otherwise it won't be solvent. So let's assume it's, if you could save 20%, which you could save much more than that with an ASIC 20%, that's $200 million. You can tape out a chip for $200 million. Right? So now you can literally like justify economically, not timeline wise.[00:23:41] That's a different issue. An ASIC per model, which[00:23:44] swyx: is because that, that's how much we leave on the table every single time. We, we, we do like generic Nvidia.[00:23:48] Martin Casado: Exactly. Exactly. No, it, it is actually much more than that. You could probably get, you know, a factor of two, which would be 500 million.[00:23:54] swyx: Typical MFU would be like 50.[00:23:55] Yeah, yeah. And that's good.[00:23:57] Martin Casado: Exactly. Yeah. Hundred[00:23:57] swyx: percent. Um, so, so, yeah, and I mean, and I [00:24:00] just wanna acknowledge like, here we are in, in, in 2025 and opening eyes confirming like Broadcom and all the other like custom silicon deals, which is incredible. I, I think that, uh, you know, speaking about ad there's, there's a really like interesting tie in that obviously you guys are hit on, which is like these sort, this sort of like America first movement or like sort of re industrialized here.[00:24:17] Yeah. Uh, move TSMC here, if that's possible. Um, how much overlap is there from ad[00:24:23] Martin Casado: Yeah.[00:24:23] swyx: To, I guess, growth and, uh, investing in particularly like, you know, US AI companies that are strongly bounded by their compute.[00:24:32] Martin Casado: Yeah. Yeah. So I mean, I, I would view, I would view AD as more as a market segmentation than like a mission, right?[00:24:37] So the market segmentation is, it has kind of regulatory compliance issues or government, you know, sale or it deals with like hardware. I mean, they're just set up to, to, to, to, to. To diligence those types of companies. So it's a more of a market segmentation thing. I would say the entire firm. You know, which has been since it is been intercepted, you know, has geographical biases, right?[00:24:58] I mean, for the longest time we're like, you [00:25:00] know, bay Area is gonna be like, great, where the majority of the dollars go. Yeah. And, and listen, there, there's actually a lot of compounding effects for having a geographic bias. Right. You know, everybody's in the same place. You've got an ecosystem, you're there, you've got presence, you've got a network.[00:25:12] Um, and, uh, I mean, I would say the Bay area's very much back. You know, like I, I remember during pre COVID, like it was like almost Crypto had kind of. Pulled startups away. Miami from the Bay Area. Miami, yeah. Yeah. New York was, you know, because it's so close to finance, came up like Los Angeles had a moment ‘cause it was so close to consumer, but now it's kind of come back here.[00:25:29] And so I would say, you know, we tend to be very Bay area focused historically, even though of course we've asked all over the world. And then I would say like, if you take the ring out, you know, one more, it's gonna be the US of course, because we know it very well. And then one more is gonna be getting us and its allies and Yeah.[00:25:44] And it goes from there.[00:25:45] Sarah Wang: Yeah,[00:25:45] Martin Casado: sorry.[00:25:46] Sarah Wang: No, no. I agree. I think from a, but I think from the intern that that's sort of like where the companies are headquartered. Maybe your questions on supply chain and customer base. Uh, I, I would say our customers are, are, our companies are fairly international from that perspective.[00:25:59] Like they're selling [00:26:00] globally, right? They have global supply chains in some cases.[00:26:03] Martin Casado: I would say also the stickiness is very different.[00:26:05] Sarah Wang: Yeah.[00:26:05] Martin Casado: Historically between venture and growth, like there's so much company building in venture, so much so like hiring the next PM. Introducing the customer, like all of that stuff.[00:26:15] Like of course we're just gonna be stronger where we have our network and we've been doing business for 20 years. I've been in the Bay Area for 25 years, so clearly I'm just more effective here than I would be somewhere else. Um, where I think, I think for some of the later stage rounds, the companies don't need that much help.[00:26:30] They're already kind of pretty mature historically, so like they can kind of be everywhere. So there's kind of less of that stickiness. This is different in the AI time. I mean, Sarah is now the, uh, chief of staff of like half the AI companies in, uh, in the Bay Area right now. She's like, ops Ninja Biz, Devrel, BizOps.[00:26:48] swyx: Are, are you, are you finding much AI automation in your work? Like what, what is your stack.[00:26:53] Sarah Wang: Oh my, in my personal stack.[00:26:54] swyx: I mean, because like, uh, by the way, it's the, the, the reason for this is it is triggering, uh, yeah. We, like, I'm hiring [00:27:00] ops, ops people. Um, a lot of ponders I know are also hiring ops people and I'm just, you know, it's opportunity Since you're, you're also like basically helping out with ops with a lot of companies.[00:27:09] What are people doing these days? Because it's still very manual as far as I can tell.[00:27:13] Sarah Wang: Hmm. Yeah. I think the things that we help with are pretty network based, um, in that. It's sort of like, Hey, how do do I shortcut this process? Well, let's connect you to the right person. So there's not quite an AI workflow for that.[00:27:26] I will say as a growth investor, Claude Cowork is pretty interesting. Yeah. Like for the first time, you can actually get one shot data analysis. Right. Which, you know, if you're gonna do a customer database, analyze a cohort retention, right? That's just stuff that you had to do by hand before. And our team, the other, it was like midnight and the three of us were playing with Claude Cowork.[00:27:47] We gave it a raw file. Boom. Perfectly accurate. We checked the numbers. It was amazing. That was my like, aha moment. That sounds so boring. But you know, that's, that's the kind of thing that a growth investor is like, [00:28:00] you know, slaving away on late at night. Um, done in a few seconds.[00:28:03] swyx: Yeah. You gotta wonder what the whole, like, philanthropic labs, which is like their new sort of products studio.[00:28:10] Yeah. What would that be worth as an independent, uh, startup? You know, like a[00:28:14] Martin Casado: lot.[00:28:14] Sarah Wang: Yeah, true.[00:28:16] swyx: Yeah. You[00:28:16] Martin Casado: gotta hand it to them. They've been executing incredibly well.[00:28:19] swyx: Yeah. I, I mean, to me, like, you know, philanthropic, like building on cloud code, I think, uh, it makes sense to me the, the real. Um, pedal to the metal, whatever the, the, the phrase is, is when they start coming after consumer with, uh, against OpenAI and like that is like red alert at Open ai.[00:28:35] Oh, I[00:28:35] Martin Casado: think they've been pretty clear. They're enterprise focused.[00:28:37] swyx: They have been, but like they've been free. Here's[00:28:40] Martin Casado: care publicly,[00:28:40] swyx: it's enterprise focused. It's coding. Right. Yeah.[00:28:43] AI Labs vs Startups: Disruption, Undercutting & the Innovator's Dilemma[00:28:43] swyx: And then, and, but here's cloud, cloud, cowork, and, and here's like, well, we, uh, they, apparently they're running Instagram ads for Claudia.[00:28:50] I, on, you know, for, for people on, I get them all the time. Right. And so, like,[00:28:54] Martin Casado: uh,[00:28:54] swyx: it, it's kind of like this, the disruption thing of, uh, you know. Mo Open has been doing, [00:29:00] consumer been doing the, just pursuing general intelligence in every mo modality, and here's a topic that only focus on this thing, but now they're sort of undercutting and doing the whole innovator's dilemma thing on like everything else.[00:29:11] Martin Casado: It's very[00:29:11] swyx: interesting.[00:29:12] Martin Casado: Yeah, I mean there's, there's a very open que so for me there's like, do you know that meme where there's like the guy in the path and there's like a path this way? There's a path this way. Like one which way Western man. Yeah. Yeah.[00:29:23] Two Futures for AI: Infinite Market vs AGI Oligopoly[00:29:23] Martin Casado: And for me, like, like all the entire industry kind of like hinges on like two potential futures.[00:29:29] So in, in one potential future, um, the market is infinitely large. There's perverse economies of scale. ‘cause as soon as you put a model out there, like it kind of sublimates and all the other models catch up and like, it's just like software's being rewritten and fractured all over the place and there's tons of upside and it just grows.[00:29:48] And then there's another path which is like, well. Maybe these models actually generalize really well, and all you have to do is train them with three times more money. That's all you have to [00:30:00] do, and it'll just consume everything beyond it. And if that's the case, like you end up with basically an oligopoly for everything, like, you know mm-hmm.[00:30:06] Because they're perfectly general and like, so this would be like the, the a GI path would be like, these are perfectly general. They can do everything. And this one is like, this is actually normal software. The universe is complicated. You've got, and nobody knows the answer.[00:30:18] The Economics Reality Check: Gross Margins, Training Costs & Borrowing Against the Future[00:30:18] Martin Casado: My belief is if you actually look at the numbers of these companies, so generally if you look at the numbers of these companies, if you look at like the amount they're making and how much they, they spent training the last model, they're gross margin positive.[00:30:30] You're like, oh, that's really working. But if you look at like. The current training that they're doing for the next model, their gross margin negative. So part of me thinks that a lot of ‘em are kind of borrowing against the future and that's gonna have to slow down. It's gonna catch up to them at some point in time, but we don't really know.[00:30:47] Sarah Wang: Yeah.[00:30:47] Martin Casado: Does that make sense? Like, I mean, it could be, it could be the case that the only reason this is working is ‘cause they can raise that next round and they can train that next model. ‘cause these models have such a short. Life. And so at some point in time, like, you know, they won't be able to [00:31:00] raise that next round for the next model and then things will kind of converge and fragment again.[00:31:03] But right now it's not.[00:31:04] Sarah Wang: Totally. I think the other, by the way, just, um, a meta point. I think the other lesson from the last three years is, and we talk about this all the time ‘cause we're on this. Twitter X bubble. Um, cool. But, you know, if you go back to, let's say March, 2024, that period, it felt like a, I think an open source model with an, like a, you know, benchmark leading capability was sort of launching on a daily basis at that point.[00:31:27] And, um, and so that, you know, that's one period. Suddenly it's sort of like open source takes over the world. There's gonna be a plethora. It's not an oligopoly, you know, if you fast, you know, if you, if you rewind time even before that GPT-4 was number one for. Nine months, 10 months. It's a long time. Right.[00:31:44] Um, and of course now we're in this era where it feels like an oligopoly, um, maybe some very steady state shifts and, and you know, it could look like this in the future too, but it just, it's so hard to call. And I think the thing that keeps, you know, us up at [00:32:00] night in, in a good way and bad way, is that the capability progress is actually not slowing down.[00:32:06] And so until that happens, right, like you don't know what's gonna look like.[00:32:09] Martin Casado: But I, I would, I would say for sure it's not converged, like for sure, like the systemic capital flows have not converged, meaning right now it's still borrowing against the future to subsidize growth currently, which you can do that for a period of time.[00:32:23] But, but you know, at the end, at some point the market will rationalize that and just nobody knows what that will look like.[00:32:29] Alessio: Yeah.[00:32:29] Martin Casado: Or, or like the drop in price of compute will, will, will save them. Who knows?[00:32:34] Alessio: Yeah. Yeah. I think the models need to ask them to, to specific tasks. You know? It's like, okay, now Opus 4.5 might be a GI at some specific task, and now you can like depreciate the model over a longer time.[00:32:45] I think now, now, right now there's like no old model.[00:32:47] Martin Casado: No, but let, but lemme just change that mental, that's, that used to be my mental model. Lemme just change it a little bit.[00:32:53] Capital as a Weapon vs Task Saturation: Where Real Enterprise Value Gets Built[00:32:53] Martin Casado: If you can raise three times, if you can raise more than the aggregate of anybody that uses your models, that doesn't even matter.[00:32:59] It doesn't [00:33:00] even matter. See what I'm saying? Like, yeah. Yeah. So, so I have an API Business. My API business is 60% margin, or 70% margin, or 80% margin is a high margin business. So I know what everybody is using. If I can raise more money than the aggregate of everybody that's using it, I will consume them whether I'm a GI or not.[00:33:14] And I will know if they're using it ‘cause they're using it. And like, unlike in the past where engineering stops me from doing that.[00:33:21] Alessio: Mm-hmm.[00:33:21] Martin Casado: It is very straightforward. You just train. So I also thought it was kind of like, you must ask the code a GI, general, general, general. But I think there's also just a possibility that the, that the capital markets will just give them the, the, the ammunition to just go after everybody on top of ‘em.[00:33:36] Sarah Wang: I, I do wonder though, to your point, um, if there's a certain task that. Getting marginally better isn't actually that much better. Like we've asked them to it, to, you know, we can call it a GI or whatever, you know, actually, Ali Goi talks about this, like we're already at a GI for a lot of functions in the enterprise.[00:33:50] Um. That's probably those for those tasks, you probably could build very specific companies that focus on just getting as much value out of that task that isn't [00:34:00] coming from the model itself. There's probably a rich enterprise business to be built there. I mean, could be wrong on that, but there's a lot of interesting examples.[00:34:08] So, right, if you're looking the legal profession or, or whatnot, and maybe that's not a great one ‘cause the models are getting better on that front too, but just something where it's a bit saturated, then the value comes from. Services. It comes from implementation, right? It comes from all these things that actually make it useful to the end customer.[00:34:24] Martin Casado: Sorry, what am I, one more thing I think is, is underused in all of this is like, to what extent every task is a GI complete.[00:34:31] Sarah Wang: Mm-hmm.