美联储降息 50 基点、AI 取代呼叫中心、500 亿美元政府项目、VC 的艰难岁月与特朗普对阵哈里斯

Jason Calacanis (00:00:00): Right, everybody. Welcome back to the All-In Podcast. The channel's been active. We're in the afterglow. Chamath Palihapitiya (00:00:07): We're in the All-In Summit afterglow. Jason Calacanis (00:00:10): It's so glowing that Friedberg couldn't make it. He has been riding a high. Chamath Palihapitiya (00:00:16): Nick told me that he's seen him happy. We've only put out half the clips and they've already gotten 20 million views. Oh my lord. Jason Calacanis (00:00:24): I, you know, I I I So we'll be Chamath Palihapitiya (00:00:26): we'll be around 50 million, I think, when all the clips are released, then you let it bake for a couple of months. That is an astoundingly large amount Jason Calacanis (00:00:35): of reach. Yeah. And that's just YouTube. We're not doing it on the podcast feed Chamath Palihapitiya (00:00:38): right now. YouTube and X. Well, hopefully, we get Jason Calacanis (00:00:40): it on the podcast feed. We get another 50 million. But, Friedberg's in his afterglow couldn't make it, but he's very busy right now. Look how happy he is. The summit went well. Is that marijuana? Think he's making potatoes. I think that's his farm, but, I mean, the smile is incredible. It's marijuana. Chamath Palihapitiya (00:01:01): It's Friedberg's version of founder mode. Jason Calacanis (00:01:03): He's in fact Chamath Palihapitiya (00:01:04): that's Friedberg's founder mode. He's hitting the bong. His founder mode gives him a bunch of his. Speaker 3 (00:01:11): We'll let your winners ride. Rain man David Sacks. And it said we Jason Calacanis (00:01:26): He is, he's in the afterglow, and he won't be with us this week. But he David Sacks (00:01:33): He organized such a great conference. Don't you think, J.C.? Hell? Jason Calacanis (00:01:36): He did great. David Sacks (00:01:37): I mean, he really took charge of that and Jason Calacanis (00:01:40): He crashed. David Sacks (00:01:40): Just an amazing job. Jason Calacanis (00:01:42): I'd like to give him his flowers. Absolutely. He Chamath Palihapitiya (00:01:45): is, like, at least a trillion times better than the first and at least 50% better than the second. Jason Calacanis (00:01:50): I mean, that's how it should go. You know, when you create something in the world, Chamath, what you wanna do is you wanna hand it off to professional management to then scale it. Chamath Palihapitiya (00:01:59): Right? Not everybody can do the Jason Calacanis (00:02:01): creative act of actually forming something. You need to have these operators to go and then execute your vision. And, I just wanna give Freeberg flowers for executing incredibly well. We all play a role, Chamath. Sacks launched a tequila company. I wanna say thanks to Friedberg. He did all of these great speakers. Big thank you to our CEO, John, who put together all the operations. Nick did incredible. Nick did an incredible, incredible job with those opening graphics. They went viral. Zach helped with the graphics. You had young Spielberg chipping in. You had Laura did an amazing job with stage management. And, of course, you know, I focused on the moderation. I got a lot of great things. So everybody plays a role. You got Sacks with the tequila, Friedberg, Laura, Zach, Spielberg, Nick, John. Everybody brought something to the table. So congratulations to everybody. Chamath Palihapitiya (00:02:57): You scaled through people. That's it. Scale through people. Jason Calacanis (00:03:00): That's it. Did anybody get the joke? We, Chamath, everybody contributed. You understand? Sacks, new tequila company. John, operations. You have Friedberg content, me with them being the world's greatest moderator up there. David Sacks (00:03:15): What was Chamath's contribution? Showed Jason Calacanis (00:03:17): up. Chamath looked great. I showed up. That's just showed up. Showed up and looked great. I brought my two Chamath Palihapitiya (00:03:23): votes, and I Jason Calacanis (00:03:23): brought my vision. Absolutely. I would also say fan favorite. You know, what you really did that was amazing was you took a lot of selfies. I was very proud of both of you with the fan service. The fans were very pleased that you guys took so many selfies. You know, we got a lot of feedback too coming in. So it was pretty, pretty great feedback. David Sacks (00:03:51): Do you think that you did better as moderator because you finally let go of just the conference organization? Jason Calacanis (00:03:59): What do you think? Yeah. David Sacks (00:04:01): I think that you're able to focus on your unique value add instead of immersing yourself in a bunch of details that could be handled by the team. Jason Calacanis (00:04:10): I agree. It was absolutely fantastic. David Sacks (00:04:12): Process to get you to let go. Jason Calacanis (00:04:15): Well, you know, you have it's a fair point. I did people did say my moderation was dialed in, and I appreciate that positive feedback from everybody. And, yeah, there is something to having people you can trust with the content. You know? Chamath Palihapitiya (00:04:28): Your moderation was excellent this time. Jason Calacanis (00:04:30): Time. It was better Chamath Palihapitiya (00:04:31): than before because I think that you're actually exceptional as a moderator, and I think you're mostly average as a conference producer. Jason Calacanis (00:04:40): But I was like, oh, Chamath Palihapitiya (00:04:41): that's fair. I do think as a moderator, you're excellent. I mean, like, some of the most memorable moments were you basically drawing out contrasting opinions. And the way that the people engaged with them was so healthy and good. That was, I think, the recurring theme. So I give you an enormous amount of credit. I think you did an exceptional job, but I also think it's because you were able to focus on what you're great at. Jason Calacanis (00:05:06): I do agree with that. I was talking to Jade about it, and she said, and Nick also pointed out, you were really dialed in, JayCal. What's up? And I said, I'm not worrying about the party and the vendors and the front desk and the sponsors, and it is, actually. You're able to focus. Did you have some favorite moments yourself there, Sacks? Any favorite moments for your panels or things maybe that exceeded expectation for you? David Sacks (00:05:28): Well, I thought the Mearsheimer, Jeffrey Sachs panel was great. I thought it would be, which is why I helped organize it, but I was just glad that so many people in the audience reacted and said that was the surprise hit of the conference. Jason Calacanis (00:05:40): I would say that was my favorite of the event, one of the best panels I've Chamath Palihapitiya (00:05:43): ever heard in. Jason Calacanis (00:05:44): Part of. Chamath Palihapitiya (00:05:44): It's the most viewed. It's, like, slightly above Elon's one. Really? Oh, just behind you. David Sacks (00:05:49): Elon's slightly ahead, but, yeah, it's still, like, growing. It's like finding an audience. Chamath Palihapitiya (00:05:53): Well, I think that if you look at the one from last year, Graham Allison, where he got a standing ovation, the thing is there are these village elders where they are at a point in their life where they're willing to just be a truth teller, but oftentimes they're deplatformed and we have the ability to actually bring some of the smartest of them on and give them a voice. And it's incredible how much they resonate because what they say is so logical and sensible. So that's a really important thing that we have now at our disposal. And I think that people have really appreciated, you know? So we're like a, I think we're doing a really important job in doing that. And now the question is what village elders do we get next year to keep, you know, being Jason Calacanis (00:06:41): Well, give us your thoughts. You know, there's an All-In Twitter handle, and he's Chamath, David Sacks. And I'm at jasoninfriedberg@friedberg. Just tell us who you think would be great. But, Sacks, I know you're super excited and want to give Biden his flowers. The Fed just cut rates 50 bips, and the stock market is tearing it up right now. On Wednesday, the Fed cut interest rates by a half a percentage point, taking them down off of a 23-year high. We've been talking about this, god, for two years here on this podcast. First rate cut since March of 2020, which is about when we started this podcast. Jay Powell basically said the Fed thinks inflation is coming down to around 2% nicely, and they don't want the job market to soften any further than it already has. He also mentioned immigration has helped soften the market, the labor market as well, obviously, with all those new people looking for jobs. So in the last two months, July August, CPI has been at a 2 handle. We talked about that. 2.9% in July, 2.5% in August. Here's the CPI over the last decade. Obviously, massive boom in interest that you see there from 2021 to 2023. Many obviously think we're going to have more rate cuts, probably 25 every meeting for a little bit. And, Dow's already at an all-time high, surged 300 points on the news. Here's some interesting data about the 50 basis point kickoff cuts. So, this is where it gets interesting, Chamath. Fed only started publicizing their interest rate changes in 1994. Since '94, Fed has initiated a cutting cycle six times. Here's the chart. Take a good look at that. '95, '98, 2019, they started with 25 bps. '07, after the great financial crisis, they started with a 50 bp cut. So obviously, there was an emergency 50 bp cut in March of 2020 when COVID hit. '01, '07, 2020, very severe situations, and what happened in the markets is what I want to discuss with both of you today. In 2001, market fell 31% in the two years after that rate cut. In 2007, market fell 26% after two years. Jason Calacanis (00:09:04): So in 2020, despite all the fears, market ripped 44% over two years. What's the more likely scenario, Chamath? Is this similar to the dotcom great financial crisis or similar to 2020? Chamath Palihapitiya (00:09:19): Well, I think 2020, you have to put a big asterisk because the question is what would have happened had there not been COVID and had there not been an entire global shutdown? So if you go back to that chart, you could probably just extrapolate and cut out that part that's flat because the part that's flat from 2020 to 2022 was largely artificially created. Because on top of that, we injected so much money into the economy. The reality is we probably would have raised at some rate of change that you could have predicted from 2016. So what do you, what do you take away from that? I think that you have to like realize we're at a point in the economy where you cut rates because there's tension. And there's tension between employment and unemployment. There's tension between earnings, growth, and contraction. And so it's a stimulatory move. So if you look through that stimulatory move, why is the Fed doing this and why will they cut probably all the way down to 2 or 3% by the end of '26? It's because we now need to stimulate the economy again. So the reason why markets tend to fall once the rate cut cycle starts is because the next couple of quarters sort of demonstrate what I think the Fed is expecting, which is that there's pressure in the economy. We have not seen that flow through in earnings