SPEAKER_00: All right, everybody. It's Friday. It's Twist. April 10th. Alex is here. We've got a great show. Lots of important things going on in the BitTensor world. There was a rug pull. We'll get into that. Obviously, tons of AI stuff going on. But just as we kick off the show, Alex, I always like to applaud, applaud. I put my plot pit on. I press my button. I get a nice little haptic.

SPEAKER_02: And I'm recording. Now I have every detail. So I can say, hey, after the show, make sure you don't forget to go over the newsletter stuff for the This Week in AI newsletter. Boom. Now it's an action

SPEAKER_05: item. I won't forget it. And I do that all day long. And plot is an amazing service. Thank you

SPEAKER_07: to them for supporting the show. Yeah. And also, if you want to get a plot for yourself, you can at a tasty discount. If you go to plot.ai slash twist, P-L-A-U-D.ai slash twist,

SPEAKER_09: use the code twist, T-W-I-S-T, save 10%. Be cool like Jason and I. Don't forget things. Get more work done. Less pain. Plod. Use that code twist for 10% off. And they know we sent you.

SPEAKER_06: All right. Let's get to work here. There was some type of a defection from the subnets of BitTensor.

SPEAKER_00: People have heard me talking about this very promising crypto project called BitTensor. The token in it is called Tau. There are subnets. What are the subnets doing? You may have heard us talk about it here or on All In or you see it on your XFeed. You can create subnets. There's 128 of them

SPEAKER_13: available. And those subnets will do different projects. One of them is a co-working or a

SPEAKER_00: co-pilot for doing coding like codex or clock code. And why are these important? Why should

SPEAKER_15: they be created using cryptocurrency? Well, it's a distributed network. And just like Bitcoin,

SPEAKER_00: you can have people compete to provide that service at the lowest possible price, which is super deflationary. And my thesis, and I've got an investment in this space, is I've got a couple

SPEAKER_04: different investments in the subnets. And I've bought Tau directly. And I might even be a little underwater now based on where I bought it. It doesn't matter to me, but I got a bunch of pings

SPEAKER_18: on my phone last night. Oh my God, Tau's going. There was some kind of rug pull. So let's get into

SPEAKER_09: it. We had Sam Dare on the show, Twist. It was March 27th, 2026. So just about two weeks ago, Jason. And he was talking about Templar, a project that was doing decentralized training of an AI model, of an AI model. This was Covenant AI, three different subnets, subnets 3, 39, and 81. They form kind of di-triumvirate, if you will, of things that work together, pre-training, compute, and post-training. And what they built was the Covenant 72 billion parameter model. In March, this got a lot of attention. Look, decentralized training of an AI model, not just the work of the major AI labs. Instead, something that maybe anyone can participate in. I drove the price of Tau up. And then, Jason, yesterday, we got a major statement from Sam and the group at Covenant AI, which is right here. And it makes a number of very important claims. It says that BitTensor is not as decentralized as it claims. It also says that one of the co-founders of the project has been essentially blocking their

SPEAKER_07: ability to do their work. Really, really big claims. There's been a response to it. But what really matters is, scrolling, scrolling, Jacob Steves, also known as Const, one of the co-founders of BitTensor, has taken a series of actions against Covenant AI's operations. These include suspension of emissions to our subnets, removal of moderation capabilities, unilateral deprecation of our subnet infra, and economic pressure via token sales. He responded, Jason, but I want to get your take

SPEAKER_09: first on basically what Covenant is claiming. There'll have to be a little bit of an investigation

SPEAKER_00: here as to what's happening. But the control of the subnets and making sure there aren't rug pulls, like we see all the time with, or we saw all the time with ICOs or meme coins. This is a major vector of attack and a major concern people have in the crypto community. So what Tao is trying to do is remove that possibility. So what system do you create to remove that possibility? Well, you have to have some control over the subnets, and there has to be governance. So that governance stuff is being worked out from what I understand from the insiders. And sometimes you'll have a bad

SPEAKER_15: actor. I'm not saying this person is a bad actor, but some people are claiming, hey, this person just ran off with a bunch of the subnets tokens and some Tao, and it just is something that happens in crypto. Sometimes as people build a project, you buy some tokens, it's not regulated, and all of a sudden you get rug pulled. That still exists. Sometimes you'll have lawsuits come because of these things. An attorney general in Florida or someone will find who was impacted by a rug pull. I remember all the celebrities who were promoting different coins. They all got tagged. So this is the kind of stuff that can happen. And this will be in my estimation, and this is my hope, and what I believe will happen is that this will help solidify how to handle and avoid these things in the future.

SPEAKER_09: This is a trip and a fall over something they're going to remove from the pathway. So in the future, no stumbles of this sort will crop up. Yeah, I think that they can, you know,

SPEAKER_15: eliminate this from happening in the future by making it such that the subnets have to stake a

SPEAKER_00: certain amount of Tao, and that the people who are participating have some control over the subnet. Subnet governance is going to be a very delicate thing because you want entrepreneurs to be able to start a subnet, put up some collateral for it, almost like buying a franchise. And then you want

SPEAKER_15: those folks to believe that they have some level of ownership, but not so much ownership that they can take a bunch of people's tokens and then just say, you know what, I don't agree with how this is being run. I'm just going to take all these tokens and leave. So, you know, as I've said to everybody, the opportunity in these kinds of projects is that these questions have not been answered. This, they are imperfect. That's why it's at a, whatever it is, you know, $2 billion

SPEAKER_17: market cap, not a 500 billion or trillion dollar market cap.

SPEAKER_07: 2.93 after the declines, a good segue, Jason, Tao was trading at roughly 335 before this news broke. As we talked to you, it's worth 271. So a pretty sharp decline, but certainly not the end of Tao. This is not, you know, the project flying apart, but a pretty large drop in value. The thing that I'm

SPEAKER_09: trying to sort out in BitTensor land, Jason, because I've talked to probably 10 different subnets in the last couple of weeks, just prepping them for the show and getting to know what they're working on and how the economics work is there does seem to be at times moments when they say, oh, the community wouldn't tolerate that type of bad action. And so often I feel like I've run into, there are some humans in this system that is not yet fully decentralized. And I wonder if this argument is essentially coming to the point to which that's no longer acceptable and it has to become even more decentralized to maintain trust. Because even though a lot of people in the BitTensor community are, I think,

SPEAKER_07: pretty negative about Sam right now. And we'll bring on a subnet guy in just a second. I don't,

SPEAKER_09: I'm struggling to get that mad at him for what he did, because it seems like he made something cool and then wants to go host it somewhere else. And you and I don't throw a fit when someone leaves

SPEAKER_28: substack. Yeah, it would be though, if you took all the subscribers money and then didn't provide the

SPEAKER_15: subscription product. So that's what has to be adjudicated here is how much Tao he collected from people. If they invest in his company, it would be like investing in a startup. And then the startup just says, you know, I don't like the way capitalism works. I'm out. And then they take the money. So these are the allegations that are all going to be worked out over time. You and I can speculate about it. But yes, you should be able to leave your subnet and go do something independent if you want, of course. But you don't get to leave with everybody's tokens. And then there might also be like some dumping going on here. So again, all allegations all to be worked out in the

SPEAKER_31: court of crypto. But let's get some of the participants. Let's bring on Gareth Howells.