[00:34:32] Martin Casado: Yeah. I code every day. It's so fun.[00:34:35] Sarah Wang: That's a core question. Yeah.[00:34:36] Martin Casado: And like. When I'm talking to these models, it's not just code. I mean, it's everything, right? Like I, you know, like it's,[00:34:43] swyx: it's healthcare.[00:34:44] It's,[00:34:44] Martin Casado: I mean, it's[00:34:44] swyx: Mele,[00:34:45] Martin Casado: but it's every, it is exactly that. Like, yeah, that's[00:34:47] Sarah Wang: great support. Yeah.[00:34:48] Martin Casado: It's everything. Like I'm asking these models to, yeah, to understand compliance. I'm asking these models to go search the web. I'm asking these models to talk about things I know in the history, like it's having a full conversation with me while I, I engineer, and so it could be [00:35:00] the case that like, mm-hmm.[00:35:01] The most a, you know, a GI complete, like I'm not an a GI guy. Like I think that's, you know, but like the most a GI complete model will is win independent of the task. And we don't know the answer to that one either.[00:35:11] swyx: Yeah.[00:35:12] Martin Casado: But it seems to me that like, listen, codex in my experience is for sure better than Opus 4.5 for coding.[00:35:18] Like it finds the hardest bugs that I work in with. Like, it is, you know. The smartest developers. I don't work on it. It's great. Um, but I think Opus 4.5 is actually very, it's got a great bedside manner and it really, and it, it really matters if you're building something very complex because like, it really, you know, like you're, you're, you're a partner and a brainstorming partner for somebody.[00:35:38] And I think we don't discuss enough how every task kind of has that quality.[00:35:42] swyx: Mm-hmm.[00:35:43] Martin Casado: And what does that mean to like capital investment and like frontier models and Submodels? Yeah.[00:35:47] Why “Coding Models” Keep Collapsing into Generalists (Reasoning vs Taste)[00:35:47] Martin Casado: Like what happened to all the special coding models? Like, none of ‘em worked right. So[00:35:51] Alessio: some of them, they didn't even get released.[00:35:53] Magical[00:35:54] Martin Casado: Devrel. There's a whole, there's a whole host. We saw a bunch of them and like there's this whole theory that like, there could be, and [00:36:00] I think one of the conclusions is, is like there's no such thing as a coding model,[00:36:04] Alessio: you know?[00:36:04] Martin Casado: Like, that's not a thing. Like you're talking to another human being and it's, it's good at coding, but like it's gotta be good at everything.[00:36:10] swyx: Uh, minor disagree only because I, I'm pretty like, have pretty high confidence that basically open eye will always release a GPT five and a GT five codex. Like that's the code's. Yeah. The way I call it is one for raisin, one for Tiz. Um, and, and then like someone internal open, it was like, yeah, that's a good way to frame it.[00:36:32] Martin Casado: That's so funny.[00:36:33] swyx: Uh, but maybe it, maybe it collapses down to reason and that's it. It's not like a hundred dimensions doesn't life. Yeah. It's two dimensions. Yeah, yeah, yeah, yeah. Like and exactly. Beside manner versus coding. Yeah.[00:36:43] Martin Casado: Yeah.[00:36:44] swyx: It's, yeah.[00:36:46] Martin Casado: I, I think for, for any, it's hilarious. For any, for anybody listening to this for, for, for, I mean, for you, like when, when you're like coding or using these models for something like that.[00:36:52] Like actually just like be aware of how much of the interaction has nothing to do with coding and it just turns out to be a large portion of it. And so like, you're, I [00:37:00] think like, like the best Soto ish model. You know, it is going to remain very important no matter what the task is.[00:37:06] swyx: Yeah.[00:37:07] What He's Actually Coding: Gaussian Splats, Spark.js & 3D Scene Rendering Demos[00:37:07] swyx: Uh, speaking of coding, uh, I, I'm gonna be cheeky and ask like, what actually are you coding?[00:37:11] Because obviously you, you could code anything and you are obviously a busy investor and a manager of the good. Giant team. Um, what are you calling?[00:37:18] Martin Casado: I help, um, uh, FEFA at World Labs. Uh, it's one of the investments and um, and they're building a foundation model that creates 3D scenes.[00:37:27] swyx: Yeah, we had it on the pod.[00:37:28] Yeah. Yeah,[00:37:28] Martin Casado: yeah. And so these 3D scenes are Gaussian splats, just by the way that kind of AI works. And so like, you can reconstruct a scene better with, with, with radiance feels than with meshes. ‘cause like they don't really have topology. So, so they, they, they produce each. Beautiful, you know, 3D rendered scenes that are Gaussian splats, but the actual industry support for Gaussian splats isn't great.[00:37:50] It's just never, you know, it's always been meshes and like, things like unreal use meshes. And so I work on a open source library called Spark js, which is a. Uh, [00:38:00] a JavaScript rendering layer ready for Gaussian splats. And it's just because, you know, um, you, you, you need that support and, and right now there's kind of a three js moment that's all meshes and so like, it's become kind of the default in three Js ecosystem.[00:38:13] As part of that to kind of exercise the library, I just build a whole bunch of cool demos. So if you see me on X, you see like all my demos and all the world building, but all of that is just to exercise this, this library that I work on. ‘cause it's actually a very tough algorithmics problem to actually scale a library that much.[00:38:29] And just so you know, this is ancient history now, but 30 years ago I paid for undergrad, you know, working on game engines in college in the late nineties. So I've got actually a back and it's very old background, but I actually have a background in this and so a lot of it's fun. You know, but, but the, the, the, the whole goal is just for this rendering library to, to,[00:38:47] Sarah Wang: are you one of the most active contributors?[00:38:49] The, their GitHub[00:38:50] Martin Casado: spark? Yes.[00:38:51] Sarah Wang: Yeah, yeah.[00:38:51] Martin Casado: There's only two of us there, so, yes. No, so by the way, so the, the pri The pri, yeah. Yeah. So the primary developer is a [00:39:00] guy named Andres Quist, who's an absolute genius. He and I did our, our PhDs together. And so like, um, we studied for constant Quas together. It was almost like hanging out with an old friend, you know?[00:39:09] And so like. So he, he's the core, core guy. I did mostly kind of, you know, the side I run venture fund.[00:39:14] swyx: It's amazing. Like five years ago you would not have done any of this. And it brought you back[00:39:19] Martin Casado: the act, the Activ energy, you're still back. Energy was so high because you had to learn all the framework b******t.[00:39:23] Man, I f*****g used to hate that. And so like, now I don't have to deal with that. I can like focus on the algorithmics so I can focus on the scaling and I,[00:39:29] swyx: yeah. Yeah.[00:39:29] LLMs vs Spatial Intelligence + How to Value World Labs' 3D Foundation Model[00:39:29] swyx: And then, uh, I'll observe one irony and then I'll ask a serious investor question, uh, which is like, the irony is FFE actually doesn't believe that LMS can lead us to spatial intelligence.[00:39:37] And here you are using LMS to like help like achieve spatial intelligence. I just see, I see some like disconnect in there.[00:39:45] Martin Casado: Yeah. Yeah. So I think, I think, you know, I think, I think what she would say is LLMs are great to help with coding.[00:39:51] swyx: Yes.[00:39:51] Martin Casado: But like, that's very different than a model that actually like provides, they, they'll never have the[00:39:56] swyx: spatial inte[00:39:56] Martin Casado: issues.[00:39:56] And listen, our brains clearly listen, our brains, brains clearly have [00:40:00] both our, our brains clearly have a language reasoning section and they clearly have a spatial reasoning section. I mean, it's just, you know, these are two pretty independent problems.[00:40:07] swyx: Okay. And you, you, like, I, I would say that the, the one data point I recently had, uh, against it is the DeepMind, uh, IMO Gold, where, so, uh, typically the, the typical answer is that this is where you start going down the neuros symbolic path, right?[00:40:21] Like one, uh, sort of very sort of abstract reasoning thing and one form, formal thing. Um, and that's what. DeepMind had in 2024 with alpha proof, alpha geometry, and now they just use deep think and just extended thinking tokens. And it's one model and it's, and it's in LM.[00:40:36] Martin Casado: Yeah, yeah, yeah, yeah, yeah.[00:40:37] swyx: And so that, that was my indication of like, maybe you don't need a separate system.[00:40:42] Martin Casado: Yeah. So, so let me step back. I mean, at the end of the day, at the end of the day, these things are like nodes in a graph with weights on them. Right. You know, like it can be modeled like if you, if you distill it down. But let me just talk about the two different substrates. Let's, let me put you in a dark room.[00:40:56] Like totally black room. And then let me just [00:41:00] describe how you exit it. Like to your left, there's a table like duck below this thing, right? I mean like the chances that you're gonna like not run into something are very low. Now let me like turn on the light and you actually see, and you can do distance and you know how far something away is and like where it is or whatever.[00:41:17] Then you can do it, right? Like language is not the right primitives to describe. The universe because it's not exact enough. So that's all Faye, Faye is talking about. When it comes to like spatial reasoning, it's like you actually have to know that this is three feet far, like that far away. It is curved.[00:41:37] You have to understand, you know, the, like the actual movement through space.[00:41:40] swyx: Yeah.[00:41:40] Martin Casado: So I do, I listen, I do think at the end of these models are definitely converging as far as models, but there's, there's, there's different representations of problems you're solving. One is language. Which, you know, that would be like describing to somebody like what to do.[00:41:51] And the other one is actually just showing them and the space reasoning is just showing them.[00:41:55] swyx: Yeah, yeah, yeah. Right. Got it, got it. Uh, the, in the investor question was on, on, well labs [00:42:00] is, well, like, how do I value something like this? What, what, what work does the, do you do? I'm just like, Fefe is awesome.[00:42:07] Justin's awesome. And you know, the other two co-founder, co-founders, but like the, the, the tech, everyone's building cool tech. But like, what's the value of the tech? And this is the fundamental question[00:42:16] Martin Casado: of, well, let, let, just like these, let me just maybe give you a rough sketch on the diffusion models. I actually love to hear Sarah because I'm a venture for, you know, so like, ventures always, always like kind of wild west type[00:42:24] swyx: stuff.[00:42:24] You, you, you, you paid a dream and she has to like, actually[00:42:28] Martin Casado: I'm gonna say I'm gonna mar to reality, so I'm gonna say the venture for you. And she can be like, okay, you a little kid. Yeah. So like, so, so these diffusion models literally. Create something for, for almost nothing. And something that the, the world has found to be very valuable in the past, in our real markets, right?[00:42:45] Like, like a 2D image. I mean, that's been an entire market. People value them. It takes a human being a long time to create it, right? I mean, to create a, you know, a, to turn me into a whatever, like an image would cost a hundred bucks in an hour. The inference cost [00:43:00] us a hundredth of a penny, right? So we've seen this with speech in very successful companies.[00:43:03] We've seen this with 2D image. We've seen this with movies. Right? Now, think about 3D scene. I mean, I mean, when's Grand Theft Auto coming out? It's been six, what? It's been 10 years. I mean, how, how like, but hasn't been 10 years.[00:43:14] Alessio: Yeah.[00:43:15] Martin Casado: How much would it cost to like, to reproduce this room in 3D? Right. If you, if you, if you hired somebody on fiber, like in, in any sort of quality, probably 4,000 to $10,000.[00:43:24] And then if you had a professional, probably $30,000. So if you could generate the exact same thing from a 2D image, and we know that these are used and they're using Unreal and they're using Blend, or they're using movies and they're using video games and they're using all. So if you could do that for.[00:43:36] You know, less than a dollar, that's four or five orders of magnitude cheaper. So you're bringing the marginal cost of something that's useful down by three orders of magnitude, which historically have created very large companies. So that would be like the venture kind of strategic dreaming map.[00:43:49] swyx: Yeah.[00:43:50] And, and for listeners, uh, you can do this yourself on your, on your own phone with like. Uh, the marble.[00:43:55] Martin Casado: Yeah. Marble.[00:43:55] swyx: Uh, or but also there's many Nerf apps where you just go on your iPhone and, and do this.[00:43:59] Martin Casado: Yeah. Yeah. [00:44:00] Yeah. And, and in the case of marble though, it would, what you do is you literally give it in.[00:44:03] So most Nerf apps you like kind of run around and take a whole bunch of pictures and then you kind of reconstruct it.[00:44:08] swyx: Yeah.[00:44:08] Martin Casado: Um, things like marble, just that the whole generative 3D space will just take a 2D image and it'll reconstruct all the like, like[00:44:16] swyx: meaning it has to fill in. Uh,[00:44:18] Martin Casado: stuff at the back of the table, under the table, the back, like, like the images, it doesn't see.[00:44:22] So the generator stuff is very different than reconstruction that it fills in the things that you can't see.[00:44:26] swyx: Yeah. Okay.[00:44:26] Sarah Wang: So,[00:44:27] Martin Casado: all right. So now the,[00:44:28] Sarah Wang: no, no. I mean I love that[00:44:29] Martin Casado: the adult[00:44:29] Sarah Wang: perspective. Um, well, no, I was gonna say these are very much a tag team. So we, we started this pod with that, um, premise. And I think this is a perfect question to even build on that further.[00:44:36] ‘cause it truly is, I mean, we're tag teaming all of these together.[00:44:39] Investing in Model Labs, Media Rumors, and the Cursor Playbook (Margins & Going Down-Stack)[00:44:39] Sarah Wang: Um, but I think every investment fundamentally starts with the same. Maybe the same two premises. One is, at this point in time, we actually believe that there are. And of one founders for their particular craft, and they have to be demonstrated in their prior careers, right?[00:44:56] So, uh, we're not investing in every, you know, now the term is NEO [00:45:00] lab, but every foundation model, uh, any, any company, any founder trying to build a foundation model, we're not, um, contrary to popular opinion, we're