or in how companies describe markets on the field by and large, except for a few. So I think this part of the cycle now will be about all of these companies telling us whether there's nothing to see here or whether there is actual real pressure. And if there is real pressure, it'll probably look like the several times before where you're just gonna have to contract the value of financial assets because they're just not worth as much when they're earning less. Jason Calacanis (00:11:19): Okay. Sacks, any thoughts here? Just balls and shrinks. David Sacks (00:11:23): I think a lot of people are commenting on the fact that the only other two times where we've had a 50 basis point rate cut in modern history, it has been just before a recession. So I think this happened in 2001, 2007, right before the recession. And the Fed had to do a dramatic rate cut because they could see in the data that things were weakening. So a lot of people are asking the question, well, is that what's going on here now? Powell's comments, though, are indicating that the economy is in good shape. He said the economy is in very good shape that, basically indicating that they had tamed inflation and that they would look to cut another 50 basis points this year. So Powell's rhetoric is, in a way at odds with the magnitude of this cut, the, you know, so why didn't they just cut 25 basis points? I think people are trying to figure that out. Jason Calacanis (00:12:17): Reading David Sacks (00:12:18): the tea leaves into the tea. Jason Calacanis (00:12:20): Why 50? Because they could just do 25 a month Sure. For 5 months as opposed to 50 and hot. David Sacks (00:12:25): Yeah. If the economy is hot, why won't you tiptoe into rate cuts, and just do 25 now? Chamath Palihapitiya (00:12:31): That's the key thing. If you look at the dot plot and if you look at where the smart financial actors are betting where rates end, so it's hard to sort of, like, look at any point in time, 50 now, 25 later. What does it all mean? It's very hard to know. But what is much clearer is where do we think terminal rates will be even in the next 18 months. And it is dramatically lower from where they are now. And I think that supports Sacks, your argument that you just made, which is if you're going to basically cut this aggressively over the next year to year and a half by the estimates of very smart financial actors whose job it is to spend every day observing the Fed, then they must see something because otherwise, as you said, you could take a much more gradual approach. And so I think that the smart financial actors are guessing recession or guessing contraction. I think what they're also guessing is similar to nonfarm payrolls. We're going to go through a couple of difficult GDP revisions, probably downward. And I think that will have an impact on people's sense of how the economy is doing even more than what their sense is today, which is already teetering on it's at best okay. And I think all of that has to play itself out. So it's gonna be a very complicated and dynamic fall in that respect. Jason Calacanis (00:13:53): Yeah. And I think so much of this has to do with unemployment. We had that period where so many jobs were available. Remember, we talked about it here, 11, 12 million jobs available at the peak. We can debate the numbers, of course, but we all saw it where you just couldn't hire talent in America. There were so few people available to take positions. And man, has that changed. And you get to see it on the ground in early-stage startups where this whole narrative, I don't know if you saw it in your board meetings, but, hey. We can't find a person. Hey. We're looking. Hey. That search is still going. We're still looking for a director of sales. We're still looking for salespeople. We're still looking for developers. We're still looking for operations people. Now it's the opposite. It's like, I just I'm hiring producers here in Austin because I'm building it in my in-person studio. We had, like, I don't know, a dozen viable candidates for this position, and I had a hard time picking between, you know, the top three. Now that's distinctly different than my experience for the last five to 10 years where you were like, how do we how do we fill this role? So I think that employment has been broken. And that's the thing that has me concerned because with all these people who came in through the southern border and then you have people outsourcing to other countries, I wonder if Americans are gonna lose so many of these mid-paying jobs, and this will dovetail into our next story about Amazon making cuts. I'm very worried about the hollowing out of the upper middle class, that elite group of $150,000 jobs that then employ nannies and spend money in the economy. I wonder I don't know if you're seeing that in your company, Sacks. David Sacks (00:15:29): I'm not worried about the hollowing out of that class. Chamath Palihapitiya (00:15:33): You you have sustained for them. Jason Calacanis (00:15:35): But, I mean, just in terms of the labor market, what do you see, you know, in companies right now, you know, hiring the talent pool, etc.? David Sacks (00:15:45): Well, I mean, in tech, things are pretty good. I mean, they're not as absurdly frothy as they were during the bubble of 2020 and 2021, but things are good. You have this huge AI tailwind now, and there's just a ton of investment going into AI. There's a little bit of a tale of two cities going on. If you're in AI, things are really bubbly. And if you're outside AI, they've returned to much more normal levels in terms of valuation and company operations, all that kind of stuff. Just to go back to the state of the economy for a second, the reason why a lot of people were predicting a recession, including me for a while, is that the yield curve inverting has been an almost perfect gauge of whether a recession is coming. It's when basically the Fed raises short-term interest rates above long-term interest rates. Normally long rates are the ones that should be higher because investors demand a higher rate of return to tie up their money for longer. So something's really off and kind of broken when short rates go above long rates, the yield curve inverts, and it's always been the prelude to a recession. But the recession doesn't come when the yield curve inverts. It usually comes when the yield curve Jason Calacanis (00:16:59): And the David Sacks (00:16:59): reason for that is because the Fed now sees weakness and dramatically cuts the short rates. So in other words, it jacks up the short rates to control inflation. That works. It trickles through the economy. The economy cools down and the Fed says, oh, shit, maybe we've They slam on the brakes, and then they cut rates to basically make up for the effect in the economy. So the yield curve has finally de-inverted, and the question is just, do we now get that recession, or did the Fed manage this to a soft landing? I don't think we know. I'm not, I'm not, like, calling a recession, but this is the thing that people are concerned about. Jason Calacanis (00:17:34): Yeah. Well, Sacks, we were talking about AI in the group chat, right? David Sacks (00:17:37): Yeah. I think it's now becoming really clear that call centers are gonna be the first really big disruption caused by AI. Yeah. I mean, all the level one customer support is gonna get replaced by AI. I mean, LLMs plus voice because, you know, OpenAI just released their audio API. You saw that at the All-In Summit, we released a Mearsheimer AI. Jason Calacanis (00:18:02): Yeah. David Sacks (00:18:03): Where we trained it on all of his work, and you can go to Mearsheimer.ai and ask it questions. And it will tell you the answers in his voice because we cloned his voice using Resemble AI. Anyway, so AI can do voice now, and it can be trained extremely well on large datasets to give you answers to questions, which is pretty much what customer support is. So I think it's now becoming clear that I think within the next two to three years, you're gonna see a massive disruption in that industry. Jason Calacanis (00:18:31): I agree with that massively. And I think there's another underreported story, which is people don't like to call and talk to a customer service agent, like an actual human, if they can avoid it. They would much rather go on YouTube and say, how do I fix this? Or, you know, ask ChatGPT, how do I fix this? It's like, I don't wanna waste another person's time. Just give me the answer as quick as possible and AI will give you the answer quicker. YouTube will give you the answer quicker. I've had so many times where I have people who work for me who are like, I don't know how to do that. And I literally would walk up to their computer and load YouTube and type in, how do I blank? And there's a video there. Watch it on 2x speed. You can do it. That's what's, you know, gonna also kill this. Like, I don't wanna talk to a human. Just change my flight. Just, you know. But David Sacks (00:19:19): you're talking about disruption. Yeah. I mean, you're talking about disruption. Call centers are a very big part of the economy in certain geographies. Oh. Denver, Salt Lake, I mean, parts of Florida. Jason Calacanis (00:19:29): Arizona. Yeah. David Sacks (00:19:30): Yeah. Exactly. It's a really big deal if, like, half the cost gets ripped out of those call centers. Jason Calacanis (00:19:35): Where would you move those people? If you if you had your choice, could they move to sales? David Sacks (00:19:40): Well, I think sales will be the one that's disrupted after customer support, but, but I don't know. I think it's gonna be very disruptive. One of the reasons I think this is, you know, in the early days of LLMs, people were saying that legal services would be disrupted, and you saw some very highly valued startups rocketing up based on that. I think the problem with that is the error rate. So when you think about AI applications, you have to think about what is the tolerable error rate that the industry will allow because we know that AIs get things wrong. They can hallucinate and you're never gonna be able to make it perfect. I mean, you can improve the quality, but it's still going to have some errors. And when you're dealing with, like, legal services, for example, you just can't have mistakes. Jason Calacanis (00:20:26): This is David Sacks (00:20:26): not tolerated. However, customer support is different. Customer support is already organized into levels, level 1, level 2, level 3 based on difficulty. And there's already in a sense, a mechanism for failover if, like, the level 1 customer support person can't answer the question. They kick it up to level 2. So there's a place for LLMs to start in customer support, which is replacing all the level 1 and then working their way up the chain to level 2 as they get better and better. And so what I'm saying is that the level of accuracy now, especially with the new PhD-level reasoning models, is good enough. Yeah. We don't need to wait for, like, some perfect LLM model. And I think this is why this is gonna be a big, big disruption. Jason Calacanis (00:21:12): Let me tell you, you David Sacks (00:21:13): potentially are gonna have their jobs disrupted or at least transformed. Jason Calacanis (00:21:17): Well, it could be the end of the entire career as well, Chamath, if you were to look at