SPEAKER_09: He's from video subnet 85. And we're going to talk to Gareth about what he's building and why it's cool and how he's using BitTensor in a second. But I wanted to get his take on the situation. Gareth, hey, you've been tuning in quickly. Who's closer to the truth there, Jason or I? And did the people

SPEAKER_36: behind Covenant AI make off with the tokens? I think Jason has got a very good understanding of the situation. Yeah, absolutely. I think this is an individual acting rather than the company or the community. I think that the subnets that Sam was heading up are probably going to carry on doing the same work and they're going to build upon that. So yeah, I think Jason's synopsis of what happened was pretty close.

SPEAKER_40: Give me your synopsis because it's always good when these new technologies come out to

SPEAKER_42: have multiple people try to describe and use analogies or their own handicapping of the

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SPEAKER_36: Yeah, Sam was a subnet owner. He had access to the wallets and he sold the tokens. The reasons that he gave for selling the tokens, I'm not 100% convinced by. I think Constance made a response saying actually some of the accusations he wasn't able to do and they weren't true. And it was impossible for him to take some of the actions that Sam has accused him of. So I think possibly he may be pointing the blame somewhere just to excuse his actions. But, you know, we don't know everything about it. This is just from obviously what I know anecdotally like you guys. I'm not

SPEAKER_00: right in the nitty-gritty of the exact situation. And why did Tau go down 20% or whatever it went down, you know, when this happened? Was it just bad vibes and people were like, oh my God, this is an attack factor. This is a weakness of the BitTensor system. Or was it because the market was flooded with

SPEAKER_38: Tau's being sold and there weren't as high of a bid to absorb them? Yeah, I think that was a big

SPEAKER_36: element of fear there. I think obviously Covenant has been absolutely killing it recently with the detail investors and it was right on the top of the emissions. And it has been for a long time. He was getting amazing press outside from people who didn't have a full understanding of BitTensor, but they obviously were understanding what he's doing and very impressed by that. And I think that when it was found out that he was selling all his Tau and taking it, I think there was a big fear amongst investors, not necessarily the community, but investors were very worried that this was going to be catastrophic for the Tau price. And a lot of

SPEAKER_50: people got out. It wasn't just him selling his Tau, but that was an element of it.

SPEAKER_07: Gareth, is it fair to say that Covenant AI and its three subnets were kind of a marquee or like Apex project for BitTensor today?

SPEAKER_36: I think they were, but I think there's also, there are only three subnets out of 128 and we've got some incredible subnets doing some amazing things and they're going to come to the forefront very soon. So I really think this is more of a blip than, you know, anything saying that BitTensor is in real trouble. I think we're going to bounce back very quickly. The community is amazing. And some of these, the other subnets are going to come to the forefront very quickly. So I really think this is, this is a very short term issue, but I also think it's going to actually make the community much stronger. We're going to put things

SPEAKER_56: in place to stop this happening again. And I think we're going to learn a lot from that.

SPEAKER_59: All right. I really appreciate that. Now let's talk about video subnet 85. First of all, give us the TLDR about what it does. And then we're going to show an upscale of Mr. Lon Harris.

SPEAKER_36: We are. We are. So yes, video subnet 85 is a video processing subnet. So essentially we're starting out doing a video compression and upscaling, but now we're moving on to optimizing your video in any way that's possible. So we, we've got an agent that we can connect to your storage. We read everything that's on your Amazon S3 bucket. For instance, we take a look at that and we, we tell you where we can optimize. Optimization can be many things we can optimize for streaming on a VOD platform. We can optimize for archiving, you know, best quality picture, saving you space. We can optimize for security, medical education. You know, we're covering all those areas of video. So, um, yeah, essentially what we're doing is, um, using an AI, AI agents to make your video, um, the best it can be for whatever your needs are.

SPEAKER_40: Just to recap, I always like to explain back to the founder. So I understand their vision.

SPEAKER_64: Yeah. Uh, vidio, V I D A I O is how the name of the company is spelled, or I should say the name of

SPEAKER_40: the subnet is the tau subnet, the bit tensor subnet. It's numbered 85. Just so people understand there's 128 subnets. A person like Gareth can start a subnet, uh, stake with some tau, uh, and they may or may

SPEAKER_00: not have a company behind it. So are you also running a startup that is doing this or a consulting

SPEAKER_68: firm? We are incubated by, um, tau stats mug who you had on the show before with a hippias. So we're,

SPEAKER_39: we're in exactly the same situation as hippias. Got it. And this could become a company it's inside

SPEAKER_15: of a different company right now. Uh, so as investors, uh, we could invest in a parent company or you could buy tau or you could buy the subnet token three different ways to invest in these opportunities. I'm looking at all of them. Uh, I have, I own tau directly myself, uh, through Coinbase. It's not on Robin hood yet. And then, uh, still core capital, uh, which I'm a partner in with Mark Jeffrey, they are going and buying subnets to buy subnets. You got to go to the subnet owner and do a deal to buy the tokens. They're not trading freely on marketplaces yet.

SPEAKER_00: Um, but when you buy tau, it's in some ways like buying a mutual fund or a, an index, an ETF, I guess would be the best way to say it, an ETF of a bunch of different startups. Okay. This

SPEAKER_40: particular subnet is challenging people, uh, on the internet or globally to give you compute. And then you take that compute and you will take video files and render them into, you know, different, um, uh, uh, different versions of it. Now this seems like a very narrow, uh, use case. Like I can, on my desktop, I can use VLC to save a file as a different file type, but you're doing something a little more sophisticated and the customers of this product or what, so let's just talk really tightly about who are the customers for upscaling a video or just essentially making

SPEAKER_36: different versions of a video and how big is that market? So, I mean, the market is enormous, uh, 85% of internet traffic is video. So, you know, it's not going anywhere, more videos getting created every day and it's going into storage buckets on the cloud that are just getting bigger and bigger. Um, people's, you know, bills are getting bigger. No, one's really doing anything about that. So to answer the question, upscaling would be anyone with a library, a library of old content. You could be, you know, the national archives in the UK, you could be a big TV broadcaster who made

SPEAKER_73: 20 years of programming in SD. Um, you could be a consumer who's got videos.

Chamath Palihapitiya: Got it. So like the BBC has a giant archive. BBC news has a giant archive.