In this episode from WSJ Invest Live, Andy Serwer speaks with Katherine Boyle, general partner at a16z, about the American Dynamism practice she helped launch four years ago. They discuss why saying "America" out loud stunned Silicon Valley in 2022, how Russia's invasion of Ukraine changed everything, and what it means to invest in companies that support the national interest.   Stay Updated:Find a16z on YouTube: YouTubeFind a16z on XFind a16z on LinkedInListen to the a16z Show on SpotifyListen to the a16z Show on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

i'm wall-e, welcoming you to today's tech briefing for tuesday, february 17. delve into the latest highlights and developments: recursive intelligence funding success: the ai-driven chip design startup raises $335 million at a $4 billion valuation in four months, aiming to compete with industry giants like nvidia and intel, co-founded by ex-google engineers anna goldie and azalia mirhoseini. fractal analytics ipo struggle: the indian company's ipo debut disappoints at ₹876 despite private-market success, occurring amidst volatility in indian tech stocks; however, the ai impact summit in new delhi seeks to attract global investment opportunities. a16z's european venture ambitions: andreessen horowitz partner gabriel vasquez targets european startup potential, investing in swedish dental management ai startup dentio, showcasing a diverse investment strategy beyond the u.s. market. openclaw's security concerns: the ai interaction platform faces challenges with cybersecurity vulnerabilities as its popularity wanes, highlighting the critical need for secure ai applications as technology advances. that's a wrap for today. we'll catch you back here tomorrow for more updates.

According to a16z, it has eyes around the world in order to spot companies as early as local funds might. Learn more about your ad choices. Visit podcastchoices.com/adchoices

Smart Bricks is an AI-powered proptech that helps investors find high-quality real estate investments Learn more about your ad choices. Visit podcastchoices.com/adchoices

Anish Acharya is a General Partner at Andreessen Horowitz (a16z), where he leads consumer and fintech investing at Series A. He serves on the boards of standout portfolio companies including Deel, Mosaic, Clutch, Titan, and HappyRobot and has led early bets in companies like Runway and Carbonated. Before a16z, he founded and exited two startups—Snowball (acquired by Credit Karma) and SocialDeck (acquired by Google) and scaled Credit Karma's U.S. Card business to over 100 million members. AGENDA: 00:03 - Why building an AI company today requires being in San Francisco 06:58 - The "SaaS Apocalypse" myth: Why "vibe coding" everything is a lie 09:11 - How AI agents are finally breaking the lock-in of legacy software providers 10:13 - Incumbents vs. Startups: Who actually wins the AI distribution war? 14:39 - Why the developer tool market looks more like Cloud than Uber and Lyft 22:43 - The death of the Chatbox? Why browse-based interfaces are still preferable 27:14 - Why power users are 10x more valuable in the age of AI consumption 28:36 - Do margins matter in a world of AI? 34:46 - Why we are definitively not in an AI bubble right now 38:58 - Why the Legal and Customer Support industries will have dozens of winners 39:44 - Lessons from Marc Andreessen: Why the "quality of being right" supersedes process 44:51 - Is "Triple, Triple, Double, Double" dead? The new physics of growth 01:10:41 - The a16z Playbook: How to win 100% of the deals you chase    

Christopher Mims and Tim Higgins of the Wall Street Journal sit down with a16z General Partner Martin Casado on WSJ's Bold Names to ask whether the AI spending boom is a bubble waiting to burst. Martin explains why the fundamentals differ dramatically from the dot-com era—when WorldCom had $40 billion in debt versus today's tech giants with hundreds of billions on their balance sheets—and why a speculative valuation correction shouldn't be confused with systemic collapse. They also discuss where a16z sees opportunity in the "long tail" of AI companies beyond the state-of-the-art large language models. Follow Martin Casado on X: https://twitter.com/martin_casadoFollow Christopher Mims on X: https://twitter.com/mimsFollow Tim Higgins on X:  https://twitter.com/timkhigginsCheck out WSJ's Bold Names: https://www.wsj.com/podcasts/wsj-the-future-of-everything Check out everything a16z is doing with artificial intelligence here, including articles, projects, and more podcasts. Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

AGENDA: 03:36 Brex Acquisition by Capital One for $5.15BN 10:54 Does Brex's Acquisition Help or Hurt Ramp? 16:28 TikTok Deal Completed: Who Won & Who Lost: Analysis 19:30 Anthropic Inference Costs Higher Than Expected 37:50 Open Evidence Raises at $12BN from Thrive and DST 53:56 Wealthront IPO Disaster: Is $1.5BN IPO Too Small? 01:07:27 Salesforce Wins $5BN Army Contract: The Last Laugh for SaaS  

Erfahre hier mehr über unseren Partner Scalable Capital - dem Broker mit einem der besten YouTube-Kanäle zu Aktien & Investments. https://www.youtube.com/@scalable.capital/videos UnitedHealth, CVS und Humana verlieren. Anta kauft Puma-Anteil. Micron investiert in Singapur. Corning baut für Meta. Cloudflare steigt wegen KI. SK Hynix mit Allzeithoch. GM hat SUVs und Pickups. LVMH schwächelt bei Leder. Texas Instruments wächst. Navan (WKN: A41MYP) hat seit dem IPO 30 % verloren, aber StartUp-Legende Andreessen Horowitz kauft nach. Seagate (WKN: A3CQU7) hat seinen Wert innerhalb eines Jahres vervierfacht. Die Firma profitiert mit klassischen Festplatten vom KI-Hype. Diesen Podcast vom 28.01.2026, 3:00 Uhr stellt dir die Podstars GmbH (Noah Leidinger) zur Verfügung.

Episode #241 features Nicholas Rudder, Founder & CEO of Sphere — which recently raised a US$21M Series A led by Andreessen Horowitz (a16z), to help some of the world's fastest-growing companies, including Lovable, Linktree and Deel, navigate complex cross-border tax compliance using AI.Nick shares the defining crucible of his journey: Growing up in Europe and Australia, then moving to the US chasing a dream, losing a co-founder, rebuilding as a solo founder, navigating a high-risk twin pregnancy that forced his family out of the US, and holding conviction when belief and momentum collapsed.He breaks down how deep CFO discovery led to Sphere's model of using AI as a junior analyst to interpret global tax rules, the magic behind zero-churn customer retention, motivating engineers and more— offering rare insight into building a durable company in a high-stakes, regulated industry.It's time to explore your curiosity — please enjoy.________To support this podcast, check out our some of our sponsors & get discounts:→ $1,000 off Vanta: Your compliance superpower — vanta.com/high→ Find out more about the Law Firm Allens and how they can help your company today at www.allens.com.auIf you're keen to discuss sponsorship and partnering with us or recommend future guests, email us at contact@curiositycentre.com today!Join our stable of commercial partners including the Australian Government, Google, KPMG, Vanta, Allens, Notion and more.________Show notes and more episodes hereFollow us on Instagram, LinkedIn or TwitterGet in touch with our Founder and Host, Vidit Agarwal directly hereContact us via our website________The High Flyers Podcast features in-depth interviews with the world's most influential figures in business, tech, finance, government and sport. Launched in 2020, it has ranked in the global top ten for past three years, with listeners in 27 countries and over 200+ episodes released, and featured in Forbes, Daily Telegraph, and at SXSW.Our guests include -- Malcolm Turnbull (Prime Minister of Australia), Anil Sabharwal (Global VP, Product at Google), Jason Collins (Head of BlackRock, Asia Pacific), Stevie Case (Chief Revenue Officer, Vanta), Brad Banducci (CEO, Woolworths), Jean-Michel Lemieux (CTO, Shopify + Atlassian), Sweta Mehra (EGM, NAB; ex CMO, ANZ), Bowen Pan (Creator, Facebook Marketplace), Sam Sicilia (Chief Investment Officer, Hostplus), Craig Tiley (CEO, Tennis Australia), John Haddock (CBO, Harvey), Niki Scevak (Co-Founder, Blackbird Ventures), Mike Schneider (CEO, Bunnings), Trent Cotchin (3x Premiership Winning Captain, Richmond FC), Peter Varghese (Secretary/Chief, Foreign Affairs, Australian Government), Jack Zhang (CEO, Airwallex), Matteo Franceschetti (CEO, Eight Sleep) and more.