this 4 by 4 sort of quadrant chart that Sacks is describing, which is the cost of an era, you know, and the actual complexity of the job perhaps, or the cost of the job. How do you look at this? I know you're working on software that kind of does this with your startup as well. Chamath Palihapitiya (00:21:44): I mean, I'll preview one use case from 8090, which is pretty stunning. You know, we work with a very large regulated, highly regulated company, public company. And they have a very complicated set of people and processes because of the field in which they're in. And David, your point is exactly right. It took us a fairly long time, but we're at a point now where we've been running AI-powered software versus the old legacy deterministic solution. And we've been running it at a 100% accuracy now for about 10 days. So this is still very new. And it's an incredible thing because to your point, our first version was like in the mid-80s. Then we were in the mid-90s. Then we were, you know, 97, 98%, but there were still errors. And it just took a lot of engineering to figure out how to get to a 100, but now it's at a 100 and it's been consistently at a 100. And so we're all kind of like scratching our head because now the next step is, well, what do we do to your point? What do we do? Do we, so we're figuring that out right now. But the art of the possible is that I think well-crafted AI software is as good as deterministic software in the sense that the error rates will be equivalent in production and at the level of a very highly regulated public company. And I think that's the gold standard because, in those sectors, those companies have zero tolerance. It's not a toy. It's not even, you know, level 1 customer support; it's system of record type work. Jason Calacanis (00:23:44): Yeah. Chamath Palihapitiya (00:23:45): But it shows what's possible. And to your point, Sacks, we're doing that today, even though they're the best models. Imagine how good those underlying models will get in a year from now. David Sacks (00:23:55): Yeah. Chamath Palihapitiya (00:23:55): Right? And you're able to take on more and more work. It's very stunning actually. It's really Jason Calacanis (00:24:00): Have you guys worked with the 01 preview yet? I just literally have been using this new reasoning engine that OpenAI released, and it is extraordinary. And it's kind of thinking about the next 3 or 4 prompts you would do. And I literally just got this while we're on the show. The thing that's hit the, I've hit the limit for my paid account because this thing is so intense on compute, I guess. Chamath Palihapitiya (00:24:23): Well, the thing with 01 is that I think it's starting to add reasoning. But the way that you do reasoning is sort of this idea that you have this chain of thought. And I think that that's a very powerful but early concept. And as we refine those ways in which these models get to better answers, the wonderful thing is that OpenAI will preview 001, and then they'll have the actual 01 production build probably in the next couple of months, which will be probably pretty spectacular. But then you'll see something from Claude. You'll see something from LLaMA. And the real art, I think, and this is where I do think it's a little bit of alchemy still, which I think is good because it keeps humans involved, all of us involved. Yes. Is how do you stitch all of those things together to get to a 0% error rate? What Sacks said, you know, how do you minimize the blast radius and how do you make sure these things are super high quality? David Sacks (00:25:20): Right. Jason Calacanis (00:25:21): Well, and people don't Chamath Palihapitiya (00:25:22): it's still a very hard technical problem. Go ahead, Sacks, Jason Calacanis (00:25:24): and then I'll I'll show you what David Sacks (00:25:25): so yeah. One of the reasons why I'm bullish on this customer support use case is because there's a very large dataset to train on. You've got all of the product documentation that companies already created. You've got all of the previous email support, you know, so and calls. Yeah. The calls have been recorded, so you can now train the AI on that. So there's a very large body of data to train the AI model on, and it's not necessarily the most proprietary. It's not like dealing with people's medical records or even confidential legal documents, something like that. So the data is readily available and then the foundation models are getting really good. I think there's a big question here about value capture, which is there's a number of startups now that are becoming very highly valued that are chasing this disruption, this certain customer support agent disruption, and they're getting into very high valuations, even unicorn valuations already. And the question is, well, wait. If the foundation models are advancing at such a rate Chamath Palihapitiya (00:26:25): Exactly. David Sacks (00:26:26): Like, a year from now, why couldn't a dev, like, a developer just a startup of a few guys take next year's model? It's such a good point. And then commoditize the Chamath Palihapitiya (00:26:35): You're making such a good point. So when we were trying to figure out, like, what applications we would build and, like, which sectors of the economy we would go after, I was like, guys, we gotta go after the hardest, most regulated places because those are the things and places and people that have absolutely zero tolerance for error and where you're going to need to do some amount of customization and specialization to actually solve these problems. And Sacks, to your point, like when you see and I said, you cannot we cannot touch customer service. We cannot touch it because it's going to get commoditized and run over by these foundational models within a year. Right. You'll you'll be able to do it on these it's just too easy. Jason Calacanis (00:27:21): You'll be able to do it on a local computer. I mean, you'll just download the entire database of every call on a MacBook with an M3. And by the way, Chamath Palihapitiya (00:27:28): just to build on that, the other thing that's now possible, and you saw this with Klarna because Klarna put out this, like, cryptic tweet slash press release where I think maybe it was in their earnings. Nick, maybe you can find this where they're like, we've deprecated Salesforce and Workday. Jason Calacanis (00:27:43): That was strange. Yeah. How how Chamath Palihapitiya (00:27:45): can a company that big deprecate those two systems of record? How is that even it's how is it possible? I think it means they're writing their own. Right? Well, I'll tell I'll tell you how it's possible. And so this is like this next crazy thing that's been happening. We've been doing a version of this to go after some other sources of software. We haven't had the balls, to be honest, to go after since for Workday, but here's how they do it. They write these agents and these agents can spawn other agents, right? So it's very classic kind of machine that builds the machine. And you start to observe the inputs and outputs of a system. Right? I'm hypersimplifying, but it'll make the point. And over time, what the agents start to do is by observing the inputs and the outputs, they start to guess on what the intervening code is and the code paths must be in the middle to generate the outputs based on these inputs. And so over time, what happens is you develop a digital twin and then you run that counterfactual against Workday or Salesforce. And then at some point you're like, it's the same. And then you say, you just said, turn it off, and you're saving yourself tens or hundreds of millions of dollars. So that's a version of what Klarna did. It takes an enormous amount of technical strength to do it. It also takes tremendous, I think, executive courage and leadership because I think that's a very difficult decision to embark on. But if you're an engineer, that must be an unbelievably exciting technical challenge to be a part of, but that's the basic premise of what they were able to do. Hopefully they share more and maybe they even open source what they did because I think it would just be an amazing thing for all of us to look at. Jason Calacanis (00:29:30): Yeah. I mean, to restate it, watch people use a piece of software. And then based on what they do, you could write the code, which you could take a video of a video game today, like Angry Birds, and somebody did this. You give the Angry Birds iPad, you know, game from 15 years ago to AI. It's gonna back into the code just by watching it. So why not just watch people use Salesforce or Workday? And those are very expensive products, thousands of dollars per user. Right? Chamath Palihapitiya (00:29:59): I wanna I wanna get Sacks' point of view. Like, the thing in enterprise software that we were always told is you cannot touch these systems of record. Don't ever start a systems of record company. Don't try to touch these systems of record companies. Don't, you know, try to disrupt them. It's an impossible task. But then the question is, if you have these things, why do you necessarily need a system of record in the way that you needed to before when you're writing all this clunky, deterministic? Well, that makes sense. David Sacks (00:30:27): Well, I saw the Klarna story where they said they were gonna rip out Salesforce and Workday because they're able to write their own bespoke code using AI. I mean, I have to say I'm a little bit skeptical of that story for a couple of reasons. One is if that's their goal, why wouldn't they have open-sourced this? These products they created, you might also get the whole ecosystem working on it because they're not trying to sell this product that they've internally created. They're just trying to rip out the cost. So why not let the whole ecosystem see it? The other thing is if it's so easy to do, why hasn't the market already been flooded with new startups that are effectively able to reverse engineer? Chamath Palihapitiya (00:31:05): I don't think you're right. I don't think it's easy to do because I don't think there's a generalization here that's productizable. Do you know what I mean? Like, I do think that these are very custom-specific things. So maybe there's, like, some scaffolding, but I don't think that that scaffolding has a ton of economic value. I think it's really good open-source stuff. Jason Calacanis (00:31:24): Yeah. Chamath Palihapitiya (00:31:24): I think it's what you build on top of it. And so that hasn't been figured out yet for David Sacks (00:31:29): sure. Yeah. Look. I, I think that if you're only using a few use cases of these big complicated software packages, then, yeah, it's probably easier than ever to deprecate them, you know, eliminate them from your stack and just have your own internal engineers build specifically what you need in a more tightly integrated way. I think that is possible. Chamath Palihapitiya (00:31:49): Nick, show this tweet to these guys. Jason Calacanis (00:31:53): Here's the tweet. Chamath Palihapitiya (00:31:54): This is and I'm not making a crazy one. Yeah. So so look at but look at the code look at the actual product itself for a second. David Sacks (00:32:03): Yeah. But the product's garbage. I mean, look how ridiculous this is. Chamath Palihapitiya (00:32:06): But that was 600,000,000. Sorry. It was a $1,000,000,000 that had my