SPEAKER_04: Exactly. Getty images has an archive. CBS owns an archive. Those archives might be in very low

SPEAKER_36: quality video. Yeah, exactly that. So, and, and they won't translate to like a 4k screen. Like we, uh, expectations these days are of high picture qualities. So we can go in there with our agent. We can scan your archive and we can tell you what we can do to that. We can make these, all these videos 4k. We can turn your black and white videos into color. We can change the frame rate. If, if the video's jerky, we can clean up noise, or if you want to keep it in black and white, we can do that. You want it in Sepio. We can do that also. We can do subtitling. We can do transcription. We can do tagging of metadata. So then you have a searchable content library. So we can do all of those things

SPEAKER_09: within, you know, within our ecosystem. Got it. So the miners here are not just providing compute Gareth. Aren't they providing the actual models themselves that you're using for those specific tasks?

SPEAKER_36: Yeah, exactly that. So we're now moving on to the new iteration, um, which is a winner takes all or winner takes most model for the miners. So essentially what they're doing now is optimizing models. So rather than we were using their compute before, but that became very difficult to scale. So now we're, we can scale with shoots, which is another subnet has a trusted executional environment, which means that it's a safe environment that our, um, clients will be happy with. Cause it's a hundred percent safe. It's, it's private for, for us and the client. Um, so now we can optimize models. So we can say we want a new upscaling model or we a colorization model or subtitling, uh, lip sync. We're looking into lip sync models as well. So there's, there's so much more versatility now in the subnet, if we move to this kind of, uh, when it takes all model. And there are desktop pieces of software

SPEAKER_00: like Topaz, uh, that I think people will use for this type of, uh, product or service. So if you had an old, um, video of a Bob Dylan concert, or I have all these old dire straights bootleg videos,

SPEAKER_15: they're all over YouTube and they are grainy. Now AI can take them and upscale them. So about three or four years ago, I started to see this on YouTube where people would say upscaled, you know,

SPEAKER_00: dire straights thing. And it's pretty amazing to see literally a VHS, shaky VHS turn into something

SPEAKER_40: that looks like, okay, maybe HD or close to HD. And it's only going to get better from here. This is the worst it will ever be. Yeah. So here's the video. Oh, okay. Here. So let's see an example.

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SPEAKER_59: first website or domain purchase. So here's an example of it from the subnet. Here's a lawn. If you're on the audio version, we have a grainy lawn on the lab.

SPEAKER_93: Rest in peace, Lon Harris. He was an amazing collaborator here. And so we're celebrating him today. He's in surgery as we speak. Well, who knows if he'll get out. He's wearing his

SPEAKER_11: plod pin. Just so you know, he's wearing his plod pin. Two plod pins in one, one shot. There you go.

SPEAKER_98: To me, it doesn't feel like Gaff is anywhere near ready to work by himself. Like even if he was in a Mac studio, I feel like I would still need to be there giving him feedback pointers, asking him to do things. I don't think he's ready to replace me. He's ready to do like 80% of what I do.

SPEAKER_17: The one on the left and the one on the right, explain to us the difference.

SPEAKER_36: So the one on the left was the original video that we upscaled, which was taken obviously from one of your podcasts. We compressed that down a bit to make the picture of quality worse, but then I put it through the subnet and we upscaled this up to 4k. So essentially what we're doing is it's a gen AI tool, which is predicting what should be in the picture and it's making all of the, the, you know, the, the blurry lines, um, clearer. So got it. And so this is a way if

SPEAKER_28: people are recording their podcasts, just as a silly example over zoom, like many people do today

SPEAKER_00: and that kind of downgrades your video a bit, you could take all in, or this week in startups here

SPEAKER_22: and twist and just boom, make it a beautiful look like it was using 4k studio red cameras or something.

SPEAKER_36: Yeah. Yeah, absolutely. We can do that. And then we can also compress that video. So you get a super high picture quality, a much smaller file size. So therefore, I mean, that's going to help you with streaming. That's going to help with your storage and your CDN costs. So it's going to create

SPEAKER_106: efficiencies all the way down, you know, how does that play into low, low connectivity markets? Like,

SPEAKER_07: you know, in parts of the world, like parts of Latin America, parts of Africa, connectivity is a lot worse. Does Starlink make it so that everyone has unlimited bandwidth. Now we don't need to worry about it. Or are there still places where people are pretty bit conscious?

SPEAKER_36: Unfortunately not. Yeah. So, uh, Africa being a perfect example, I've got a lot of experience working in Africa, uh, and in emerging markets. So connectivity, there's a real problem. Also, everyone uses mobile phones. There's no laptops, no 4k TV. So everything's needs to be compressed down to the small screen. Connectivity is an issue. Data is an issue. Phone batteries an issue. So these, all of this, everything we're doing to these files is solving those problems. Essentially we can get say conservatively 60% smaller file at the same perceptual visual quality. So the user has no, like there's no degradation for the user. Uh, they get a perfect quality file, but it's 60% smaller. So all of the costs along that chain, um, yeah, they reduce.

SPEAKER_42: Yeah. And if you look at this space, um, it's predicted to grow from 175 million in 2025 to 1.1

SPEAKER_00: billion in 2032. So this is going to be calm. This is going to be like a compounding vertical where people are really going to want to be upscaling videos on a regular basis. Yeah. And there are many competitors here already from desktop software to Amazon has an offering.

SPEAKER_40: Yeah. You, in terms of your pricing, walk us through the economics now because you're using another sub net for compute. And so you're using your miners, miners or individuals who want to earn tau for doing a task. So just so people think about it, that's the supply side. So that's the Uber drivers. That's the Airbnb hosts. They can come into this network, but unlike Uber, where they need a driver's license, they need to register. They can just sign up here and compete for these jobs.

SPEAKER_79: And then there's a validator, uh, that confirms that they did the job and then picks the winner.

SPEAKER_116: Am I broadly correct in how subnets work and how this one works?

SPEAKER_36: The thing is with video is compute heavy for sure, but there's, um, it's very hard to put a price per minute on what we're doing, which is essentially the old way of, um, pricing. Say that's what, uh, AWS would do. Um, because we're, we now have this optimization model where we could be using three, four or five different models on one piece of video. We, um, it goes kind of on a case by case basis, but what we have on our side, not only do we have the innovation of BitTensor, which is of course, the incentive mechanism and the miners creating better and better models. So we've already done benchmarking with all our competitors and we're already better. So we know that we know that we're good there, but also you have the emissions from the subnet, which can also subsidize our earnings. So we can pay our miners. So we're essentially paying 256 machine learning engineers to outdo each other on a daily basis. And that's, you know, that's an unbelievable,

SPEAKER_00: powerful tool to have behind you. So what are the models that they're using? These are open source models. They're tweaking their models. They're the model originators. They're making SMLs out of

SPEAKER_40: large language models. Who are these, uh, what are these models they're using?

SPEAKER_36: It's some and some. So when we launched the subnet, we always start with a base model. Um, for upscaling, we use an open source model for, uh, compression. We created our own because there was none existing. Um, the miners have taken those and they've, they've built upon them and they've tweaked them and they've made them better, or they've created their own model. Sometimes we don't even know what models they're using. We just know that the output is better than, you know, we can do ourselves. So with this, the, with the new winner takes all we, we will ask them to open source their models to us. So then we will be able to use that in a private environment for our clients.

SPEAKER_42: Have you ever met these miners and the people who are participating?