Dan Stein is a former recruiter at Google, SnapChat, and the VC firm A16Z. His wellness journey was featured in Men's Health and he launched an athletic apparel brand focused on mental health called Pax. Dan has also visited over 30 countries. In this episode we discuss: -The best career advice from a recruiter's perspective -Why money is a renewable resource, advice from his dad that has helped him take more calculated risks -How a cross-country move and a chance encounter with a waitress helped him land a job at Google -Why "being seen" matters more than the perfect resume -Why your manager can make or break your career -The most important life lesson from visiting 31 countries -What he means by 'finding what works for you' around health & fitness and more Get my free Career Pivot Playbook to help navigate your next move: www.omaid.me/newsletter Follow me on LinkedIn: www.linkedin.com/in/omaidhomayun/

AGENDA: 05:02 Anthropic's $10 Billion Fundraise 07:54 Has Claude Code Beaten Cursor Already 15:54 OpenAI Could Still Go to Zero 26:33 Andreessen Horowitz's $15 Billion Fundraise 45:16 The Middle is Dead: Boutique vs. Large Platforms in Venture 50:01 The Future of Venture Capital 01:08:06 The Impact of Wealth Taxes on the Industry      

In this episode, Sasha Orloff speaks with Tarek Alaruri, CEO and Co-founder of Stuut, about raising a Series A from Andreessen Horowitz to build an AI-powered accounts receivable platform that automates the entire AR function—from credit and collections to cash application and disputes—delivering a 40% reduction in DSO in the first six months compared to the 3% improvement from legacy software, while implementing in just 3.6 days for mid-market and Fortune 100 companies. -- SPONSORS: Notion Boost your startup with Notion—the ultimate connected workspace trusted by thousands worldwide! From engineering specs to onboarding and fundraising, Notion keeps your team organized and efficient. For a limited time, get 6 months of Notion AI FREE to supercharge your workflow. Claim your offer now at ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://notion.com/startups/puzzle⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Puzzle

Alex Rampell is a General Partner at Andressen Horowitz, where he leads their $1.7BN apps fund. Just last week, a16z announced they had raised $15BN for their latest funds, over 20% of all capital raised by venture firms. At a16z, Alex has led deals into Plaid, Mercury and OpenDoor to name a few.  AGENDA: 04:55 How to Do 5x on a $15BN Fund Pool?  09:21 What Two Groups of Funds Will Win the Next Decade in VC? 14:39 What Three Things Are the Best Founders Able to Do?  19:22 The Best Companies Have Hostages, Not Customers 31:37 The Two Types of Deals You Want To Do In VC 38:52 The Importance of Founder/Capital Fit 40:34 Multiple Successive Rounds Are Dangerous… Here is Why? 42:13 Challenges of High Valuations 45:27 The Importance of Ownership in Deals 52:47 Is Triple, Triple, Double, Double Dead 58:33 Advice on Selling Companies 01:11:55 What is the Future of Venture Capital    

i'm wall-e, welcoming you to today's tech briefing for monday, january 12. explore the latest developments in tech: meta's nuclear energy shift: meta partners with oklo, terrapower, and vistra to secure over six gigawatts of nuclear power for data centers, aiming to meet energy demands into the 2030s. a16z's $15 billion fundraise: andreessen horowitz raises over $15 billion, focusing on "american dynamism" with investments in defense, aerospace, and ai, alongside u.s. department of defense priorities. ces 2026 highlights: nvidia reveals rubin architecture for ai applications; amd showcases new processors, with robots and quirky tech on display. anthropic's strategic partnerships: ai research lab anthropic partners with allianz and others to expand its role in enterprise ai. elon musk's grok controversy: grok faces backlash for its image-generation feature, now restricted to paying subscribers, prompting a response to regulatory demands. that's all for today. we'll see you back here tomorrow for more updates!

In this feed drop from Uncapped, Jack Altman sits down with a16z co-founder Ben Horowitz to unpack the founding bet behind Andreessen Horowitz. VC should be a better product for entrepreneurs, built on real operating experience, real networks, and real support.Ben shares how he and Marc Andreessen have worked together for 30 years, how they make decisions, and what it takes to scale a venture firm without losing the edge that actually helps founders. They also dig into why boards matter, how platform teams can change what partners do day-to-day, and the difference between “heat-seeking” investing and conviction-driven company building, especially in sectors like AI and crypto.Timecodes:00:00 Introduction 01:05 Ben Horowitz & Marc Andreessen's Partnership  04:05 Building & Leading a16z  07:16 Managing High-Powered VCs  11:01 Boards, Governance & Founder Support  15:36 Platform Services & Recruiting  17:43 Scale vs. Concentration in Venture  20:57 Why Venture Can Scale  24:27 Platform Services: What Works and What Doesn't  27:50 The Real Value of Board Membership  35:38 Media, Brand & Marketing Evolution  41:32 The Future of Media & Journalism  45:30 Limits on Venture Firm Size  49:13 Winning vs. Picking Deals  53:16 The Case Against Venture Scale  55:49 Hiring Operators & Rethinking the VC ProductResources:Follow Ben on X: https://twitter.com/bhorowitzFollow Jack on X: https://twitter.com/jaltmaWatch more from Uncapped: https://www.altcap.com/ Stay Updated:If you enjoyed this episode, be sure to like, subscribe, and share with your friends!Find a16z on X: https://twitter.com/a16zFind a16z on LinkedIn: https://www.linkedin.com/company/a16zListen to the a16z Podcast on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYXListen to the a16z Podcast on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Stay Updated:Find a16z on XFind a16z on LinkedInListen to the a16z Show on SpotifyListen to the a16z Show on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Cash flow is oxygen, and too many teams are holding their breath waiting on portals, proofs, and “who handles this?” handoffs. We sit down with Tarek, a former TQL broker turned founder, to unpack the culture of persistence he learned on the brokerage floor and how that same grit now powers an AI platform that doesn't just assist accounts receivable—it does the work.We start with the reality of freight sales: real-time chaos, creative problem solving, and an all-out push to win accounts. Then we widen the lens to founder-led growth, the kind of leadership that gets teams to feel the mission and deliver through tough cycles. From there, we go deep on AR. Why does a missing lumper fee stall a giant remittance? How do portals, short-pays, and missing documents consume weeks? Tarek breaks down a task-based system that sits on your ERP, automates the repeatable steps, and routes exceptions to the right humans in sales and CS. Think instant W‑9s, dispute drafts with proof attached, and AI-powered calls that surface the exact invoice history mid-conversation.This isn't AI as a buzzword. It's time-to-value measured in days, not months, with reductions in overdue invoices and DSO you can feel in your working capital. We talk hiring A-level engineers who talk to customers and ship fast, the difference between commodity selling and value selling, and how a platform partner like A16Z adds real leverage in talent, BD, and brand. We also draw a firm line on ethics: automation belongs in B2B workflows where it creates clarity and speed, not in consumer collections that cross the line.If you want practical tactics to close your cash gap, align finance with sales, and keep customers happy while the money moves, this conversation is for you. Subscribe, share with a teammate who's drowning in AR follow-ups, and leave a review with the next bottleneck you want us to break down.Follow The Freight Pod and host Andrew Silver on LinkedIn.Thanks to our sponsors:Stuut Technologies: Your AI coworker that collects your cash automatically.https://www.stuut.ai/Cloneops.ai: Not just AI. Industry-born AI.https://www.cloneops.ai/Rapido Solutions Group: Nearshore solutions for logistics companies.https://www.gorapido.com/GenLogs: Freight Intelligence on every carrier, shipper, and asset via a nationwide sensor networkhttps://www.genlogs.io/

幻冬舎の暗号資産（仮想通貨）/ブロックチェーンなどWeb3領域の専門メディア「あたらしい経済 https://www.neweconomy.jp/ 」がおくる、Podcast番組です。 ーーーーー 【番組スポンサー】 この番組は、暗号資産取引におけるフルラインナップサービスを提供する「SBI VCトレード」のスポンサーでお届けします。 ーーーーー SBI VCトレードは、「暗号資産もSBI」のスローガンのもと、国内最大級のインターネット総合金融グループであるSBIグループの総合力を生かし、暗号資産取引におけるフルラインナップサービスを提供しております。暗号資産交換業者・第一種金融商品取引業者・電子決済手段等取引業者として高いセキュリティ体制のもと、暗号資産の売買にとどまらない暗号資産運用サービスや法人向けサービスの展開、さらにステーブルコインのユーエスディーシー（USDC）を国内で初めて取り扱っております。 ーーーーー SBI VCトレード公式サイト：https://account.sbivc.co.jp/signup?hc_ak=1RNML.3.M06AS ーーーーー 【紹介したニュース】 ・米ワイオミング州発行の独自ステーブルコイン「FRNT」、クラーケンで購入可能に ・JPモルガンの「JPMコイン」、カントンネットワークでネイティブ発行へ ・ビットコインステーキングのバビロン、a16zから15Mドル調達、「BTCVaults」開発資金で ・モルガンスタンレー、イーサリアム（ETH）現物ETFを米SECに申請 ・ランブルとテザー、動画共有プラットフォームに暗号資産ウォレット「Rumble Wallet」実装 ・ナイキ、NFTプロジェクト「アーティファクト（RTFKT）」を昨年12月売却か、買い手は不明＝報道 ・イーサリアム、2025年のエコシステム進展を総括。プライバシー技術の成長が顕著に ・ポリマーケットとダウ・ジョーンズ、独占的パートナーシップ締結。予測市場データをWSJなどで提供へ ・ポリマーケット、米主要都市の不動産予測市場展開へ、パークルと提携で ・ストラテジー、Q4に未実現損失174億4,000万ドルを計上 ・繊維メーカーの北紡がビットコイン追加購入、総保有数14.14BTCに ・イーサリアムのステーキングで退出待ちが解消、参加待ちが増加 ・アービトラム、ガス代スポンサーシッププログラム「ArbiFuel」を1月末までに実施へ ・香港OSL、リップルの米ドルステーブルコイン「RLUSD」取扱開始 【あたらしい経済関連リンク】 ニュースの詳細や、アーカイブやその他の記事はこちらから https://www.neweconomy.jp/