Okay. So here's David Sacks (00:32:10): the this is this is the same project. Jason Calacanis (00:32:13): Paid Oracle 600,000,000 to build our course management portal. It's built on top of Oracle's PeopleSoft suite, which they refused to customize without an extra 400,000,000 to hit 1,000,000,000 New Yorkers got the image below and pay 5,000,000 plus a year for hosting. David Sacks (00:32:28): Look. This is egregious government waste. I mean, that site looks like it's pathetic. I mean, honestly, this looks like it could have been done with a SharePoint site and you pay some consultant to stand it up for 1% of the cost, and there are better, more modern platforms than that. So this is just incredibly wasteful and inefficient government spending. Jason Calacanis (00:32:52): But they're going for a retro. They were going for a retro. They wanted to hearken back to the '90s. Chamath Palihapitiya (00:32:57): But the reason I wanted to show this to you is I think that these kinds of things will not be possible in the future. I just don't see how one could spend $1 billion if one tried to enable that feature. It'll be impossible. David Sacks (00:33:13): Right. But that $600 million that was wasted on that crappy portal, that shouldn't have happened even without AI. Right? Because there's, like, much better ways. You could buy a much better product for 1% of the cost. Or 0.1% of the cost. Jason Calacanis (00:33:29): There must be some regulatory capture going on here where somebody's got a record. No. It's like a 10 Chamath Palihapitiya (00:33:35): year trip. Jason Calacanis (00:33:35): That's what I'm saying. Like, a 10-year relationship with somebody in Albany that, you know, David Sacks (00:33:40): worked at Oracle previously. Just like fraud and abuse. It's the same thing that's happening with rural Internet. Jason Calacanis (00:33:46): Do you see that story? Paradoxically is our next story. So let's go for it. In related news of our government burning our money, rural broadband, rural broadband and EV charging, $42 billion and $7.5 billion, almost $50 billion combined. Let's just go over these two programs real quickly here. Both were part of the $1.2 trillion infrastructure bill in 2021. $42 billion carved out to provide high-speed internet to people living on farms in rural locations. $7.5 billion carved out to build 500,000 EV chargers over 10 years. It's been 1,000 days since the bill was passed. So let's check on the progress. Zero people have been connected according to FCC Commissioner Brendan Carr. And 8, 1, 2, 3, 4, 5, 6, 7, 8 e three chargers have been built as of May according to AutoWeek Magazine. What's even crazier, private industry already solved these problems. United Airlines just announced they're putting Starlink on a thousand of their planes, and they're gonna offer it for free. And Starlink now has 2,500 planes under contract with a bunch of other airlines. And, in the second half of 2023 alone, the private sector built over 1,000 charging stations in the U.S. These are two problems that have already been solved, Sacks. Why are we burning $50 billion in the future with this on things that have already been solved? We've solved for this. You and I own electric cars. I have Starlink. Answer. Chamath Palihapitiya (00:35:28): You know the answer. Say the answer, Jason. Jason Calacanis (00:35:30): Corruption. Chamath Palihapitiya (00:35:32): No. Come on, Jason. Jason Calacanis (00:35:33): Incompetence. Really? Graft. Keep going. I mean, you tell me. Corruption, graft, buying votes from your constituents? They haven't delivered any of it. Incompetence. Yes. David Sacks (00:35:50): Well, there's a couple things going on here. So one is typical government waste, fraud, and abuse where they've allocated $42 billion for rural Internet, haven't hooked anyone up, and we could spend a fraction of that giving people Starlink and allowing the private sector to do its job. Jason Calacanis (00:36:09): And why even pay for it? Why are we paying for it Speaker 3 (00:36:12): if it's Jason Calacanis (00:36:12): available for David Sacks (00:36:13): a hundred? That's the baseline, but it's worse than that because on top of the waste, fraud, and abuse, and the fact that the government is grossly incompetent and inefficient, you also have naked political retaliation going on here. Chamath Palihapitiya (00:36:26): That's the answer. David Sacks (00:36:27): Yeah. Exactly. And Brendan Carr, who's an FCC commissioner, pointed this out. He said that in 2023, the FCC canceled or revoked an $885 million contract with the company by claiming Starlink is not capable of providing high-speed internet. Then the year later that, yeah, of course that was a lie. And then a year later, the FCC is now claiming that Starlink provides so much high-speed internet that the word monopoly should be tossed out. Yeah. So look, this is just pure it's pure naked retaliation. The Biden-Harris administration doesn't want to admit that Elon has the best solution for rural internet, just like they couldn't admit he made the best electric cars. Remember when they did that EV summit and they didn't invite him? That was just nakedly political, because he's not. Right. So look, I mean, the Biden-Harris administration, it's blue no matter who. And Elon has drifted from being sort of independent and not aligned to Jason Calacanis (00:37:30): He was blue. That's what it is. David Sacks (00:37:31): I mean, he's voted for Jason Calacanis (00:37:32): Hillary and Obama, he said. David Sacks (00:37:34): He's no longer team blue, and so they're punishing him for this. Yeah. And it's costing taxpayers a huge amount of money. I think this is one of the worst decisions by the current administration. And if Trump gets in there, he should reverse it on day one. Jason Calacanis (00:37:47): Well, we need to investigate. I mean, I think how we got to the point of wasting $50 billion, that requires an investigation, I think. Chamath, your thoughts? Chamath Palihapitiya (00:37:57): One comment is, and this is so sad, but I'm so desensitized by the amount of waste that I don't know whether $50 billion is a lot or a little anymore when it comes to the United States government. Isn't that sad? Like because now everything I hear is an enormous hundreds of billions and trillions, but $50 billion is an enormous amount of money. Right? David Sacks (00:38:18): Well, that's such a good point. I remember, you know, back in the day, 60 Minutes used to do these segments on waste, fraud, and abuse at the Pentagon, different parts of the government, $42 billion just spent on something that really taxpayers could have for free or without the government getting involved and, you know, $42 billion that was lining someone's pocket when the service doesn't even work, that would have been a scandal and the media would have covered it, but the media doesn't even cover it these days. And again, it's because the media has become so tribal that it's better dead than red and blue no matter who. And so because the media would have to admit that Elon's already solved this problem, they just can't go there. They won't even cover this. And so we have no accountability. There's no accountability on the government. Chamath Palihapitiya (00:39:03): If I had to just take a step back and just generalize going forward, do we want to live in the kind of administrative state where they will pick people that they dislike based on totally random criteria, a tweet, a meme, a post, and then all of a sudden punish a bunch of the rest of us because of that? They're punishing all of America because they collect our taxes to waste on it. And then they punish the people that they actually say they're going to uplift by not delivering what they promised. And if you take Elon out of it for a second, the problem was when we crossed the chasm and did it with the first guy, him. But the reality is there's only one of him and then there's a lot of the rest of us. And what'll happen is people would just get added to this list of folks that certain nameless, faceless people in the administrative state dislike. And what happens is the country slows down and the country wastes money and the country pilfers it away and that has to stop. And so what really bothers me about these things is, a, I don't know how to desensitize myself to the fact that all of a sudden now because of just all of this sloppy waste, I didn't react as much as I should have to just $50 billion being flushed down the toilet on these two projects. And then, Jason, your point, it is a solved problem that you can give incredibly cheaply. And the fact that it's not left to private enterprise to solve this and instead it's just brazen partisanship combined with retaliation, combined with incompetence. Jason Calacanis (00:40:50): And we vote by giving this money to other vendors who are giving them donations. Chamath Palihapitiya (00:40:56): And just to give the Democrats their due, what happens if then Trump does the same thing for a solution that you support and you need and you think should be everywhere? The point is we don't want any of this stuff under any administration. Separate. And the minute that one administration breaks the seal and makes it acceptable, it becomes part of the water table. And that's the real problem. We broke the seal on this crazy multi, multi-trillion-dollar spending and it has just never stopped since then. Jason Calacanis (00:41:27): And, you know, the incentives really matter. If you look at a private company, if you were at Klarna and to our previous story, and you go to the boss and say, I know how to get rid of this wasteful spending we're doing here. We can get rid of all tier one calls with AI and save that money. You get a promotion. If you're in the government, you can't. If you're a politician and you cut this program, your constituents get upset, you don't have that stuff being built in your district, there's a perverse incentive that you can't buy the votes, which is why these folks are constantly trying to buy votes. And then second good Chamath Palihapitiya (00:42:01): news is the good news is I really applaud the people that have the courage to show this stuff on X, to tweet this stuff out so that the rest of us know about it and the person that talked about the NYC thing. But then the next step has to happen, which is that we all need to decide that this stuff needs to stop. Otherwise, it's gonna bankrupt our country. Jason Calacanis (00:42:22): And we have to celebrate it. That's the key. If we can celebrate people saving money again, like Millet is getting a lot of credit, and that's up to us. Leadership in podcasting or the media or influential people have followings. If you point out, hey, this is a waste. Go save this money and somebody does save the money. Well, why don't we start celebrating people saving the money and doing the right thing here? Because this is our children's future. Chamath Palihapitiya (00:42:47): Is it true that Kamala was the broadband czar that was responsible for this thing? Jason Calacanis (00:42:51): I mean, it's who knows? Chamath Palihapitiya (00:42:53): It's just no. Because I saw it. I saw that a bunch of senators wrote a letter to her, and they claimed that she was the broadband czar, but I don't know if that's true or not true and whether she was. Jason Calacanis (00:43:04): I mean, it's