SPEAKER_36: Face to face? No, but we've had, uh, some, uh, some meetings. Uh, there's a couple of pro mining teams that are working on the subnet, which come from the video world, actually not machine learning engineers, which is very interesting. Um, so we have, yeah, we're, we do talk to them and we, you know,

SPEAKER_00: and describe for us who these type of people are. These people who work at IBM and they make a great salary and they're doing a side hustle or, you know, they, they work at a Hollywood studio and on the weekends they do this, or they're just bored at work or they're living in Thailand. And they don't have to make a ton of money and they just are nomadic entrepreneurial CTOs. And in their spare time, they, you know, uh, contribute to these subnets because it's a fun way to make

SPEAKER_38: a, you know, an extra couple of thousand dollars a week. I mean, we've had a team from Vietnam doing exactly that. There was, there was, I think,

SPEAKER_36: three or four guys working solely on this. I think, I think they were university students or,

SPEAKER_04: or graduates from Vietnam or people who were like nomads. No, no, they were Vietnamese. Yeah.

SPEAKER_00: They were Vietnamese. Yeah. That's a very interesting thing to pause on there. Uh, Alex is there's incredible tech talent around the world. They might have a hard time getting a job at Google or Coinbase

SPEAKER_15: or whatever it happens to be, but they can permissionlessly join a Tau subnet and immediately start making money and put their tech skills to work and they can do it anonymously and they don't have to worry about visas, nor do they have to worry about payments because it's on, you know, a distributed, uh, you know, crypto project where it's permissionless, permissionless, fancy way of saying, um, I can just participate without somebody, you know, approving me. That's a really,

SPEAKER_18: you know, unique thing in all the world. This has been my biggest learning,

SPEAKER_09: talking to the different subnets in the last few weeks is that there are so many people out there who can contribute to machine learning technology that don't only work at Google. Cause I've asked this question, where are you finding these people? Where are these ML engineers that have all this spare time on their hands? Cause we beat up startups, Jason, they're desperate for local talent. Everyone's fighting over the same eight people. Yeah. But you go to Vietnam, you have a bunch of

SPEAKER_133: smart people who can do great work and Gareth doesn't care. Yeah. They come to us. That's the,

SPEAKER_36: the beauty of it is that like we built it and they come to us. So, you know, they obviously have an understanding of the ecosystem and the network, but you, you create a new subnet people register, they start mining. You, you've no idea who they are and you don't really need to, you just, obviously you need to see their proof of work and you need to validate it. And that's the only thing that matters. And that's, and that's why, you know, you can get the best talent and maybe they are working for Google. Maybe they're doing this on the side, but, uh, sometimes we don't know.

SPEAKER_135: All right. Uh, Gareth, anything else we missed? If not, we'll drop you off and thank you for your

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SPEAKER_10: subnets. I believe in this project. I have very, you know, since the administration's changed and the

SPEAKER_00: and the folks who were running crypto policy have changed. True. I am now officially open for business

SPEAKER_142: in crypto. I'm doing a stable coin project. I'm getting involved in Tao. I'm specifically looking,

SPEAKER_00: though, only for projects where there's a customer who is either making money, saving money, entertained or otherwise delighted by a product or service. So I'm not looking for meme coins. I am not looking for pump and dumps. I'm looking for, you know, actual products that create value and use the

SPEAKER_15: technology in a way that it was intended that gives it an advantage. And really, when you look at the BitTensor universe, incentives matter, tapping into a global workforce, tapping into global compute, having it be distributed. And, you know, again, there's like fancy words used in crypto, like permissionless and, you know, or, you know, peer to peer or distributed. All this stuff means is anybody can participate. The compute or storage or transit can come from anybody. And that means it moves faster and it more violently removes cost. So if you just open your mind up for a second, if everybody in the world could work at your local Starbucks or anybody in the world could magically sell coffee beans to your local coffee shop. And they basically had a competition. You would have a barista for $1 a day, $2 a day, living like a king or queen in their native location. And if the beans could magically be transported without all the distribution between where the coffee beans are and the roaster and eventually the cafe, just allow your mind to think about how powerful that is. Your cup of coffee and that experience would be delivered faster and better and cheaper. That's all. And you wouldn't have the friction of, I have to hire this person. I've got a union, I've got to pay taxes, whatever. It just, boom, just happens magically in this global cloud, this machine known as the interwebs.

SPEAKER_18: Yeah. Do you think that we're going to see a little bit less winner takes most or winner takes

SPEAKER_09: all? Because I've seen several different subnets moving towards this model for their miners and I fully understand why it's good for the subnets. But when I think about expanding economic opportunity, Jason, kind of what you're saying to me, if it is going to be winner takes

SPEAKER_59: most or winner takes all, there's less lower hanging fruit for people that are trying to get to that top rung of a particular minor task for a subnet. I'm just curious if that's a concern for you as well

SPEAKER_40: or just good economic? Yeah, no, I mean, you're a big fan of capitalism. What happens if the buy side

SPEAKER_142: doesn't make a good enough offer to labor, the supply side? Oh, they don't hire enough people.

SPEAKER_40: They don't leave their house. So if you're going to pay $10 an hour to be a barista and people can work from home for 15 bucks an hour, they're not coming to your Starbucks to work. Apple stores were faced with this and so were Starbucks and coffee bean and everybody else. When Uber and DoorDash came out, it turned out working for one or two hours, picking your own schedule and making,

SPEAKER_00: you know, $21 an hour was better than getting up at the crack of dawn, showing up at 5.30 a.m. at a Starbucks and having to work an eight hour shift and not knowing what shifts you were working.

SPEAKER_40: It just was a better offering. So this actually empowers, I believe, labor. If you consider labor, you know, the supply side on these things and the customers are the people who want their videos to be upscaled. So the people who lose are the people who are charging a higher price or and or giving a lower level of service. The winner is best price, best service. And sometimes it's some combination of that. If the validator, which is the person who basically arbitrates,

SPEAKER_15: did you actually perform the task again? And crypto uses a lot of fancy terms or a lot of wonky terms. A validator is just the person who checks the work. OK, you made a flat white. Is this a good flat white or is it garbage? Is it an acceptable flat white? You know, or fuck off. You know, so the validators will determine that. And then the person who's buying the service will say, well, this wasn't good enough. I'm going to go use another service so they could go use the desktop software or Amazon's

SPEAKER_00: offering. Sure. Amazon's offering is might be faster. It might be better, but it might also be twice the price. And then the BBC might say, you know what? These things haven't been upscaled

SPEAKER_15: for 50 years. We're in no rush here. If it takes, you know, a week or a month or a day, it doesn't matter versus an hour, a minute or two hours. So here we are, folks. This is capitalism at its finest. And if you ever dreamed of, you know, one human race working on projects beyond borders, beyond governments, beyond regulation, that's what makes this so compelling to me. It kind of cuts across humanity and just makes a global competition for capitalism. And if the people who lose are people in the West who are coddled, overpaid, lazy, whatever, and the people who win are the ones who are the biggest hustlers who, you know, will do it for the right price. But if you don't offer a decent price, people don't participate.