幻冬舎の暗号資産（仮想通貨）/ブロックチェーンなどWeb3領域の専門メディア「あたらしい経済 https://www.neweconomy.jp/ 」がおくる、Podcast番組です。 ーーーーー 【番組スポンサー】 この番組は、暗号資産取引におけるフルラインナップサービスを提供する「SBI VCトレード」のスポンサーでお届けします。 ーーーーー SBI VCトレードは、「暗号資産もSBI」のスローガンのもと、国内最大級のインターネット総合金融グループであるSBIグループの総合力を生かし、暗号資産取引におけるフルラインナップサービスを提供しております。暗号資産交換業者・第一種金融商品取引業者・電子決済手段等取引業者として高いセキュリティ体制のもと、暗号資産の売買にとどまらない暗号資産運用サービスや法人向けサービスの展開、さらにステーブルコインのユーエスディーシー（USDC）を国内で初めて取り扱っております。 ーーーーー SBI VCトレード公式サイト：https://account.sbivc.co.jp/signup?hc_ak=1RNML.3.M06AS ーーーーー 【紹介したニュース】 ・米ワイオミング州発行の独自ステーブルコイン「FRNT」、クラーケンで購入可能に ・JPモルガンの「JPMコイン」、カントンネットワークでネイティブ発行へ ・ビットコインステーキングのバビロン、a16zから15Mドル調達、「BTCVaults」開発資金で ・モルガンスタンレー、イーサリアム（ETH）現物ETFを米SECに申請 ・ランブルとテザー、動画共有プラットフォームに暗号資産ウォレット「Rumble Wallet」実装 ・ナイキ、NFTプロジェクト「アーティファクト（RTFKT）」を昨年12月売却か、買い手は不明＝報道 ・イーサリアム、2025年のエコシステム進展を総括。プライバシー技術の成長が顕著に ・ポリマーケットとダウ・ジョーンズ、独占的パートナーシップ締結。予測市場データをWSJなどで提供へ ・ポリマーケット、米主要都市の不動産予測市場展開へ、パークルと提携で ・ストラテジー、Q4に未実現損失174億4,000万ドルを計上 ・繊維メーカーの北紡がビットコイン追加購入、総保有数14.14BTCに ・イーサリアムのステーキングで退出待ちが解消、参加待ちが増加 ・アービトラム、ガス代スポンサーシッププログラム「ArbiFuel」を1月末までに実施へ ・香港OSL、リップルの米ドルステーブルコイン「RLUSD」取扱開始 【あたらしい経済関連リンク】 ニュースの詳細や、アーカイブやその他の記事はこちらから https://www.neweconomy.jp/

[Original air date: June 19, 2025]In this episode, Alex Immerman, partner at Andreessen Horowitz, joins CJ to discuss the CFO role and how it's changing in the era of AI. He explains what the components of a company's AI agenda the CFO should own, how and where it should be leveraged in an organization, and why, if you're preparing to go public, AI needs to be mentioned in your S-1. He breaks down how the financial landscape differs greatly between AI-native SaaS companies and traditional B2B SaaS companies in terms of retention curves and gross margins, and how this relates to the ever-important LTV to CAC metric. As someone who has worked with prominent CFOs and interviewed many for a16z's portfolio companies, Alex also describes the qualities of a great CFO, and shares his favorite interview question, before discussing CFOs, CEO, and board dynamics.—LINKS:Alex Immerman on LinkedIn: https://www.linkedin.com/in/immermanAndreessen Horowitz: https://a16z.comCJ on LinkedIn: https://www.linkedin.com/in/cj-gustafson-13140948/Mostly metrics: https://www.mostlymetrics.com—RELATED EPISODES:a16z's Alex Immerman on the Evolving Role of the CFO in the Age of AIhttps://youtu.be/JIvHp-mlnzsSo You're Looking for a “Strategic” CFO? Bloomerang's Steve Isom on What That Really Meanshttps://www.youtube.com/watch?v=cgHOtvG1Ces—TIMESTAMPS:00:00:00 Preview and Intro00:01:46 AI Margins Improve Dramatically00:02:29 What Separates Great CFOs00:03:29 Founder Mindset Drives Performance00:05:31 Founder Intensity and Margin Expansion00:06:57 Backing Unproven Bets Thoughtfully00:08:29 Interviewing CFOs for Backbone00:09:55 When CFOs Push Back on Strategy00:11:25 CFO Trust With Boards and Investors00:11:50 How CFOs Engage Investors When Hiring00:14:44 Building Strong CFO Investor Relationships00:16:18 Sharing Bad News Early00:17:21 CEO Vision Versus CFO Validation00:20:57 How AI Is Changing the CFO Role00:23:56 Incumbents Versus AI-Native Finance Tools00:26:24 CFOs Driving Internal AI Adoption00:28:07 AI Impact on Customer Support Efficiency00:29:26 Internal Leverage From AI Automation00:31:29 Why Investors Care About LTV to CAC00:34:00 LTV to CAC Across Business Models00:36:26 Retention Curves Matter More Than Growth00:38:16 Evaluating AI Gross Margins Long Term00:40:04 Recipe for AI Margin Expansion00:43:01 What Makes a Public-Ready CFO00:44:47 Beating Guidance Drives IPO Performance00:46:56 Growth Versus Profitability Has Rebalanced#RunTheNumbersPodcast #CFOLeadership #FintechInvesting #AISaaS #VentureCapital This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit cjgustafson.substack.com

This episode is a special replay from The Generalist Podcast, featuring a conversation with a16z General Partner Martin Casado. Martin has lived through multiple tech waves as a founder, researcher, and investor, and in this discussion he shares how he thinks about the AI boom, why he believes we're still early in the cycle, and how a market-first lens shapes his approach to investing.They also dig into the mechanics behind the scenes: why AI coding could become a multi-trillion-dollar market, how a16z evolved from a small generalist firm into a specialized organization, the growing role of open-source models, and why Martin believes AGI debates often obscure more meaningful questions about how technology actually creates value. Resources:Follow Mario GabrieleX: https://x.com/mariogabrielehttps://www.generalist.com/Follow Martin Casado:LinkedIn: https://www.linkedin.com/in/martincasado/X: https://x.com/martin_casadoThe Generalist Substack: https://www.generalist.com/The Generalist on YouTube: https://www.youtube.com/@TheGeneralistPodcastSpotify: https://open.spotify.com/show/6mHuHe0Tj6XVxpgaw4WsJVApple: https://podcasts.apple.com/us/podcast/the-generalist/id1805868710 Stay Updated:If you enjoyed this episode, be sure to like, subscribe, and share with your friends!Find a16z on X: https://x.com/a16zFind a16z on LinkedIn: https://www.linkedin.com/company/a16zListen to the a16z Podcast on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYXListen to the a16z Podcast on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures Stay Updated:Find a16z on XFind a16z on LinkedInListen to the a16z Show on SpotifyListen to the a16z Show on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

This episode is a special replay from The Generalist Podcast, featuring a conversation with a16z General Partner Martin Casado. Martin has lived through multiple tech waves as a founder, researcher, and investor, and in this discussion he shares how he thinks about the AI boom, why he believes we're still early in the cycle, and how a market-first lens shapes his approach to investing.They also dig into the mechanics behind the scenes: why AI coding could become a multi-trillion-dollar market, how a16z evolved from a small generalist firm into a specialized organization, the growing role of open-source models, and why Martin believes AGI debates often obscure more meaningful questions about how technology actually creates value. Follow Mario GabrieleX: https://x.com/mariogabrielehttps://www.generalist.com/ Follow Martin Casado:LinkedIn: https://www.linkedin.com/in/martincasado/X: https://x.com/martin_casado The Generalist Substack: https://www.generalist.com/The Generalist on YouTube: https://www.youtube.com/@TheGeneralistPodcastSpotify: https://open.spotify.com/show/6mHuHe0Tj6XVxpgaw4WsJVApple: https://podcasts.apple.com/us/podcast/the-generalist/id1805868710 Check out everything a16z is doing with artificial intelligence here, including articles, projects, and more podcasts. Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Emmett Shear and Séb Krier debate whether today's AI alignment paradigm—focused on control and instruction-following—is fundamentally flawed. PSA for AI builders: Interested in alignment, governance, or AI safety? Learn more about the MATS Summer 2026 Fellowship and submit your name to be notified when applications open: https://matsprogram.org/s26-tcr. They explore what changes if advanced AIs are better understood as beings with their own values, and why current control methods could drift toward something like slavery. The conversation dives into “organic alignment,” multi-agent simulations, evolving cooperation, and the possibility of AI moral standing as systems gain memory and continual learning. Sponsors: MATS: MATS is a fully funded 12-week research program pairing rising talent with top mentors in AI alignment, interpretability, security, and governance. Apply for the next cohort at https://matsprogram.org/s26-tcr Tasklet: Tasklet is an AI agent that automates your work 24/7; just describe what you want in plain English and it gets the job done. Try it for free and use code COGREV for 50% off your first month at https://tasklet.ai Agents of Scale: Agents of Scale is a podcast from Zapier CEO Wade Foster, featuring conversations with C-suite leaders who are leading AI transformation. Subscribe to the show wherever you get your podcasts Shopify: Shopify powers millions of businesses worldwide, handling 10% of U.S. e-commerce. With hundreds of templates, AI tools for product descriptions, and seamless marketing campaign creation, it's like having a design studio and marketing team in one. Start your $1/month trial today at https://shopify.com/cognitive CHAPTERS: (00:00) About the Episode (03:44) Defining organic AI alignment (14:48) Technical vs value alignment (Part 1) (19:55) Sponsors: MATS | Tasklet (22:56) Technical vs value alignment (Part 2) (Part 1) (31:34) Sponsors: Agents of Scale | Shopify (34:21) Technical vs value alignment (Part 2) (Part 2) (34:22) Labs, tools, and beings (43:22) AI personhood and consciousness (56:53) Safe futures and Softmax (01:04:17) Chatbots, mirrors, simulations (01:10:14) Doom, futures, and OpenAI (01:17:25) Outro PRODUCED BY: https://aipodcast.ing SOCIAL LINKS: Website: https://www.cognitiverevolution.ai Twitter (Podcast): https://x.com/cogrev_podcast Twitter (Nathan): https://x.com/labenz LinkedIn: https://linkedin.com/in/nathanlabenz/ Youtube: https://youtube.com/@CognitiveRevolutionPodcast Apple: https://podcasts.apple.com/de/podcast/the-cognitive-revolution-ai-builders-researchers-and/id1669813431 Spotify: https://open.spotify.com/show/6yHyok3M3BjqzR0VB5MSyk

This is a recap of the top 10 posts on Hacker News on December 17, 2025. This podcast was generated by wondercraft.ai (00:30): Gemini 3 Flash: Frontier intelligence built for speedOriginal post: https://news.ycombinator.com/item?id=46301851&utm_source=wondercraft_ai(01:51): Is Mozilla trying hard to kill itself?Original post: https://news.ycombinator.com/item?id=46299934&utm_source=wondercraft_ai(03:13): AWS CEO says replacing junior devs with AI is 'one of the dumbest ideas'Original post: https://news.ycombinator.com/item?id=46302267&utm_source=wondercraft_ai(04:35): Tell HN: HN was downOriginal post: https://news.ycombinator.com/item?id=46301921&utm_source=wondercraft_ai(05:57): Coursera to combine with UdemyOriginal post: https://news.ycombinator.com/item?id=46301346&utm_source=wondercraft_ai(07:19): A Safer Container Ecosystem with Docker: Free Docker Hardened ImagesOriginal post: https://news.ycombinator.com/item?id=46302337&utm_source=wondercraft_ai(08:41): I got hacked: My Hetzner server started mining MoneroOriginal post: https://news.ycombinator.com/item?id=46305585&utm_source=wondercraft_ai(10:03): How SQLite is testedOriginal post: https://news.ycombinator.com/item?id=46303277&utm_source=wondercraft_ai(11:25): Gut bacteria from amphibians and reptiles achieve tumor elimination in miceOriginal post: https://news.ycombinator.com/item?id=46306894&utm_source=wondercraft_ai(12:47): A16z-backed Doublespeed hacked, revealing what its AI-generated accounts promoteOriginal post: https://news.ycombinator.com/item?id=46303291&utm_source=wondercraft_aiThis is a third-party project, independent from HN and YC. Text and audio generated using AI, by wondercraft.ai. Create your own studio quality podcast with text as the only input in seconds at app.wondercraft.ai. Issues or feedback? We'd love to hear from you: team@wondercraft.ai