well, remember. David Sacks (00:43:05): She was the AI czar? I mean, the administration did put her nominally in charge of various technology initiatives. Jason Calacanis (00:43:12): Here's an idea. Save money. Get the best solution at the lowest price and then reevaluate that as you go. And I just want to point out with the it's a, this is a subtle point, but Elon also open-sourced his patents for the superchargers and let anybody do them. And he opened up the superchargers to other vehicles, which he didn't have to do. And when they gave him a loan back in the Solyndra days and the Fisker days, remember they gave these incentives in the form of loans? He's the only guy who paid it back. Everybody else failed. So now you're punishing the guy who actually built the infrastructure for both of these projects. So the reward for actually doing the right thing, which Starlink did, SpaceX did, and Tesla did, is to be punished, and then you're giving a leg up to somebody else who's building these chargers. Who's more qualified to build these chargers at scale? Or a satellite network at scale? Chamath Palihapitiya (00:44:04): The person who's already done it. He's already done it. I do worry that there's a growing version of the Elon Derangement Syndrome that's also kind of, like, festering. Jason Calacanis (00:44:15): Yeah. For sure. Which Chamath Palihapitiya (00:44:17): just it just stops people from thinking rationally. Jason Calacanis (00:44:20): Of course. I mean, we're talking about laying fiber lines, cable modems to people who are hundreds of miles into the countryside. That makes no sense when you can just beep, put a satellite dish up today. What are we even talking about? David Sacks (00:44:35): I mean, government has never been particularly efficient, but there was a period of time where people would at least care about wanting to make it more efficient. And it would be a scandal if there was political corruption to try and bias the result in a way that actually deprived the intended recipients of the program from getting the services they were supposed to get and cost the government way more money than it needed to. We're so far beyond being that country anymore where we actually debate the best policy. Now it's just like we're warring political tribes and the objective of the party is to punish its political opponents, to engage in retaliation, and to basically loot the public coffers as much as possible on behalf of their constituents. And that's what's basically happening. You know, it's completely dysfunctional. Jason Calacanis (00:45:26): Well, let's use this podcast. If you see government waste, tell us. David Sacks (00:45:30): And no one cares because the media doesn't really shine a light on it because they're completely tribalized as well. Chamath Palihapitiya (00:45:35): I agree with everything you're saying except the last part. I don't think it's on behalf of their constituents. I don't think any of us see any benefit from any of the spend. David Sacks (00:45:43): No. No. I meant their donors, their donor constituents. There's not the citizens of the country. Jason Calacanis (00:45:49): Yeah. Chamath Palihapitiya (00:45:49): Yeah. Yeah. Right. But who's winning in this? It's not like this $42 billion is it it's $42 billion lining the pockets of, I don't know, name names. David Sacks (00:45:56): For sure. How do you think your contracts get over to it? Jason Calacanis (00:45:58): Companies not gonna lay that fiber are gonna get that money. David Sacks (00:46:01): And then and then they're gonna kick Jason Calacanis (00:46:03): that bills of contributions. Chamath Palihapitiya (00:46:03): It's been it's been three or four years. They they haven't done a single thing. Jason Calacanis (00:46:07): I mean, I still think they'll cash the checks. Yeah. Chamath Palihapitiya (00:46:10): It seems like we're at the stage of just pure incompetence and retaliation. We're not even at the stage of actually then giving it to anybody else. Jason Calacanis (00:46:17): I mean, that would be still so they're giving the money away and David Sacks (00:46:20): they're so confident they're not Chamath Palihapitiya (00:46:21): getting the political benefit from it. David Sacks (00:46:23): No. They're so confident they can't get out of their own way, but somebody's getting that, call it $50 billion that we don't need to spend. And the way that money is awarded is gonna be political. Jason Calacanis (00:46:34): We're gonna do that. David Sacks (00:46:35): That they're gonna turn around and give big political contributions? Jason Calacanis (00:46:37): Of course Chamath Palihapitiya (00:46:38): they are. Jason Calacanis (00:46:38): Well, I Chamath Palihapitiya (00:46:38): think I think that I think the good news is that the more of these things we shine a light on, the harder it'll be to hide when these grants are actually given or what the execution is and to your point. List. Jason Calacanis (00:46:51): Let's start a running list. No. Chamath Palihapitiya (00:46:53): To your point, Sacks, maybe, like, you know, we need a revival of the 60 Minutes, you know, waste, fraud, and abuse. Jason Calacanis (00:46:58): On this program, we'll do it at the end of the show every time. We'll have a running list at allin.com of just every one of these scandals, and we'll feature it. So leak it to us first. Send it to us. My DMs are open. All right. Listen, early-stage investing has always been hard. There was a tweet storm this week that Y Combinator might be having a hard time replicating their early success. We'll discuss it now. A thread this week from ex-user Molson Hart caught a couple people's eyes. He made the case that it's been a rough decade for YC based on the accelerator's top companies page. YC lists its top companies by 2023 revenue there. And you'll notice there's not a lot of companies from the recent cohorts out of the 50 companies featured. Only three are from the classes after 2020, most of them being from the early Obviously, that's because they've been around longer, but it sparked a big discussion that there were so many winners from the 2009 to 2016 era, and that maybe the class size at YC has expanded a whole bunch, and maybe that's part of the problem. But there's a bigger problem in VC that we've talked about here. Here's a chart from Carta that just shows the percentage of VC funds that have made a distribution since 2017. Over 40% of 2018 vintage funds have not made a single distribution yet. And it's getting to the point, year 5, 6, or 7, where you probably should have had some distributions occur. Obviously, a lot of this has to do with maybe M&A and those early wins being taken off the table. We've talked about that a whole bunch, but here's the chart that kind of gets really interesting. An explosion in fund managers occurred, as we all know, and this chart shows from PitchBook the first-time VC managers that raised a second VC fund as a share of all first-time VC managers. And it's now down from above 50% to below, gosh, 15%. So what are your thoughts here, Chamath? Chamath Palihapitiya (00:48:57): My gosh. Venture is a really, really tough business. Every year for the last 6 or 7 years, I have published my returns, which most VCs don't wanna do. I do it because I go back and I look at it and I think having public accountability actually drives some good decisions. They may seem suboptimal in the moment, but they, in the long run, turn out to be good decisions. And the biggest one has been generating liquidity. So Nick, you can throw up this thing, but I'm sure there are funds in each of these vintages that have done way better than me. So I'm not saying, you know, it is what it is. But what I wanna point out is if I go and look inside of these funds and tell you how hard it has been to generate this DPI, it's like dragging an entire Jason Calacanis (00:49:58): sack of potatoes over the finish line. Chamath Palihapitiya (00:50:00): It's like a truck of dead bodies over a finish line. It is super, super hard. And the things that we have fought are two. One is that the gestation of companies has totally blown out. We used to be in a world where by year five, six, or seven, you could return money. You just can't do that anymore unless you get extraordinarily lucky, which by the way I got when Sacks was running Yammer. It was an enormous win for all of us, but that is just exceptionally rare. Jason Calacanis (00:50:33): And that was M&A in year what, five or six, Sacks? Chamath Palihapitiya (00:50:36): When they get so yeah, there's so few entrepreneurs capable of that. He's one of maybe five or ten. So other than that, I've never really had a company that has generated liquidity in year five, six, or seven. They've always generated, if they did generate it at all, in years 11, 12, 13. And so the problem with that is that at some point you have these paper marks that say you're winning and things are working but there's no path to liquidity. So then I, what I did was I stepped into the secondary markets and I would sell. And it would really upset certain founders. But I was very clear that when I was running outside capital and I was running outside capital on behalf of really organizations that I believed in, the Broad Foundation, the Mayo Clinic, Memorial Sloan Kettering. My job was to get them money back. You know, these were their pension funds. These were the things that they used to build facilities. Cancer research. Cancer research. I didn't have the, you know, ability to just sit on my hands and say, oh, you know what, year 15, don't worry. So it's just meant to say that the tactics of generating liquidity in venture are very misunderstood and very underappreciated. And even then you sell some things that are just absolute winners that had you waited another five or six years would have turned another, you know, one or two turns, but that's not the job. The job is not to maximize absolute every single win. The job is to return capital in a reasonable time period so that your investors don't run out of money to give you. Yeah. It's a tough game, man. It is really, really, really tough. Jason Calacanis (00:52:23): Yeah. And the insight Chamath Palihapitiya (00:52:25): And sorry, by the way, and I feel this now because, you know, the last five or six years has been entirely my own capital. And my gosh, it's hard. Yeah. Managing liquidity is it's impossible, especially when you can't rely on anybody else. So it's tough. Thank God Jason Calacanis (00:52:39): for the secondary markets even emerging because at the same time that the secondary markets emerged and people were willing to buy venture assets, you know, going into their second decade I Chamath Palihapitiya (00:52:50): would have been in real trouble without the without reasonably liquid myself included. Jason Calacanis (00:52:54): I mean, I Chamath Palihapitiya (00:52:54): My numbers my numbers would be a quarter of what they are. Jason Calacanis (00:52:58): Yeah. And I took advantage of almost every time I had one of those opportunities to sell some shares, pare some positions. And that's how we got our DPI as well because let's face it, Lina Khan and the anti-tech sentiment has led to these large companies not buying startups and instead they compete with them. They just say we'll build it in-house because you're not letting us buy it. And it's broken the entire ecosystem