SPEAKER_155: So you have that backstop, right? So before anybody gets, you know, their hands wringing too hard here

SPEAKER_15: and they rip the skin off their knuckles, the guys in Vietnam doing this four person team, if they get a job, you know, for a Korean company or a Japanese company and they pay them more, they stop participating in the subnet. Again, back to capitalism, back to free markets.

SPEAKER_146: This is free markets, like unconstrained. What do you and I like, Jason? Free markets and unconstrained.

SPEAKER_09: And those are our favorite things. What I like though, just as a lot, I know we've got to move on, but your point that buying Tau is a bit like an ATF into the Bitcoin economy. I like that a lot because frankly, I don't think right now I would have confidence to say, Jason,

SPEAKER_59: here are the top three subnets. These are the ones that are going to win the other 125 or whatever, but I don't mind having kind of like a effectively a call option on decentralized global intelligence.

SPEAKER_160: So that, that translates well for me. I appreciate that.

SPEAKER_15: Yeah. And I, you know, listen, everybody wants to debate me and like, I'm not writing the code of BitTensor. I haven't been like a market participant in crypto aside from, you know,

SPEAKER_87: my, uh, you know, uh, some bet, small bets, uh, we've made as a family office, but it's, uh,

SPEAKER_15: my job is to explain it in plain English and to explain my thesis. So for people who are like, you're pumping this for people who are like, you don't know what you're talking about. Of course, I don't know what I'm talking about. I am an investor. I am a commentator. So the way I choose to place bets is not by writing code, not by being a subnet, uh, participant or launching a subnet. My way is studying, placing bets, losing bets, learning, placing more bets. And that's the job of an investor is you learn by betting. My job is to learn by betting and to have conversations, which is what I'm doing here. So to the mids and the weirdos, you know, now I'm, I got all these crypto weirdos back in my replies again. You poor thing. It's the worst.

SPEAKER_04: I'm trying to think of like, what's worse, like the mega bots who are still loyal to Trump after,

SPEAKER_170: you know, he starts a forever war or hopefully not a forever war, but you know, that group of people in my replies or the crypto people in my replies saying, have fun staying poor. And I'm like, guys,

SPEAKER_171: I'm worth collectively more than all of you. I'm doing okay guys. You know, like,

SPEAKER_173: it's so tribal though at times. And I think, I really hope that maybe, maybe BitTensor can,

SPEAKER_09: can help break some of this, but people get so parasocial about their favorite token that it

SPEAKER_04: becomes nigh religious. And then they, it's the nature of humans, Alex. I mean, I, I literally, when I told Mac people like back in the day, like how that's, yeah, some of the Mac decisions were, they would lose their minds when I would tell them how like pathetic it was that Microsoft couldn't

SPEAKER_93: build a UX and have less than 300 things in sub menus. Like they got upset. I'm like, okay,

SPEAKER_155: this is just valid criticism. Like people want a headphone port. People want an on off button, you know, like just give them the volume buttons, you know, it's not like a big thing to keep a

SPEAKER_179: headphone port on your laptop, like bad decision to remove the headphone port. I'll, I'll die with that.

SPEAKER_23: I'm still mad about it. And I own several pairs of wireless headphones, but I also like to listen

SPEAKER_158: to audio sound as Jason for more than 20 fricking minutes. Exactly. Exactly. All right. Let's keep

SPEAKER_15: going. All right. And I welcome the feedback from crypto minutes. Congratulations on hitting. I was

SPEAKER_187: getting into a fight with a guy about this stuff. And then I looked, he had eight followers and he started his account in 2013. I was like, congratulations on almost hitting double digits in your follower account. I'm like taking this account seriously for 15 minutes of my life.

SPEAKER_191: That's Jason. That's one follower per year. That literally is that 0.6 followers per year. And by the way, I get 20.

SPEAKER_15: I probably get a hundred at this point. Bots following me per day, right? Like, yeah,

SPEAKER_187: it's not hard to get past 10, bro. And then I look, he's tweeting 20 times a day with eight

SPEAKER_194: followers. I'm like, what's the point? You have to be pretty toxic to tweet that much and end up with no followers unless you're like blocking people that are following. Anyways. All right. Next up,

SPEAKER_07: we're going to bring, uh, my new best friend, Ola Lehman on the show. Ola is a social media poster. He builds with OpenClaw, builds skills for Claude code, runs classes for people, and built, Jason, what I think is the single coolest skill for OpenClaw we've ever yet had on the show, though we are going to show it off inside of Claude cowork. Ola, welcome to the show. Unmute your microphone and tell us all about Andre Carpathie's idea behind the council of advisors.

SPEAKER_201: Yeah. Great to be here. So I saw Carpathie's post, uh, for some context, Carpathie is co-founder. I was co-founder of, um, OpenAI later head of AI, um, with Tesla. So AI giga chat, and he posted about his LLM council, which basically has the idea of you have a question, you send it to different models. So Grok, Claude, chat GPT, all of that. They all come up with a different answer. Then the answers get anonymized and then they get peer reviewed. So every single model reviews all of the outputs in an, um, anonymous way. Then they get to the chairman. There's like another model at the end and the chairman just comes up with the final verdict. So that, that was the idea of, um, Carpathie's council. And I really liked that idea, but I thought, okay, it would be cool to build something in Claude. That's more based around basically giving you basic advice for everything

SPEAKER_07: in your business and also for general life advice. So is your council of advisors using different models for each of the advisors that debates the question, or is it one model with different personas attached to it to kind of talk amongst themselves? Yeah. So this is just one model. So

SPEAKER_201: I'm just using Claude Opus 4.6 right here. Um, it's because most part of my audience are really non-technical. So I wanted to build something that's still kind of simple, but still uses the same concept that Carpathie uses. So I was just using Opus right here. So let's ask it a question. Let's

SPEAKER_07: let Jason pick a question. And then as it thinks, I want you to talk us through what it's doing. So

SPEAKER_09: Jason, uh, what's a good startup question for founders that would they be asking themselves today?

SPEAKER_211: Sure. Um, how much equity should I give my VP of engineering who has five years

SPEAKER_142: years of work experience and who previously worked at Google? I'm a seed stage startup. That's raised

SPEAKER_212: three million dollars. I am a solo founder and I have 85% of the equity and my investors have 15%.

SPEAKER_146: I wonder how many tokens this is going to consume.

SPEAKER_211: Not a lot. It's not so bad. And this is how, you know, the more specific you get, the better the models tend to do. And then what you're doing only is you've given one model,

SPEAKER_14: Anthropics exceptional model, but you've, you haven't have four or five different personas. So you've loaded into those personas, a contrarian, like, why would this fail? You've got a first

SPEAKER_142: principles thinker and Elon Musk on the team. You've got an expansionist, which would be like a Jcal.