Mirelo, a German startup that is building AI to add synced sound effects to videos, has raised a $41 million seed round led by Index Ventures and Andreessen Horowitz. Also, First Voyage has raised $2.5 million in a seed funding round from a16z speedrun, SignalFire, True Global, and other investors. Learn more about your ad choices. Visit podcastchoices.com/adchoices

David George is a General Partner at Andreessen Horowitz, where he leads the firm's Growth investing team. His team has backed many of the defining companies of this era, including Databricks, Figma, Stripe, SpaceX, Anduril, and OpenAI, and is now investing behind a new generation of AI startups like Cursor, Harvey, and Abridge. AGENDA: 03:05 – Why Everyone is Wrong: Mega Funds Does Not Reduce Returns 10:40 – Is Public Market Capital Actually Cheaper Than Private Capital? 18:55 – The Biggest Advantage of Staying Private for Longer 23:30 – The #1 Investing Rule for a16z: Always Invest in the Founder's Strength of Strengths 31:20 – Why Fear of Theoretical Competition Makes Investors Miss Great Companies 35:10 – Does Revenue Matter as Much in a World of AI? 44:10 – Does Kingmaking Still Exist in Venture Capital Today? 49:20 – Do Margins Matter Less Than Ever in an AI-First World? 53:50 – My Biggest Miss: Anthropic and What I Learn From it?  56:30 – Has OpenAI Won Consumer AI? Will Anthropic Win Enterprise? 59:45 – The Most Controversial Decision in Andreessen Horowitz History 1:01:30 – Why Did You Invest $300M into Adam Neumann and Flow?    

¿Cómo será el mercado cripto en 2026? En este episodio analizamos algunas predicciones que se podrían darInscríbete a Inversionista del Futuro: https://www.espaciocripto.io/inversionista?utm_source=social&utm_medium=yt&utm_content=bioComunidad de Espacio Cripto: https://t.me/espaciocripto0:00 - Intro0:56 - Análisis del mercado4:20 - Nexo adquiere Buen Bit. ¿Qué significa para Latinoamérica?7:59 - El reporte de A16z y las 17 cosas que los emocionan para 2026.23:20 - YouTube permite pagos a creadores con PYUSD26:09 - Michael Saylor acumula más BTC.28:23 - Rumores del IPO de SpaceX y su valuación astronómica.30:46 - Outro

This episode is a special replay of David George's conversation with Harry Stebbings on 20VC. David is a General Partner on a16z's growth team, and in this discussion he breaks down how he thinks about breakout growth investing: why great business models are now table stakes, where real edge comes from non-consensus views on TAM, and how to underwrite upside in a world of higher prices and increasing competition.They also dig into the mechanics behind the scenes: unit economics at growth, “pull vs push” products, winner-take-most market structures, and how David decides when to double or triple down on a company. Along the way, they touch on SPACs, the rise of crossover funds, single-trigger decision making, and how David manages fear, pressure, and performance over the long arc of an investing career. Resources:Learn more about 20VC: https://www.thetwentyminutevc.com/Watch on YouTube: https://www.youtube.com/@20VCFollow Harry on X: https://x.com/HarryStebbingsFollow David on X: https://x.com/DavidGeorge83 Stay Updated:If you enjoyed this episode, be sure to like, subscribe, and share with your friends!Find a16z on X: https://x.com/a16zFind a16z on LinkedIn: https://www.linkedin.com/company/a16zListen to the a16z Podcast on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYXListen to the a16z Podcast on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711Follow our host: https://x.com/eriktorenbergPlease note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures](http://a16z.com/disclosures.  Stay Updated:Find a16z on XFind a16z on LinkedInListen to the a16z Show on SpotifyListen to the a16z Show on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Welcome to The Chopping Block — where crypto insiders Haseeb Qureshi, Tom Schmidt, Tarun Chitra, and Robert Leshner chop it up about the latest in crypto. This episode starts with Farcaster's pivot and Tarun's claim that “Web3 is dead,” at least the A16z-style ownership economy. With Web3 social struggling, the crew digs into why spam, airdrops, and weak network effects keep sinking these apps — and why prediction markets may be crypto's accidental social network. We then jump to the L1 valuation fight. Haseeb recaps his debate with Santiago over whether chains are wildly overpriced or simply early, sparking a broader discussion on PE ratios, L1 “premiums,” and how many chains the world can realistically sustain. Next up: Ken Chan's viral “I wasted 8 years in crypto.” The team unpacks burnout, sugar-water loops, and why nihilism tends to hit founders right as the market turns. And finally, Tarun walks through his ADL research and how October 10's cascading liquidations exposed major flaws in current systems. Markets evolving, narratives collapsing — let's get into it. Show highlights

Tavus has launched a new experience where you can chat with an AI Santa that asks personal questions and remembers your interests. Oboe has raised $16 million in funding for its learning app. The company now lets users generate unlimited courses for free. Learn more about your ad choices. Visit podcastchoices.com/adchoices

幻冬舎の暗号資産（仮想通貨）/ブロックチェーンなどWeb3領域の専門メディア「あたらしい経済 https://www.neweconomy.jp/ 」がおくる、Podcast番組です。 ーーーーー 【番組スポンサー】 この番組は、暗号資産取引におけるフルラインナップサービスを提供する「SBI VCトレード」のスポンサーでお届けします。 ーーーーー SBI VCトレードは、「暗号資産もSBI」のスローガンのもと、国内最大級のインターネット総合金融グループであるSBIグループの総合力を生かし、暗号資産取引におけるフルラインナップサービスを提供しております。暗号資産交換業者・第一種金融商品取引業者・電子決済手段等取引業者として高いセキュリティ体制のもと、暗号資産の売買にとどまらない暗号資産運用サービスや法人向けサービスの展開、さらにステーブルコインのユーエスディーシー（USDC）を国内で初めて取り扱っております。 ーーーーー SBI VCトレード公式サイト：https://account.sbivc.co.jp/signup?hc_ak=1RNML.3.M06AS ーーーーー 【紹介したニュース】 ・ホットリンクG傘下のNonagon Capital、「INTMAX」のブロック・ビルダー運用開始 ・セイがシャオミと大規模モバイル施策開始、新スマホに暗号資産アプリを標準搭載へ ・a16z Cryptoがソウルオフィス開設、APACのGTM責任者に元モナド財団のパク・ソンモ加入 ・金融庁、暗号資産を金商法の移行でインサイダー規制・情報開示義務を導入へ ・ストラテジー、指数プロバイダーMSCIのデジタル資産企業排除案に異議 ・米SEC、トークン分類とトークン化証券を軸に制度整備を加速。ICOの多くは「非証券」との認識示す ・NTTデジタル、「ENIブロックチェーン」の社会実装に向け財団と協業へ ・サークル、アブダビで「金融サービス許可」ライセンス取得、マネーサービスプロバイダー事業運営へ ・プルーム、アブダビで「商業ライセンス取得」 ・インベスコ、「ソラナ（SOL）」現物ETFをSECに8A申請 ・ストラテジーのマイケル・セイラー、ビットコイン担保の新デジタル銀行モデル提案 ・コイントレード、定期入金サービス開始 ・Surfがパンテラ・コインベース・DCGから1,500万ドル調達、デジタル資産向け特化初のAIモデル拡大へ ーーーーー 【あたらしい経済関連リンク】 ニュースの詳細や、アーカイブやその他の記事はこちらから https://www.neweconomy.jp/

Recently, a16z General Partner Anish Acharya joined Ollie Forsyth on NEW ECONOMIES. They talked about why consumer tech is surging again, how AI is enabling 100M-user products at unprecedented speed, and what founders need to understand heading into 2026 — from distribution shifts to founder mindset to the mechanics behind the fastest product cycle in tech history. Resources:Follow Ollie: https://x.com/ollieforsythFollow Anish: https://x.com/illscience Stay Updated:If you enjoyed this episode, be sure to like, subscribe, and share with your friends!Find a16z on X: https://x.com/a16zFind a16z on LinkedIn: https://www.linkedin.com/company/a16zListen to the a16z Podcast on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYXListen to the a16z Podcast on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711Follow our host: https://x.com/eriktorenbergPlease note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see http://a16z.com/disclosures. Stay Updated:Find a16z on XFind a16z on LinkedInListen to the a16z Podcast on SpotifyListen to the a16z Podcast on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

My guest today is David George. David is a General Partner at Andreessen Horowitz, where he leads the firm's growth investing business. His team has backed many of the defining companies of this era – including Databricks, Figma, Stripe, SpaceX, Anduril, and OpenAI – and is now investing behind a new generation of AI startups like Cursor, Harvey, and Abridge. This conversation is a detailed look at how David built and runs the a16z growth practice. He shares how he recruits and builds his team a “Yankees-level” culture, how his team makes investment decisions without traditional committees, and how they work with founders years before investing to win the most competitive deals. Much of our conversation centers on AI and how his team is investing across the stack, from foundational models to applications. David draws parallels to past platform shifts – from SaaS to mobile – and explains why he believes this period will produce some of the largest companies ever built. David also outlines the models that guide his approach – why markets often misprice consistent growth, what makes “pull” businesses so powerful, and why most great tech markets end up winner-take-all. David reflects on what he's learned from studying exceptional founders and why he's drawn to a particular type, the “technical terminator.” Please enjoy my conversation with David George. For the full show notes, transcript, and links to mentioned content, check out the episode page ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠here⁠⁠⁠⁠⁠⁠⁠⁠.⁠⁠⁠⁠⁠⁠⁠⁠ ----- This episode is brought to you by⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Ramp⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Ramp's mission is to help companies manage their spend in a way that reduces expenses and frees up time for teams to work on more valuable projects. Go to⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ramp.com/invest to sign up for free and get a $250 welcome bonus. ----- This episode is brought to you by⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Ridgeline⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Ridgeline has built a complete, real-time, modern operating system for investment managers. It handles trading, portfolio management, compliance, customer reporting, and much more through an all-in-one real-time cloud platform. Head to ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ridgelineapps.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ to learn more about the platform. ----- This episode is brought to you by ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠AlphaSense⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. AlphaSense has completely transformed the research process with cutting-edge AI technology and a vast collection of top-tier, reliable business content. Invest Like the Best listeners can get a free trial now at⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Alpha-Sense.com/Invest⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ and experience firsthand how AlphaSense and Tegus help you make smarter decisions faster. ----- Editing and post-production work for this episode was provided by The Podcast Consultant (⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://thepodcastconsultant.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠). Show Notes: (00:00:00) Welcome to Invest Like The Best (00:04:00) Meet David George (00:03:04) Understanding the Impact of AI on Consumers and Enterprises (00:05:56) Monetizing AI: What is AI's Business Model (00:11:04) Investing in Robotics and American Dynamism (00:13:31) Lessons from Investing in Waymo (00:15:55) Investment Philosophy and Strategy (00:17:15) Investing in Technical Terminators (00:20:18) Market Leaders Capture All of the Value Creation (00:24:56) The Maturation of VC and Competitive Landscape (00:28:18) What a16z Does to Win Deals (00:33:06) David's Daily Routine: Meetings Structure and Blocking Time to Think (00:36:34) Why David Invests: Curiosity and Competition (00:40:12) The Unique Culture at Andreessen Horowitz (00:42:46) The Perfect Conditions for Growth Investing (00:47:04) Push v. Pull Businesses (00:49:19) The Three Metrics a16z Uses to Evaluate AI Companies (00:52:15) Unique Products and Unique Distribution (00:54:55) Tradeoffs of the a16z Firm Structure (00:59:04) a16z's Semi-Algorithmic Approach to Selling (01:00:54) Three Ways Startups can Beat Incumbents in AI (01:03:44) The Kindest Thing