now. Chamath Palihapitiya (00:53:23): That's broken. The IPO process is broken. I tried to flip that on its head with SPACs. You know, some worked, some didn't, many didn't in the end. Many of mine didn't work out at the end. There was a period where it looked like it was working, but these are all attempts at changing the liquidity cycle. Yeah. Of these companies because the way that things stand today, we are not in a sustainable industry. It is if you raise funds and think about fee generation, but it is not if you think about returning money to founders, LPs, getting employees compensated for many years of, you know, toil that they put in. It's a very tough game right now. Jason Calacanis (00:54:06): Well, Sacks, right now, we're seeing people do things like selling, you know, their early SpaceX or their early Stripe, whatever it is, to other VCs, to later stage funds, a lot of ways to try to secure DPI. What's your thoughts on the state of venture today given all this data that we're looking at today? David Sacks (00:54:25): Well, two points. So first, I agree with Chamath that the amount of time it takes to generate an outcome for, I'd say, most startups is longer than the 10-year period of these funds. And these funds can be extended up to 12 years usually, but then what do you do after that? This takes a lot longer than that in a lot of cases to generate a meaningful outcome. I just had two companies that I invested in in my second fund. So in 2019 and 2020, so four years ago and five years ago, just got marked up and it was a big market that the company is doing well. I call them late bloomers. It took four to five years for them to accomplish what they wanted to in terms of building out the tech. I mean, I invested at the earliest stage, so that's how long it took. And now they just did growth rounds and they're kind of off to the races. But, you know, it could easily be 10 years from here to get to a liquidity event. So you're talking about more like 15-year funds. So I agree with that point. The second thing though, is that the big thing that's happened in our industry is we had a bubble in 2020 and especially 2021. And we just had a ton of capital come into the industry because the Fed and the federal government airdropped $10 trillion liquidity onto the economy in reaction to COVID and not all that money went into VC. It went into a lot of places, but the VC industry was flooded with cash. And you see this in the deployments. I mean, in those bubble years, there was something like $200 billion a year of capital deployment when normally it's $60 to $100 billion. So if twice the amount of money is going into the industry and is being deployed and rounds are now twice as big and valuations are twice as big, that has a huge outcome, a huge effect on returns. So for example, the average venture fund is like a 2x return, but if the entry prices were artificially double, then there goes your return right there. David Sacks (00:56:19): You get 2x to come to 1x. Jason Calacanis (00:56:20): So such a, David Sacks (00:56:21): Look, I think we're just in the hangover of this massive liquidity bubble that didn't originate in the venture capital industry. It came from, frankly, the federal government, but we're just downstream of that. Now, what I would say is I do think we're at the tail end of working that out. And the good news is that we now have maybe the most exciting tech wave ever, which is AI. Definitely the most exciting tech wave since the internet came along in the mid to late '90s. So the hope is we're finally going to have like really exciting things to invest in again. But, but, yeah, look. I think we're at the tail end of the last cycle and the beginning of a new cycle. Jason Calacanis (00:57:00): And vintage distortion is so real. You know? It's very hard to understand how each of these vintages with your late bloomers or overpriced things, companies getting $100 million rounds totally. At a $1 billion valuation before they have product-market fit. And those distortions were just so pronounced the last five to ten years that we're now sorting them out like a house of mirrors where you don't know who's tall, who's fat, who's skinny, what the reality is here. And the other big thing is this peanut butter effect that, you know, I tweeted about today. You know, during peak ZIRP, you had all these exceptional team members. You know, the number two, three, four, five person at a company that was doing great, they would leave to start their own company. So the talent got spread. Then you had so many of these founders rushing into the same vertical. So you'd have 20 startups because there was too much capital pursuing the same opportunity. You're pursuing the same opportunity. What happens to earnings? They get spread then. What happens to customers? They get spread across 20 different products competing for the same customer. And then what happens with, you know, ownership stakes for us as GPs and LPs, Chamath? The ownership stakes, because the valuations went up so much, they got spread like peanut butter. And instead of a Series A getting you 20% of a company, it got you 10. Instead of a seed check getting you 5 percent, it got you 1. There's no DPI possible. Chamath Palihapitiya (00:58:22): You nailed it and Sacks nailed it. But the thing to remember is both of those two things now work together to erode the return stream for the general partner, but really most importantly for the limited partner. So I do think that we are in a situation where the average returns are going to decay by 50 to 100% because of what Sacks said and because of what you said. On top of that, I don't think we know what the actual cap structure needs to be for a successful AI company. Is it 20 people that do the work of 2,000 now because they have all of these agents and systems that work on their behalf? If that's true, giving that company hundreds of millions of dollars is actually the opposite of what you wanna do. You wanna give that company 10 or 15 and then let them cook. And so we have a right-sizing of capital problem that needs to happen. The data would tell you though that the industry understands that. So the fact that we've gone from 50% of people being able to raise a fund to 12% means that a lot of people will get washed out of the industry, less capital being raised, which probably is foreshadowing the fact that these companies will need a lot less capital. But, you know, that has a lot of implications as it ripples through our economy. It has, I think it's very good for the early stage. I think, you know, you guys are very good there. You've talked about how it's good for you. It's very complicated, I think, for the expansion and growth stage capital. And then I think it's going to be, there's gonna be another turn on what happens on the IPO markets because you can't have so many companies waiting with very, very few ways of accessing public market capital and exposure. I just think that is fundamentally broken and we're gonna have to reinvent. We tried once with SPACs. We're gonna have to go back to the drawing board and try again. Jason Calacanis (01:00:11): Direct listings, secondary markets that are more fluid. I don't Chamath Palihapitiya (01:00:14): know what it is, but we need to do something because the status quo doesn't work. Jason Calacanis (01:00:18): I think there's so many good points that we're hitting here. I'll just say the other thing to build on your point about, hey, these take less capital. You have to look at what does your ownership after you've been diluted by 50% as a seed or Series A investor, you're gonna be down to half. So if you own 10%, you own 5%. If you owned 7 like YC or we do in a company, you're gonna own 3. You're gonna really have to model out is the valuation you're looking at, what does it pencil out to for an outcome? And when I did this with our investments, I saw a leak in my game, which was, hey. I'm putting a 100k into a $25 million round or a $50 million round as a follow-on investment, you know, to support the founder. Okay. What does that do for my LPs? Well, that 100k would need to hit some extraordinary outcome, 5, 10, 20, $40 billion in order for us to return the fund. So now my team understands, hey, take that 125ks, that 250ks, that 500ks, do 4 more accelerator companies with it because those could return the fund. And that fund math, people stop doing. I think all these fund managers who are getting wiped out, they never penciled out, what does this company I'm giving a $1 million need to hit in order for me to return my fund? And now they're finding out that look at it. It's not that it's Chamath Palihapitiya (01:01:37): just tweeted. Jason Calacanis (01:01:38): Look at that. Let me see it. Chamath Palihapitiya (01:01:39): You know, everybody's course correcting. David Sacks (01:01:41): I mean, it's basically the capital deployment's gone back to Jason Calacanis (01:01:45): where it David Sacks (01:01:46): was in 2019, let's call it. So, again, we had this bubble. The foam started building in 2020, but you had COVID. People didn't know what to think, so there was some restraint, I guess. And then 2021, it just went wild. Jason Calacanis (01:01:59): That was nuts, man. Those Well, I mean, Chamath Palihapitiya (01:02:01): the question is vintages are just gonna be garbanzo beans 21, 22. Well You know, that's Jason Calacanis (01:02:06): such an interesting point. Chamath Palihapitiya (01:02:07): Could return capital, you're gonna look like a euro. Jason Calacanis (01:02:10): Also, Chamath, I remember I don't know if it was Michael Moritz or or Doug Leone, but I was talking to Sequoia about the time dispersion of your fund. Like, over what period of time are you deploying a fund? And, man, people started deploying funds in 18 months because they could raise the next fund so quick. So like, screw it. I'm going to deploy this fund in 18 months, 24 months. And LPs were saying to me, like, what period are you going to deploy this? And I said, well, you know, I was taught by Fred Wilson and this person, 36 months, 48 months would be a good window to deploy capital because, you know, it just weirds it out. Chamath Palihapitiya (01:02:46): I think you're saying the dirty little secret of the venture business, which is at some point people get to a fork in the road. If they hyper-optimize for returns, I'll put Benchmark, I'll put Fred Wilson in USV, I'll put Sequoia's early-stage fund. They have to introduce time diversity. They keep the funds small and they look to hit grand slams. But there are many other people and I would say the most of the set outside of that take the road more traveled, which is then you optimize for size, which then becomes a fee game and so you optimize for velocity. Get the funds out as quick as possible, raise a new fund. They have no intention of generating returns because they have no ability to. When you have absolutely no time diversity in this business in a pool of capital, you're giving away one of your best edges. David just talked about it. As a smart practitioner, he was able to nurture these companies that all of a sudden they start to win. If you've all of a sudden flushed all your money in fund 1, then you go to fund 2, fund 3. By the time something in fund 1 hits, what are you gonna do? You're gonna cross the funds or you're gonna justify taking money