SPEAKER_04: How does this grow faster? You got an outsider. Um, who's like, I don't, I've never, I don't even know what you're talking about. I'm done. And then you have an executor, um, and who's like a sycophant

SPEAKER_15: who says, Hey, I'll get it done for you or something. I would put the sycophant in here too, but okay.

SPEAKER_201: Yeah, this, this is the basic idea. And, um, again, what's important that you have the step here to anonymize all of the responses before the peer reviews happen. That's like one of the key steps here. So once that happened, we can see if they already, in the beginning, it would spin up five different sub agents. So this is really cool because Cloud Code or Cloud Cowork. So this also works with Cloud Cowork for everyone watching. Um, I just like to use Cloud Code more, but it's just the preference here. Um, it totally works too. And again, this is because Anthropic now has these agents working inside all of their products. So it just spins up different sub agents.

SPEAKER_116: So it does it in parallel, saves a lot of time. You anonymize the five, um, different responses

SPEAKER_00: because when you go to the peer review stage, you don't want it thinking, Oh, this is the expert. This is the contrarian. You want it to just evaluate it, you know, without any baggage, correct?

SPEAKER_222: Exactly. And I, I read Karpathy's, um, thoughts on that. And he was quite surprised that in this

SPEAKER_201: version, he used different LLM models and they, um, oftentimes rated other LLM models higher than themselves once, um, this peer review thing kind of got started. So it really helps because most of these models have some kind of bias, especially, um, when it comes to rating other stuff. So with this, this step really helps to, to get to a, to a better, like more balanced opinion. This is also why I chose these, Jekyll already like talked about this a little bit. I tried to include opposites a little bit. So the contrarian is kind of, what is the downside? The expansionist is what is the upside? The first principle thinker is kind of takes a step back. It goes deeper into thinking. And the executor is just going forward. I'm just full throttling. Um, not really thinking, just doing and the outside. Maxing, just call it what it is. I'm actually going to drop an article

SPEAKER_226: today about maxing. So it's funny you talk about that. I'm sorry to everybody who's offended by

SPEAKER_187: the word, but it's in popular culture right now. It's not going backwards.

SPEAKER_15: Yeah. Um, it is what it is. But, uh, for people who don't know, stop ruminating, don't go to therapy, don't overthink things, folks, just go forward and build. It's all that

SPEAKER_14: matters is building and making your venture capitalists more money faster. Let's go.

SPEAKER_201: We can see, you know, all the advisors now responded and is running the peer review. It's also complete. So now it all comes to the final stage here, stage three, which is the chairman. And so the chairman gathers all the data and all of these different responses. So the, the council members rated, okay, who has a strong response? Who is the weakest? Also what I can blind spots that some of the, the reviews missed. And also I added this thing. So this is not from Karpathy, but I thought it's kind of a good data to have is the, what did all five miss? So they all sit down and try to find things and all of them missed. Ooh, love it. So that's kind of an extra angle here.

SPEAKER_224: Now wait, how many people are on the peer review and did the peer review people have personas? So the peer review still happens in these personas. Ah, got it. So the five are evaluating each other's answers without knowing them.

SPEAKER_201: Exactly. Yeah. And they go through these three questions here. There's a little bit more context in the skill. Um, but this is kind of the basic principle of it. And then they go, go to the chairman and once the chairman has all the data, he creates a report for you. And this will be shown on a dashboard. So hopefully we'll get there. Yeah. It's still.

SPEAKER_07: Well, while it works Ola and while we wait for it to finish doing its number crunching, can you just quickly break down for folks, uh, when you'd like to use cloud code slash co-work and

SPEAKER_09: when you prefer to use open claw, because I'm seeing a lot more folks in my circles start to tinker more with co-work and I'm still a claw guy. So I'm curious pros and cons and what I'm missing.

SPEAKER_201: Yeah, that's, that's a really good question. I would say for me, the most like more serious in-depth work I like to do in a cloud code or cloud co-work just because most of my open claw is in my telegram. Um, I think the, the big upside of open claw is that you have the, the memory system built in. You can also get there with cloud code using things like obsidian, for example, or using projects now in co-work. So it's kind of, it's becoming a little bit more alike over time, I would say. Um, but in general to me for, for more in-depth work, I like to use, uh, cloud coaches, uh, to be very honest with you, because I like the interface more. You can probably do most of the work on open claw, but in, um, in cloud code, it's easier for me to also work on my local, on my local files and just be like, Hey, just put this in this, do this folder. It's also a little bit, I would say habit because the truth is I could potentially do most of the work I'm doing inside cloud code or cloud co-work inside open claw. One big difference I would say is, especially for non-technical people who I mainly talk to is you have, you have better or like easier control inside co-work. So you can just go into your connected apps. So let's say Gmail or Notion, and you can just see these are the permissions I gave my co-work. But if you look at open claw, sometimes it will just do things and you don't really understand like which permissions you gave to it, or you maybe gave it an API key is still in there. So there's some files, some stuff is safe, but you don't have a good overview. So I just think that Anthropic is doing a great job of just making

SPEAKER_223: it more accessible and yeah, just easier to use for non-technical people. Now, is this all open source,

SPEAKER_252: Ole? And is it a skill in open claw? Where does this exist? If people want to build,

SPEAKER_254: or are you building this as a proprietary startup that I can invest in?

SPEAKER_245: Yeah. So you can just get this from either my X account. So you can find me at

SPEAKER_201: it's Ole Lehmann and I pinned it to my profile here. So it's an article here that I wrote about it and you can find this as a Google doc in there. I also put it into GitHub, but again, I'm mainly talking to you.

SPEAKER_179: And we will put this in our enhanced show notes. I have given producer Jacob and producer Oliver explicit instructions that I want enhanced show notes. So I want them running the show notes

SPEAKER_15: and asking our own, I want them to ask our own LLMs, our own council, what did we miss in the transcript that could have been linked to? And I want to do that like twice. Yeah. That's good. And I want to have absurd show notes going forward with tons of links in it. Why? I take notes myself, Alex, when I'm listening to a podcast or I'm listening to an audio book. So let's really do

SPEAKER_179: that with our show notes. I want enhanced show notes, please. And if somebody wants to make a skill for OpenClaw to do this, I will put out a $1,000 bounty. And on let's say May 1st, I'll give the $1,000 bounty for the open source project that proves they can do incredible enhanced show notes for

SPEAKER_211: me for twist. Okay. I'm doing this new, this is a new program we're going to do here, Alex,

SPEAKER_87: which is the bounty program. I'm going to offer money for OpenClaw skills so that we can keep the

SPEAKER_183: capitalists who I'm invested in from killing OpenClaw. This is our format here is demo or die, folks.