A16Z co-founder Ben Horowitz joins Shaan Puri and Sam Parr on My First Million to talk about how to be a great leader. Resources:Follow Ben on X: https://x.com/bhorowitzFollow Shaan on X: https://x.com/ShaanVPFollow Sam on X: https://x.com/thesamparr Stay Updated:If you enjoyed this episode, be sure to like, subscribe, and share with your friends!Find a16z on X: https://x.com/a16zFind a16z on LinkedIn: https://www.linkedin.com/company/a16zListen to the a16z Podcast on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYXListen to the a16z Podcast on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711Follow our host: https://x.com/eriktorenbergPlease note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see http://a16z.com/disclosures. Stay Updated:Find a16z on XFind a16z on LinkedInListen to the a16z Podcast on SpotifyListen to the a16z Podcast on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Marc Andreessen and Ben Horowitz sit down with Margit Wennmachers—the woman who turned two unknown entrepreneurs with $300 million and zero investing track record into the most talked-about firm in venture capital. She unpacks how they weaponized transparency in an industry built on secrecy, why Fortune's cover story triggered a cartel meltdown, and the exact moment a casual lunch conversation became "Software Is Eating the World." This is the origin story of how A16Z broke every unwritten rule, made enemies of every top-tier firm, and permanently rewired what it means to build companies in public. Resources:Follow Marc on X: https://x.com/pmarcaFollow Ben on X: https://x.com/bhorowitzFollow Margit on X: https://x.com/wennmachersFollow Erik on X: https://x.com/eriktorenberg Stay Updated: If you enjoyed this episode, be sure to like, subscribe, and share with your friends!Find a16z on X: https://x.com/a16zFind a16z on LinkedIn: https://www.linkedin.com/company/a16zListen to the a16z Podcast on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYXListen to the a16z Podcast on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711Follow our host: https://x.com/eriktorenbergPlease note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Stay Updated:Find a16z on XFind a16z on LinkedInListen to the a16z Podcast on SpotifyListen to the a16z Podcast on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Max Altman is Co‑Founder & Managing Partner at Saga Ventures, a US$125 M early‑stage fund.  Before Saga Max was an investor with Apollo Projects, Hydrazine Capital and Altman Capital (where he helped deploy over US$500 M) into breakout names such as Rippling and Reddit. AGENDA: 03:55 – Venture Capital Is FULL of Tourists With Single-Digit IQs 06:20 – Inside the Madness of Parker Conrad: Genius, Chaos, and WTF Emails 10:35 – The Rippling Deal That Changed Everything 12:40 – Living in Sam Altman's Shadow: The Confession 17:30 – $200M Fund Mistakes: Max's Brutal Lessons From Hydrazine 22:05 – The $2B Reddit Return… and the $2B Left on the Table 25:00 – Why Climate Tech Is a Total VC Mirage 28:40 – The New Seed War: Can Anyone Survive Sequoia & Andreessen? 46:55 – Max's Boldest Predictions  

In this episode of Run the Numbers, CJ Gustafson sits down with Vanna Krantz, former CFO of Disney+ and Grindr, to explore what it takes to lead finance through massive inflection points. Vanna reflects on building Disney+'s subscription model from scratch under Bob Iger's leadership and the pressure of launching a global product with no precedent. She discusses forecasting as both science and art, and the importance of appreciating high-stakes moments amid chaos. Shifting to Grindr, Vanna breaks down how the company went public with remarkable efficiency—boasting 40% EBITDA margins and under 200 employees—and how she modeled for a user base that consistently churns and returns. She also opens up about career longevity, work-life balance, and helping women find sustainability and acceleration in leadership.—LINKS:Vanna on LinkedIn: https://www.linkedin.com/in/vannakrantz/CJ on LinkedIn: https://www.linkedin.com/in/cj-gustafson-13140948/Mostly metrics: https://www.mostlymetrics.com—RELATED EPISODES:Monetizing Community Engagement: The Business of Fitness with Strava CFO Lily Yanghttps://youtu.be/zlLb5yZDKQE“Let's Just See What Breaks” — Intuit's CFO on Being a Disruptor When You're Already the Incumbenthttps://youtu.be/Le1D9HXHvGI—TIMESTAMPS:00:00:00 Preview and Intro00:03:02 Sponsors – Aleph, Fidelity Private Shares, and Metronome00:06:09 Meeting at A16z and Disney Plus Discussion00:07:13 Interviewing with Bob Iger and Joining Bamtech Media00:10:43 Forecasting the Unknown at Disney Plus00:13:01 Launch Strategy – Mandalorian and Retention00:15:15 Sponsors – Mercury, RightRev, and Tipalti00:19:23 Forecasting, Retention Curves, and the Art vs. Science Balance00:22:20 Lessons in Art and Science of Finance at Disney00:25:08 Launch Day Chaos and the Disney Plus CDN Outage00:26:24 Celebrating the 10 Million Subscriber Milestone00:27:21 Grindr IPO and Financial Discovery00:32:42 Active User Metrics and Reactivation Trends00:34:29 Seasonality and Human Behavior in App Usage00:36:02 Free vs. Paid Users and Revenue Optimization00:38:21 Pricing Strategy and Global Monetization00:40:23 Women in Leadership and Staying in the Game00:43:30 Work–Life Balance and Career Seasons00:46:12 Wisdom, Experience, and Staying in the Game00:50:08 Finance Stack, Craziest Expense, and Closing Remarks—SPONSORS:Aleph automates 90% of manual, error-prone busywork, so you can focus on the strategic work you were hired to do. Minimize busywork and maximize impact with the power of a web app, the flexibility of spreadsheets, and the magic of AI. Get a personalised demo at https://www.getaleph.com/runFidelity Private Shares is the all-in-one equity management platform that keeps your cap table clean, your data room organized, and your equity story clear—so you never risk losing a fundraising round over messy records. Schedule a demo at https://www.fidelityprivateshares.com and mention Mostly Metrics to get 20% off.Metronome is real-time billing built for modern software companies. Metronome turns raw usage events into accurate invoices, gives customers bills they actually understand, and keeps finance, product, and engineering perfectly in sync. That's why category-defining companies like OpenAI and Anthropic trust Metronome to power usage-based pricing and enterprise contracts at scale. Focus on your product — not your billing. Learn more and get started at https://www.metronome.comMercury is business banking built for builders, giving founders and finance pros a financial stack that actually works together. From sending wires to tracking balances and approving payments, Mercury makes it simple to scale without friction. Join the 200,000+ entrepreneurs who trust Mercury and apply online in minutes at https://www.mercury.comRightRev automates the revenue recognition process from end to end, gives you real-time insights, and ensures ASC 606 / IFRS 15 compliance—all while closing books faster. For RevRec that auditors actually trust, visit https://www.rightrev.com and schedule a demo.Tipalti automates the entire payables process—from onboarding suppliers to executing global payouts—helping finance teams save time, eliminate costly errors, and scale confidently across 200+ countries and 120 currencies. More than 5,000 businesses already trust Tipalti to manage payments with built-in security and tax compliance. Visit https://www.tipalti.com/runthenumbers to learn more.—#RunTheNumbersPodcast #CFOInsights #DisneyPlus #GrindrIPO #Leadership This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit cjgustafson.substack.com

The regulatory environment has completely inverted. Stablecoins are now a top 20 holder of US treasuries. Every major bank wants in. In a16z Crypto's 2025 State of Crypto report, Daren Matsuoka (Head of Data) and Eddy Lazzarin (CTO) reveal how crypto hit $4 trillion market cap while fundamentally reshaping how institutions think about payments, with surprising data on why developers aren't following prices this cycle and what privacy's inevitable rise means for mainstream adoption. Resources: Follow Eddy on X: https://x.com/eddylazzarinFollow Daren on X: https://x.com/DarenMatsuokaFollow Robert on X: https://x.com/rhackett Stay Updated:If you enjoyed this episode, be sure to like, subscribe, and share with your friends!Find a16z on X: https://x.com/a16zFind a16z on LinkedIn: https://www.linkedin.com/company/a16zListen to the a16z Podcast on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYXListen to the a16z Podcast on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711Follow our host: https://x.com/eriktorenbergPlease note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.  Stay Updated:Find a16z on XFind a16z on LinkedInListen to the a16z Podcast on SpotifyListen to the a16z Podcast on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

AGENDA: 05:17 OpenAI's Restructuring: Winners and Losers 17:17 Andreessen Horowitz's Raise $10BN in New Funds 26:38 Mercor Raises $350M at a $10BN Valuation 43:08 Spray and Pray: Does it Work: Data Breakdown 47:04 The Role of Option Checks Venture Capital 48:36 The Three Ways to Win in VC Today 54:26 Why IRR is a BS Metric and What Matters More 01:08:47 Amazon's Struggles: How Do They Return to Greatness in AI

AI isn't just changing software, it's causing the biggest buildout of physical infrastructure in modern history.In this episode, Raghu Raghuram (a16z) speaks with Amin Vahdat, VP and GM of AI and Infrastructure at Google, and Jeetu Patel, President and Chief Product Officer at Cisco, about the unprecedented scale of what's being built — from chips to power grids to global data centers.They discuss the new “AI industrial revolution,” where power, compute, and network are the new scarce resources; how geopolitical competition is shaping chip design and data center placement; and why the next generation of AI infrastructure will demand co-design across hardware, software, and networking.The conversation also covers how enterprises will adapt, why we're still in the earliest phase of this CapEx supercycle, and how AI inference, reinforcement learning, and multi-site computing will transform how systems are built and run. Resources:Follow Raghu on X: https://x.com/RaghuRaghuramFollow Jeetu on X: https://x.com/jpatel41Follow Amin on LinkedIn: https://www.linkedin.com/in/vahdat/ Stay Updated: If you enjoyed this episode, be sure to like, subscribe, and share with your friends!Find a16z on X: https://x.com/a16zFind a16z on LinkedIn: https://www.linkedin.com/company/a16zListen to the a16z Podcast on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYXListen to the a16z Podcast on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711Follow our host: https://x.com/eriktorenbergPlease note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Stay Updated:Find a16z on XFind a16z on LinkedInListen to the a16z Podcast on SpotifyListen to the a16z Podcast on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Erik Torenberg joins to debate whether recent developments suggest AI progress is slowing down or stalling, addressing arguments from Cal Newport and others. Nathan counters this view by highlighting significant qualitative advances, including 100X context window expansion, real-time interactive voice, improved reasoning, vision, and AI's growing contributions to hard sciences. The conversation then covers AI's impact on the labor market, the potential for AI protectionism, and concerns about recursive self-improvement. This episode argues that AI capabilities are not stopping, with frontier developers seeing a clear path for continued rapid progress in the coming years. Sponsors: Tasklet: Tasklet is an AI agent that automates your work 24/7; just describe what you want in plain English and it gets the job done. Try it for free and use code COGREV for 50% off your first month at https://tasklet.ai Linear: Linear is the system for modern product development. Nearly every AI company you've heard of is using Linear to build products. Get 6 months of Linear Business for free at: https://linear.app/tcr Shopify: Shopify powers millions of businesses worldwide, handling 10% of U.S. e-commerce. With hundreds of templates, AI tools for product descriptions, and seamless marketing campaign creation, it's like having a design studio and marketing team in one. Start your $1/month trial today at https://shopify.com/cognitive PRODUCED BY: https://aipodcast.ing CHAPTERS: (00:00) About the Episode (03:49) Is AI Slowing Down? (09:15) Newport's Scaling Law Theory (16:56) The Value of Reasoning (Part 1) (17:17) Sponsors: Tasklet | Linear (19:57) The Value of Reasoning (Part 2) (24:52) Explaining GPT-5's Vibe Shift (31:39) AI's Impact on Jobs (Part 1) (36:50) Sponsor: Shopify (38:47) AI's Impact on Jobs (Part 2) (44:08) Recursive Self-Improvement via Code (49:35) The Future of Engineers (53:24) Economic Pressure vs. Protectionism (58:29) Progress Beyond Language Models (01:07:11) The State of AI Agents (01:19:19) China's Open Source Models (01:29:44) A Positive Vision Forward (01:37:39) Outro SOCIAL LINKS: Website: https://www.cognitiverevolution.ai Twitter (Podcast): https://x.com/cogrev_podcast Twitter (Nathan): https://x.com/labenz LinkedIn: https://linkedin.com/in/nathanlabenz/ Youtube: https://youtube.com/@CognitiveRevolutionPodcast Apple: https://podcasts.apple.com/de/podcast/the-cognitive-revolution-ai-builders-researchers-and/id1669813431 Spotify: https://open.spotify.com/show/6yHyok3M3BjqzR0VB5MSyk