from the left hand to pay the right hand, or you're just gonna let your ownership wane because you frittered all the money away. These are all the problems that most of these folks have encumbered themselves with. It's very difficult to get out of. It's gonna take now look, in fairness to them, they probably, you know, got good while the getting's good. So they'll make a ton of money in fees, but they will not be able to raise funds. Jason Calacanis (01:04:15): And those fees are not clawed back, folks, for those of you playing along at home. David Sacks (01:04:18): Just by the way, I feel better about those late bloomers in my portfolio because I know the marks are real. Because if they're getting marked up now, then it's very, very solid. Compared to, frankly, some of those marks that we got in the bubble year, like 2021, I call them tiger marks, whether it was Tiger or not. This is less real, quite frankly, and a lot of those companies are retrenching and have issues. So a mark now just means something different than a mark then. But, look, I wanna, you know, just so we're not, like, totally beating up on VC. There was you remember that in this bubble period of September 2021, everybody thought that this party would just continue forever. And this is a good example from The Wall Street Journal where I was talking about how university endowments were minting billions in the golden era of venture capital. So the bubble wasn't just in VC, it was in the public markets too, because we had ZIRP. Right? Like, interest rates were zero, liquidity was just flowing. And so it was very easy for companies to get liquid, they IPO'ed, and then the valuations were stratospheric. So the distributions to LPs were massive in 2021. And then that led to, again, more funds being able to raise bigger funds. Everyone was just kinda paying it forward and thought the party would just keep going. So this is what happens in a bubble is everybody thinks that it's just gonna keep going like that. Jason Calacanis (01:05:43): Is why it's so important as a fund manager or an entrepreneur for you to get great advice from people who've been at this for a long time and focus on the process. You cannot control all these outcomes. You cannot control all these meta events. What you can control is your relationship with your customers, building a team, making great bets, supporting late bloomers. That's the critical part of all this is the process and you can make your process better. And so with my team internally, I'm constantly talking to them about our selection of companies, how we help companies get pulled through and get downstream funding, how we literally our big effort this year is how do we introduce our companies to the top VC firms? And we've been working on that as an internal project, right, of just getting our great breakout companies to the best investors to increase our pull through. It is a process and you have to trust and focus on the process. Yeah. David Sacks (01:06:42): Well, look, I ironically, just, I mean, just to end on sort of a positive note, if these interest rate cuts are real, like, if we we just got 50, if we get another 50 this year, if inflation's really tamed and inflation's never gonna go to 0, but if they go down substantially and we have this new AI disruption, this new AI tailwind, we could be back in another golden era. It's not gonna be a bubble, but it's could be another golden era. So we'll see. Jason Calacanis (01:07:12): Start companies from your lips to God's ears, guys. Chamath Palihapitiya (01:07:16): Love you, guys. I gotta go. Love you. Alright. Chamath had Jason Calacanis (01:07:19): to go do work. Apparently, he's starting this new concept, Sacks, where Chamath is actually going to work and, at a company. We never got to talk about the debate because we were busy doing the summit and we took the week off from a new episode. People wanted to hear your take. What did you think of Kamala and Trump, the one and only debate we're gonna hear, apparently? Any any thoughts? David Sacks (01:07:43): I think that Kamala Harris performed better than expected. She did that, I think, mostly through having canned answers to topics, and she was able to kinda memorize those answers and and say them, and she was never knocked out of her preparation. Jason Calacanis (01:08:03): She was well prepared. Yeah. I David Sacks (01:08:04): think she was well prepared. However, we now know that these were canned answers because in subsequent press interviews, she gives us the exact same thing. It's like a jukebox where you just push the button Jason Calacanis (01:08:13): and get David Sacks (01:08:14): the same answer. Exactly. So she's she's memorized a certain number of talking points, and that's all she's gonna give you no matter what the question is. And if you saw that, it's become a meme now where if you saw that question when she was asked about inflation, there's a pause when she's figuring out which greatest hit she's gonna play and then, you know, she, I guess, pushes B26 in her head and then it begins, so I was born in the middle class. Jason Calacanis (01:08:40): And it's working apparently, right? It seems like it's it's helping her. Yeah? David Sacks (01:08:45): I think what you saw is that she got a bounce out of the debate, but now it's sort of like a lot of these bounces. There's been kind of, effervescence to it, and then it kinda settles down back to the recurring pattern. And so I think the election is extremely close, but I don't Jason Calacanis (01:09:01): think yeah. I mean, every day, it's like a poll going one way or the other. I mean, this is the closest of our lifetime maybe or that I can remember. Yeah. I mean, it's nuts how this thing has flipped over and over again. What did you think of Trump's performance? Were you disappointed? There were some rumors, people were a little upset that he doesn't prep as much as he should. What's your what's your advice there? You know? David Sacks (01:09:22): Well, I mean, I think that he was in a very difficult situation. You basically had a 3-on-1 situation where he was up against not just Kamala Harris, but the two debate moderators. It turns out that Linsey Davis is Kamala's sorority sister. David Muir was fact-checking him constantly, and some of those fact checks weren't even correct. For example, we now know that the Springfield city manager has acknowledged complaints about pets being eaten. Jason Calacanis (01:09:52): Oh, that's what we got. Speaker 3 (01:09:53): Oh, he's wondering if Chamath Palihapitiya (01:09:54): we were gonna get through the episode. David Sacks (01:09:56): It's as far back as March, there are videos of him talking about the complaints Jason Calacanis (01:10:01): that city council made. Yeah. David Sacks (01:10:03): Now you can say that you don't believe those stories or whatever, but those reports were real. But David Muir fact-checked in real time saying that Trump was wrong, and there was, like, this effort to kinda gaslight and make him sound crazy during the debate when there are, in fact, sources for what he was saying. Jason Calacanis (01:10:23): And it might have thrown him off a little bit, I noticed. Like, it was like he—I agree. Going into it, I think they need to negotiate in the future. You know, how they're negotiating the microphones on or off, audience on or off. I think they should negotiate. Are we fact-checking in real time, or are we not fact-checking? And who's doing that fact-checking? David Sacks (01:10:43): And they only fact-check one candidate. For example, when Kamala Harris repeated numerous hoaxes, like the very fine people hoax, the bloodbath hoax, the suckers and losers hoax. I mean, these are things that were already addressed in the last debate and, you know, even left-wing sites like Snopes have said the whole very fine people thing is Jason Calacanis (01:11:02): Just for people who don't know that, there's been selective edits and, I mean, there's been selective edits forever, but that one is particularly egregious. David Sacks (01:11:09): It's really egregious. The bloodbath one is really egregious too because Jason Calacanis (01:11:11): what I'm talking about the bloodbath. The auto industry. Yeah. Yeah. Chamath Palihapitiya (01:11:15): You just make it Jason Calacanis (01:11:15): into a January 6th extension, which it's not. Right. David Sacks (01:11:19): So she was able to say these things and never got fact-checked once, which meant she never got knocked out of the preparation. Jason Calacanis (01:11:25): And let's also be honest. Like, Trump is hyperbolic. So if you are going to say, you know, oh, we're gonna fact-check Trump. Like, there's a lot of material there, and he's just—he's a hyperbolic guy. That's kind of his shtick. Right? I mean, David Sacks (01:11:39): But here's the thing is that in the wake of that debate, look, I think a lot of people scoring the debate on, like, technical debaters' points would award her the win for that night. I don't clearly, she Jason Calacanis (01:11:50): won. Yeah. David Sacks (01:11:51): I don't deny that. However, what I think has been surprising is that in the wake of the debate, you're seeing her support sort of return more to its previous level. And so what I'm saying is the effect that that's wearing off, and I think one of the reasons why that's wearing off is because Trump still has the killer issues in this election. He's got the border, and he's got inflation and the economy. And Harris may have done well again on debaters' points, but what substantive answer did she give in that debate except to say I'm not Joe Biden, which is, I guess, true. However, what you're basically saying is you won't defend your own administration's record. You are the incumbent. You're not the change candidate, and you're saying that people should vote for you because you're not Joe Biden. Well, what is it about Joe Biden's record that what is it about Joe Biden's policies that you don't agree with? I mean, after all, you cast the tie-breaking vote for the Inflation Reduction Act. You cast it for the $2 trillion American Rescue Plan that set off the inflation. So the debate moderators never asked Harris, well, what is it about you that is different than Joe Biden on a policy level other than the fact that Jason Calacanis (01:13:02): you're different? Again, I thought that was, like, a great moment for her. Objectively, I think, you know, and I've said this forever here on this show, putting our feelings aside about the candidates. I think whoever comes across as the most normal or the most moderate is gonna win. And I think she's done a great job of, like, convincing those moderates that she's not crazy and he is. What are your thoughts on that? Because people looked at this very podcast, and they've said to me, my God. That's the Trump I wanna vote for, that Trump 2.0, the all-in Trump. And then people are like, ah, he's going back to the insult comic Trump, but I don't want the chaos. What are your thoughts on moderates specifically in the swing states and this sort of strategy? David Sacks (01:13:45): Let's talk about let's talk about the Teamsters. So Biden, when he was still in the race, was plus 8 among the Teamsters rank and file. And now that Harris is the candidate, Trump is up something like plus 26 with the Teamsters. Jason Calacanis (01:14:00): Yeah. Why is that? Because