SPEAKER_211: And so in the tradition of the, what was the original computer hacker club called Alex in,

SPEAKER_112: um, this is like a good, uh, jeopardy, uh, was the computer something club. Uh, and it was in like Palo Alto or whatever in the seventies. And like Steve jobs used to go to it and they would just have demo or die. What was chaos, chaos computer club? No, it wasn't the chaos computer club. It

SPEAKER_266: wasn't like 2,600 out of New York computer club founded, uh, 1975 Menlo park, Palo Alto premiere

SPEAKER_146: 1970s hobbyist group, Steve Wozniak, Steve jobs, the homebrew computer club. I want to do an episode

SPEAKER_15: on the homebrew. We'll do like an acquired episode, you know, like when they go like, do a deep dive. Uh, Jacob put this on for the summer schedule, deep dive homebrew. And I want to do an oral history of the homebrew. This is new from this week and startups from the mind of executive

SPEAKER_254: producer, Jake, how I want to do an oral history documentary on it. And we'll, we'll debut it as a one or two part series during our summer session. Now we have the council report and it, uh,

SPEAKER_245: gives a recommendation first. We can just have a look at it.

SPEAKER_14: Take a look here. The recommendation 0.75 to 1% offer 0.75 negotiate up to 1% ceiling. If pushed, you're a C stage with 3 million raised and a series a coming that will dilute everyone by 20,

SPEAKER_211: 25%. Okay. That seems likely. Uh, I would have said 15 to 20% Google tenure and five years experience are real signals. Correct. That's why I gave them, but they don't justify top of the market. You need room for two to three more senior hires before or after your series. And that's true. Structure it as ISOs with a four year vest, one year cliff, that standard double trigger acceleration. That's a fancy way of saying if the company gets bought, they get their vesting, um, push for it in case like the acquirer doesn't need the CTO. Uh, if the candidate pushes beyond 1%, shift the conversation to base salary first, moving base up is cheaper long-term than moving to equity. That's true. If you succeed, because equity compounds through dilution rounds and salary does not. The one thing to do first, create the option pool before this conversation, a 10 to 15% option pool documented and board approved. So the VP offer is priced against real post pool cap table, not a number that will change the moment you formalize the hire. This is critically important. This is something I wasn't even thinking of.

SPEAKER_87: So that's a great, great, um, punch up there that I put in yellow where the council agrees.

SPEAKER_274: Every advisor landed the same, uh, mechanical range 0.5 to 1.5. And I didn't do CTO. Oh,

SPEAKER_87: right. I did VP of engineering, I think, which is like a step below CTO. Um,

SPEAKER_272: what the council clashes on the ex pensionist push for 1.5 to 2%. That's what I was going to say. I was

SPEAKER_211: going to say two to 3%, but I am the optimist pushing for like getting great candidates. I would have said 2%. Um, um, blind spots, council caught cash equity trade-off option pool math and role trajectory. Does this person eventually become the CTL? Wow. Oh my Lord. This is exceptional. Like if you had a discussion with your board as a founder, you would not get to this answer, uh,

SPEAKER_00: as crisply and as cleanly as possible. This is why I think you should create a digital board of

SPEAKER_14: directors from day one of your startup and having it get completed access to your Slack and working

SPEAKER_18: on these decisions. Really genius. Amazing. Can you click on just one of these for me, Ola,

SPEAKER_201: so I can see what it looks like? Yeah. Okay. So this is one response. The outputs, the individual outputs of the, um, of the different council members. And it also gives you some highlights here and some, some blind spots. And I, I think the general idea is everyone who like makes important decisions has a council, right? Like the president has a council, like maybe, you know, in, in every decision is made by having influenced by these people that have in-depth knowledge. And if you have a startup, you would have never had these opportunities or these resources before. Like Jake had said, now you have an LLM and LLMs are so good to like stepping into another role. And also it saves a lot of your own biological compute, because if you have to think and emphasize with a different, different opinion every day, it takes so much of your, of your own, um, of your own energy. So for me, it's just helpful to let these different council members run through, um, to, through ideas because yeah, it's, it's such a big, big advantage. And most people don't use LLMs for that. And they're

SPEAKER_59: extremely good at that. You said that Claude Mythos is quote, Hiroshima for software. Um, that's a very vivid image. You might say, uh, why are you that concerned right now? It's under

SPEAKER_07: lock and key. Jason and I talked about project glass wing. Um, it seems like we're a bit of a

SPEAKER_201: holding pattern. Why are you so scared? I just think it's a point in time. It's, I don't want to be too alarmist, but it's one of these point in time where it just makes sense to take a step back and take your security seriously, because the downside, if you don't, is just so immense, right? Like they're just, if you have a big moment of uncertainty, it's usually smart to take some measures. And I think, um, just taking these basic security measures is something everyone would do, but most people never do them. I think if you, if you just ask the random, a random person, like, what are your security measures? They are incredibly bad. So this is why I made this post. The headline was kind of extreme just to get to attention, but the, the, the meat of the post was just, Hey, these are the basics of security. And this is a good point in time to take them seriously. On the other hand, we don't really know how advanced Mythos is, right? Like maybe you do all the security measures, but it's still going to be so advanced that it's just a drop in the ocean, right? So that's the

SPEAKER_222: big question here. And just, Ole, before you go, what's your story? Where are you based? What do

SPEAKER_201: you do for a living? Yeah. So, um, I'm based in Cyprus. I'm German, but I'm in Berlin right now. Um, I'm the founder of the AI Solopreneur, which is an AI media and training company. So I mainly, mainly do media around AI. Um, I do some B2B consulting for companies. I'm focusing more on GTM engineering. So everything AI automation based, um, around marketing, around building distribution. All right. You're hired. Yeah. I really believe. Yeah.

SPEAKER_04: Everything you want to work in venture capital, you're hired. You'll be the first and only European employee I've ever had. You seem brilliant. Uh, really appreciate you coming on the program

SPEAKER_93: and everybody sign up for Oli's, uh, sub stack.

SPEAKER_07: Sub stack. Yes. It is AI solo.beehive.com. B E E H I I V.com. Screw sub stack, Jason. That's so 2024. Everyone's now on the hive. Yeah. Beehive is a great product too. And, uh, I love a little

SPEAKER_220: capitalism and, uh, I'm trying to bring capitalism back to Europe. I'm saying.

SPEAKER_254: Yeah. Good luck. Be careful. You might get shivved. Uh, yeah. What are you paying taxes? What's your, what's the high tax rate where you are?

SPEAKER_201: I mean, that's why I moved my business to Cyprus and I have residency there. This is like 12.5%. So

SPEAKER_287: I'm, I'm pretty, I'm pretty fine with that. This is amazing. Now, if you were still in Berlin,

SPEAKER_293: you'd be paying 52% or something. Yeah. It's around 50. Yeah. That's what I've paid before. Yeah. Yeah. See, this is a, one of the important things that people have to understand the most, uh, savvy

SPEAKER_112: entrepreneurs, especially ones outside the United States, because, uh, unlike Americans, Europeans can move

SPEAKER_87: to Dubai and pay like one or 0%, uh, Singapore or whatever. And they get tax treatment, Alex. That's extraordinary. If you're an American and you try this, you still have to pay your federal.