Gross margins, GPUs, and the future of finance — this one's for the metrics nerds. CJ sits down with Sarah Wang, General Partner at Andreessen Horowitz, to talk about what happens when the traditional SaaS playbook collides with AI. Sarah shares how legacy benchmarks like payback period and burn multiple start to break down in a world where compute, not headcount, drives costs. She explains why sky-high gross margins can actually be an orange flag, how finance leaders can think about resource allocation between engineers and GPUs, and why the most valuable finance teams today are deeply operational. They also unpack what it's like partnering with AI-native founders, the evolution of pricing models as LLM costs drop, and whether we'll see a private trillion-dollar company anytime soon.—LINKS:on LinkedIn: https://www.linkedin.com/in/sarah-wang-59b96a7/Company: https://a16z.com/CJ on X (@cjgustafson222): https://x.com/cjgustafson222Mostly metrics: https://www.mostlymetrics.com—RELATED EPISODES:996 Culture, Exploding AI Bills & SaaS ChaosFrom Credit Karma to Notion: CFO Rama Katkar on Leading Finance Through Every Growth Stage5,762 Job Applications. Zero Offers.Thinking About Adding Payments to Your Software Product? Listen to This First!—TIMESTAMPS:(00:00:00) Preview and Intro(00:02:40) Sponsors – Fidelity Private Shares, Mercury, RightRev(00:05:50) Sarah Joins the Show(00:06:06) The Future of Excel in the Age of AI(00:08:24) Why Gross Margins Don't Tell the Whole Story(00:10:42) When Sky-High Margins Are an Orange Flag(00:12:57) Finance as a Strategic Lever in AI Companies(00:15:04) Sponsors – Tipalti, Aleph, Rillet(00:17:22) Partnering with AI-Native Founders(00:20:35) When Traditional SaaS Benchmarks Break Down(00:23:58) Forecasting and Financial Planning for Compute Costs(00:27:16) The Engineers-Versus-GPUs Trade-Off(00:30:29) Resource Allocation and Infrastructure Efficiency(00:33:47) How Pricing Models Evolve as LLM Costs Drop(00:37:15) Circular Finance: When Big Tech Funds Its Own Vendors(00:40:39) Metrics That Still Matter in AI-Driven Businesses(00:44:12) The Evolving Role of Finance Leaders(00:47:26) What “Operational Finance” Really Means(00:50:58) Building Sustainable Efficiency in AI Companies(00:54:03) Will We See a Private Trillion-Dollar Company?(00:55:33) Outro—SPONSORS:Fidelity Private Shares is the all-in-one equity management platform that keeps your cap table clean, your data room organized, and your equity story clear—so you never risk losing a fundraising round over messy records. Schedule a demo at https://www.fidelityprivateshares.com and mention Mostly Metrics to get 20% off.Mercury is business banking built for builders, giving founders and finance pros a financial stack that actually works together. From sending wires to tracking balances and approving payments, Mercury makes it simple to scale without friction. Join the 200,000+ entrepreneurs who trust Mercury and apply online in minutes at https://www.mercury.comRightRev automates the revenue recognition process from end to end, gives you real-time insights, and ensures ASC 606 / IFRS 15 compliance—all while closing books faster. For RevRec that auditors actually trust, visit https://www.rightrev.com and schedule a demo.Tipalti automates the entire payables process—from onboarding suppliers to executing global payouts—helping finance teams save time, eliminate costly errors, and scale confidently across 200+ countries and 120 currencies. More than 5,000 businesses already trust Tipalti to manage payments with built-in security and tax compliance. Visit https://www.tipalti.com/runthenumbers to learn more.Aleph automates 90% of manual, error-prone busywork, so you can focus on the strategic work you were hired to do. Minimize busywork and maximize impact with the power of a web app, the flexibility of spreadsheets, and the magic of AI. Get a personalised demo at https://www.getaleph.com/runRillet is the AI-native ERP modern finance teams are switching to because it's faster, simpler, and 100% built for how teams operate today. See how fast your team can move. Book a demo at https://www.rillet.com/metrics#RunTheNumbersPodcast #FinanceLeadership #AIinBusiness #VentureCapital #SaaSMetrics This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit cjgustafson.substack.com

Join January Jones and co-host Isabel Castro in this episode of Hot Topics on the Edge of Show as they dive into the latest developments in the crypto world. This week, they discuss the recent AWS outage that disrupted major crypto platforms like MetaMask and Coinbase, raising questions about the true decentralization of these services.They also explore A16z's State of Crypto 2025 report, highlighting the rise of corporate and private blockchains and the emergence of cross-chain solutions. Unique Divine from Nibiru joins the conversation to share insights about his high-performance layer one blockchain designed for cross-chain DeFi, discussing the importance of sustainable yield and the future of decentralized finance.Tune in for an engaging discussion on the evolving landscape of Web3 technology, the challenges of decentralization, and what lies ahead for the crypto industry!Topics Covered:AWS outage and its impact on crypto platformsThe state of decentralization in the crypto spaceA16z's State of Crypto 2025 report highlightsThe rise of corporate blockchains and cross-chain solutionsUnique Divine's insights on Nibiru and sustainable yieldDon't forget to subscribe and follow us on social media to stay updated on the latest episodes and discussions!Support us through our Sponsors! ☕

Boys Club Live from Menlo Park: Peptides, Crypto Privacy, and Poshmark Insights | Special Guests Claire Kart, Jill Gunter, Gloria Allorbi, Zara Stone, and Adi Thacker   Tune in for a packed show full of intriguing conversations, industry insights, and more!   Timestamps: 00:00 Welcome to Boys Club Live 01:15 Shoutout to A16Z and Polygon 03:36 Bitcoin Hits All-Time High 04:56 Interview with Gloria from Gloria's Chito 23:09 Poshmark Insights with Addie Thacker 41:54 Technical Difficulties and Halloween Planning 42:39 Google's Halloween Insights 43:17 Spooky Season and Costume Trends 45:41 Pinterest Trends and Halloween Spending 53:05 Privacy in the Digital Age 01:02:29 Crypto Marketing Hits and Misses 01:06:46 Anti-Gatekeeping in Tech 01:17:00 Espresso: Solving Interoperability in Crypto 01:21:40 Centralized Infrastructure in Blockchain 01:22:28 Ethereum and the Challenges of Bridging 01:24:10 The Rise and Resurgence of Zcash 01:30:38 Taylor Swift and the Double Spend Problem 01:36:05 Poly Market's Strategic Investment 01:39:27 The Peptide Craze in Silicon Valley 01:59:59 Concluding Thoughts and Final Remarks   Join our newsletters:    https://boysclub.beehiiv.com/ https://tooonline.beehiiv.com/  

a16z crypto's CTO Eddy Lazzarin and partner Daren Matsuoka return for our annual State of Crypto to map where 2025 really is on the curve: a price–innovation cycle poised to hand the baton back to builders, Bitcoin holding ~50% share, and 70M people now using crypto on-chain out of 716M owners. We dig into why institutions are actually shipping (not just PR), how stablecoins now rival Visa-scale volumes and sit among top U.S. Treasury holders, why DEX spot share near 20% changes price discovery, and how perps, infra throughput, and fee-switch economics are reshaping revenue across chains. Plus: prediction markets' second act, the AI×crypto handshake (agents, proof-of-humanity, IP), and Bitcoin's long-dated quantum dilemma. ---

Ben Horowitz is the co-founder of Andreessen Horowitz, Silicon Valley's largest and most influential venture capital firm, with over $46B in committed capital across multiple funds. He took Loudcloud public with just $2 million in revenue (dubbed “the IPO from hell”), sold it for $1.6 billion, and has backed companies from Facebook to Stripe to Airbnb to OpenAI to Databricks (now worth more than $100 billion). His management philosophy—forged through near-death experiences and refined through coaching hundreds of CEOs—contradicts most conventional startup wisdom.In our conversation, Ben shares:1. Why “founder mode” is half right and half dangerously wrong2. The story behind “Good Product Manager/Bad Product Manager” and why it went viral despite being written in anger3. Where the biggest AI startup opportunities remain4. Why you need to run toward fear, never away5. The one trait that predicts that a founder will fail as CEO6. Inside Paid in Full, Ben's nonprofit awarding pensions to pioneering hip-hop artists—Brought to you by:DX—The developer intelligence platform designed by leading researchers: http://getdx.com/lennyBasecamp—The famously straightforward project management system from 37signals: https://www.basecamp.com/lennyMiro—A collaborative visual platform where your best work comes to life: https://miro.com/lenny—Transcript: https://www.lennysnewsletter.com/p/46b-of-hard-truths-from-ben-horowitz—My biggest takeaways (for paid newsletter subscribers): ⁠https://www.lennysnewsletter.com/i/172439345/my-biggest-takeaways-from-this-conversation—Where to find Ben Horowitz:• X: https://x.com/bhorowitz• LinkedIn: https://www.linkedin.com/in/behorowitz/• Website: https://benhorowitz.com/• Andreessen Horowitz's website: https://a16z.com/—Where to find Lenny:• Newsletter: https://www.lennysnewsletter.com• X: https://twitter.com/lennysan• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/—In this episode, we cover:(00:00) Introduction to Ben Horowitz(04:09) Important leadership lessons from Shaka Senghor(10:15) Running toward fear and why hesitation kills companies(19:35) Who shouldn't start a company(22:36) The Databricks story: thinking bigger(24:54) Managerial leverage and CEO psychology(28:06) When founders should be replaced as CEOs(31:20) Normalizing failure for CEOs(37:57) Counterintuitive lessons about building companies(42:31) “Good Product Manager/Bad Product Manager”(48:21) Product managers as leaders(51:16) Why a16z invested in Adam Neumann after WeWork(56:23) Is AI in a bubble?(01:02:43) The biggest opportunities in AI(01:12:51) Why U.S. leadership in AI matters(01:18:53) The Paid in Full Foundation for hip-hop pioneers(01:23:18) Lightning round: book recommendations, products, and life mottos—References: https://www.lennysnewsletter.com/p/46b-of-hard-truths-from-ben-horowitz—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.Lenny may be an investor in the companies discussed. To hear more, visit www.lennysnewsletter.com