isn't she pro-union as well? He was Union Joe, so, I mean, it was, like, in the name. I understand why they left him. David Sacks (01:14:07): There's something about her policies, and I think her the the look. I think within the Democratic Party Jason Calacanis (01:14:15): is her personality. David Sacks (01:14:17): I think I think it's partly personality, but I also think it's it's policies and cultural issues. So within the Democratic Party, there've always been two tracks. There's the beer track and there's the wine track. And so, you know, Bill Clinton was classic beer track guy. Right? You're a summit. You're a Jason Calacanis (01:14:32): summit with Obama. David Sacks (01:14:33): Right. And I think Joe Biden was beer track. Then there's kind of the wine track, which is the part of the party that cares about these boutique cultural issues, starting with DEI and equity, and trans and things like that. Jason Calacanis (01:14:47): liberals is what they used to be called, but I like yours. Wine liberals or, yeah, the woke wine. David Sacks (01:14:53): Basically, the entire California Democratic Party is very wine track. I mean, Gavin is very wine track. Tom Steyer is very wine track. You can understand why a blue-collar worker, it doesn't appeal to that. They want more of that lunch pail traditional Democrat. But that Democratic Party doesn't really exist anymore. I mean, the Democratic Party has evolved to be the party of the professional class, whereas the Republicans are more the party of the working class. And you're now starting to see it. I think Biden was the Democrats' last vestige of this working-class party. He really worked at being appealing to those voters, you know, the whole Scranton Joe image. Jason Calacanis (01:15:30): Yeah. And you need Joe. David Sacks (01:15:31): Yeah. Exactly. Whereas, Kamala, when you get her talking in an unguarded moment, and it's not a canned answer, she's gonna talk about diversity, equity, and inclusion, and that's not what your typical teamster wants to hear. Jason Calacanis (01:15:43): Let me ask you a challenging question because the audience likes when they ask you a challenge a bit. If Trump loses, what do you think will be the cause of the loss? If he loses, like, strategically, when we look back on the last six months, what do you think you would change? What would cause it? David Sacks (01:16:02): Well, look, I mean, the great asset that Kamala Harris has is not her likability. It's not her track record. It's not her policies. It's the fact that she's got the media behind her. And if you look at, like, for example, ABC News, 100% of the coverage by ABC News is positive, whereas something like 93% of their coverage on Trump is negative. And you saw this before Harris replaced Biden as the nominee, she had very low favorability ratings, and then the media basically reinvented her as this transformative candidate. So, look, when you've got the media willing to operate as de facto members of your campaign, that's tremendously powerful. If we had a fair media, this election wouldn't be close. So that is the advantage the Democrats had. Now look, should Trump have done the debate with ABC News? No. I think he should have chosen more fair moderators. I mean, to their credit, I think CNN played the Biden-Trump debate pretty fair and down the middle. But ABC, I mean, it was predictable that, like I said, I mean, one of the hosts was her sorority sister. So, you know, I think that if Trump loses, you could say that his willingness to walk into the lion's den, take on all comers, do every interview. You could say, maybe that wasn't as strategic as what she did. But at the end of the day, I think that voters will appreciate that both Trump and JD are willing to do basically every podcast, every interview. They're not afraid to answer questions. And when they do answer questions, you can see them thinking, and they don't give you the same canned answer they've given 10 times before, including at the debate. So, yeah, I mean, that's my take. What's yours, JCal? Jason Calacanis (01:17:47): On which aspect? Be more specific. Give me a specific what David Sacks (01:17:50): What do you think? What do you if if if she ends up winning, what do you think the reason will be? Yeah. Jason Calacanis (01:17:57): That's a good that's a good question. If she ends up winning, I think it will be that people believe that they I think it will be that moderates in those swing states and women believe that it's too much chaos and that Trump will be too much. They want a calmer, same thing, reason Biden won. Right? Like, that there's this, like, concept that the adults are in the room and it will be calm and it won't be chaotic. And I think people just still see Trump as a bit chaotic. And I I think that's the big fear. And I think they've played the abortion card and the right to choose really well. Even though Trump said it here, I'm not gonna sign the abortion ban. I'm pro-IVF. I think they have that really great win of saying, hey. You bragged about overturning Roe v. Wade. Probably wasn't smart to brag about that, and they have that clip that they can keep reinforcing. So he does lose. And I don't know that he's gonna lose. I think there's a lot of people who are gonna go in there and vote for him but not say it to pollsters and not say it to their family and friends because they're embarrassed because of the pressure against Orange Hitler or, you know, this whole rhetoric that he's going to, you know, overturn democracy. So I think there's a pretty good chance that he's gonna win, actually. I don't think that this. Yeah. David Sacks (01:19:19): I mean, look. I think Jason Calacanis (01:19:20): he's race. Right? They say the statistics in a close race favor him. David Sacks (01:19:24): Yeah. Look. I mean, maybe we're asking the wrong question here, which is why would he lose? I mean, I think maybe the real question is why is he favored to win? Because I think the polls, including Nate Silver, still show him favored to win. And I think that when you look at what the big issues are in this campaign and what has people agitated and upset, why they think the country's on the wrong track, something like 65%. It has to do with the economy. It has to do with inflation. It has to do with the border. I think that on the cultural issues, the trans stuff drives parents crazy. They don't want the government telling them what to do with their kids. So it's hard to think of a killer issue other than maybe abortion that Harris has on her side. It feels like all the issues cut Trump's way, but the, again, the thing that Trump doesn't have, and there's no way for him to fix this is the media is just so in the tank for Harris. Now you raise a good point. Look. Could Trump be more disciplined? Yeah. Absolutely. However, you know, I think that what amplifies that is the fact that the media is quick to jump on every little thing he says and distorts it. Jason Calacanis (01:20:26): And he sets himself up for it. You know? Like, part of what makes him activate the base is that erratic behavior, his shtick, you know, the comedy. And then I do believe that it gets weaponized by the press because it's, like, so easy for them. David Sacks (01:20:40): I agree with you that Trump could be more disciplined. However, I don't think it's as bad as what you're saying because if it were, there'd be no need to make up these obvious hoaxes. There'd be no need to, you know, lie about the very fine people or what he said about bloodbath. So if he was really saying that many outrageous things, why would you need to keep inventing things that he didn't say? And if you're actually Jason Calacanis (01:21:03): just stacking them. Yeah. The answer to that question is just throw everything you got at him. David Sacks (01:21:06): Yeah. They're throwing everything at him. But look at Kamala's interviews. I mean, she hasn't given very many. No. But, I mean, her answers are just I mean, just watch them. I'm not gonna characterize them, but just just watch her actual interviews. Jason Calacanis (01:21:18): I mean, Megyn Kelly thinks she's stupid and not bright. I mean, she's not the most dynamic speaker, that's for sure. And she doesn't seem to be able to, have a dynamic debate with intelligent people who are experts in their field, let's say. You know, she can't hold her own in the way you can see JD can. Right? And and Trump can. So here we go. And just on the, on the second assassination attempt, I don't know if you even wanna go there, but I mean, gosh, I'm so glad that he David Sacks (01:21:51): Yeah. It's being scary. Jason Calacanis (01:21:52): Shot it again. It's this is scary stuff, folks. This rhetoric's gotta come down. I keep saying it. Nobody wants to listen to me, but, man, be David Sacks (01:22:01): Well, let's look at the rhetoric that Ryan Ruth was literally quoting on his Twitter, was saying that Trump is basically an existential threat to democracy. He was quoting what Joe Biden and Kamala Harris and the mainstream media have been saying chapter and verse. So I think that, you know, if you want to ascribe motivation there, where did Ruth get these ideas? They've been endlessly amplified by the mainstream media, and it's not like a one-off comment. It's been the central narrative for the last several years is that somehow Trump represents this existential threat to democracy, and one way or another, that threat must be eliminated. And I think Ryan Ruth simply took literally what the mainstream media has been saying. Jason Calacanis (01:22:44): percent of your followers is what I tell everybody, high-profile people you and I both know, is 1% of people in your following, and we all have large followings here, and there's certainly people who have extremely large followings. One percent are mentally ill. Like, when I say mentally ill, I mean severely mentally ill. And if it's but 1% of your following, if it's 0.1%, this could be thousands of people. And this is what happened to John Lennon and other famous people who've been killed tragically, is those mentally ill people interpret things in a very different way. And when you say, you know, a phrase that has triggers in it, threat to democracy, fight like hell, whatever it is, they interpret it differently. And so just please focus David Sacks (01:23:28): on calling the guy Hitler for years, and again, you create millions or billions of impressions around that, and it's not like a one-off statement, but it's something that's drummed into the public over and over again. It seems to me you're asking Jason Calacanis (01:23:42): Yeah. David Sacks (01:23:42): for trouble. Jason Calacanis (01:23:43): Stay safe. Please tone down the rhetoric, everybody, and we will see you next time on the All-In Podcast. Bye bye. Speaker 3 (01:23:51): We'll let your winners ride. Rain Man David Sacks. And it said, we open-sourced it to the fans, and they've just gone crazy with it. Love you, Wes. I do queen of quinoa. Besties are all. That is my dog taking it out of your driveway. Oh, man. My appetizer. We should all just get a room and just have one big huge orgy because they're all just useless. It's like this, like, sexual tension that they just need to release somehow. Wet your feet. Wet your feet. Wet your feet. Jason Calacanis (01:24:32): Wet your feet. Wet your feet. Wet your feet. Wet your feet. Wet your feet.