SPEAKER_112: So you're still on the hook for 30% or so. And, uh, the Americans move abroad. The only thing they get a benefit from is state taxes. What do you pay in state taxes, Alex? What's the, what's the VIG up in, uh, Rhode Island? I don't know, but I'll find out. Yeah. That's how rich, uh, Alex is. He doesn't even know. He's just pouring in this money.

SPEAKER_96: From all his, uh, incredible. Uh, so 3.75% up to 6%, uh, top rates for income over 180. Oh,

SPEAKER_142: that's not very high. Okay. I mean, it's half of, you're basically half of California, New York.

SPEAKER_07: Yeah. I think we're at 13% state. But our state is 1% as large. So whenever we try to do high speed rail, it's only eight cars long, you know, so it's pretty cheap to run a state. Basically,

SPEAKER_305: the tip of the train is already at the next station and people are still getting off the last.

SPEAKER_193: I can't believe we have two senators. Like it's incredible to me. Like you can literally

SPEAKER_146: see across Rhode Island. Shout out to our founding fathers. Like what's the least

SPEAKER_15: popular state? Is it still Wyoming or Nebraska or something? It's unbelievable how our system works, that a state with, you know, a fraction of the, uh, population of these other states get the equal.

SPEAKER_146: Yeah. It's Wyoming. Yeah. It's Wyoming. 580,000 people. That's so few. I'm pretty sure they have a

SPEAKER_07: lottery and you draw out of a hat. And if it's your turn, you have to be representative in Congress.

SPEAKER_112: I mean, it's basically, you have a, uh, yeah, if you have two, you have a one in 250.

SPEAKER_191: The chance of being a Senator, I'm moving to Wyoming, Senator Jake out from the great state of Wyoming. We're dropping you off, but you're coming back on this program. Cause you crushed it.

SPEAKER_15: Okay. Thanks. Oh, I appreciate you, man. All right. Listen, everybody wants to know, Jake, how you look great. You're no longer a fat bastard. You know why? Because of road.co. I have been doing a GLP. Yes, it's true. And I lost 40 pounds and I've added muscle. If you are GLP curious road.co is my partner and they do a great job. Now you don't

SPEAKER_142: need to get Roe sparks. If you're great, you might want to pick up some Roe sparks while you're there, but I'm going to say GLPs are life-changing. Do your research and then use the checker. They have an incredible insurance checker. If your insurance doesn't cover it, man, it's getting more and more

SPEAKER_18: affordable. Thanks to folks like road.co. What's the offer we do. It's road.co slash twist. If you

SPEAKER_07: want to check your insurance road.co slash twist, it's very affordable, very good. And you should all

SPEAKER_93: go check it out. Uh, well, let's go off duty. This is your first chance to go off duty. We're doing

SPEAKER_112: off duty at the end of the program. Why are we doing it? Uh, people love to know what, um, you know, we're into when we're not doing podcasts or investing in companies or writing newsletters. So, uh, your first Alex, what, what are you consuming obsessed with or otherwise? Uh, yeah.

SPEAKER_07: Find yourself enamored by. I think for me, it's the egregiousness in a recent television show of a

SPEAKER_09: Microsoft bit of Astro turfing. Now we all know that Apple has rules. If you have an Apple computer in a movie, you're not allowed to have the bad guy use it. That sort of thing. They're very image conscious. Uh, Microsoft on the other hand, in a clip that our, our dear friend lawn pulled for us that I, that I watched and it's terrible, uh, goes to show how not to do product placement. So if you are on the Microsoft co-pilot team, let me tell you, this is egregious, Jason,

SPEAKER_07: get your vomit bucket ready and tune in. Now, wait, this is yours or this is lawns. Well, we, we both agreed on it. We'd talk back and forth on the show today. Yeah. Cause we, we co-produced because he has surgery and such, but, but you're endorsing this or no,

SPEAKER_173: I, I'm endorsing the badness of this. I, I'm saying that have you watched this? Okay,

SPEAKER_320: here we go. Oh, several, several times. Oh yeah. Oh, okay. Here we go. Please enjoy.

SPEAKER_322: I'm a water, New Mexico, San Angelo, Texas, Yakima, Washington.

SPEAKER_326: You know, I can run it in co-pilot. I'll have it categorized police reports by location, date and name, then color code them by location and create a summary of the findings. Okay, here we go. Wait a second. I'm finding reports on alleged scams in multiple cities he's lived in. Like he posed as a startup investor in Phoenix, a high-end real estate partner in Ojai.

SPEAKER_331: So he's not a businessman. He's a con man. So Frank was his next target. That is essentially

SPEAKER_194: a television commercial inside of a television show. And Jason, I'm not a big procedural guy,

SPEAKER_07: but if I was watching ABC's hit show, uh, High Potential, I'd be pissed that they just sold me out to Microsoft. Who is that for? Wait, is that a Microsoft co-pilot? Is that Claude co-work? Oh, no, I think it's Microsoft co-pilot. They were in Excel there. So I thought that was, and they said co-pilot directly. That's not co-work. Got it. They did say co-pilot. Don't you think Anthropic

SPEAKER_14: would have slightly better taste than that? Yeah. Listen, uh, product placement is, uh, a great way for

SPEAKER_142: these folks to, uh, make money and reduce the number of ads, but it does feel smarmy to me at times. I'm a fan of like when they just have a Heineken in the background or something to that effect, but this type of product placement is like literally being bashed in the, in the skull, in the middle of a show. It takes you right out of the experience. I'm going to go ahead and say

SPEAKER_59: the scratchy odd ABC. Yeah. Terrible. But, but Microsoft is the one who should have just more quality control here. Like you have trillions of dollars in market cap, hire someone who has taste.

SPEAKER_09: Like, like this actually makes me doubt their ability to make good products because they can't

SPEAKER_18: advertise them well. Maybe that's too much apple in my head, but I want, here's the thing. If you

SPEAKER_14: are spending more time promoting your product than making a great product. And yeah, I don't know, I haven't used this product, so I'm not making a judgment on it. Uh, that is what I call pouring

SPEAKER_15: kerosene on a giant, you know, tree that's been felled in the forest. You can start a fire. You might even start a forest fire, but generally you're going to wind up with a charred giant log. You want to build your company and your product through what I call a kindling each piece of kindling. Those little tiny sticks are the like first 10 users. You get that fire going, then you put sticks after you have sticks. Then you might put like branches after branches, you might put logs, but you want those hot embers. And you want to go nice and slow, you know, and, and get those users in there who are the early advocates who give you great feedback. You don't want to just go right to marketing with your startup. That's a good poll. I like it. Here's my poll. Uh, I have always loved the character

SPEAKER_87: Darth Maul. Darth Maul is the guy with the two-sided light saber, and they have created a series called

SPEAKER_347: Maul. And I have now watched the first episode three times. Three times? With my 10 year olds,

SPEAKER_15: uh, cause I watched it myself. Then they wanted to watch it. Then they wanted to watch it again. The first two episodes are out. I think they're dropping two episodes for five weeks in a row

SPEAKER_211: on Disney. Here's a trailer. I'll talk over it. Uh, the first episode, super banger. Second episode, incredibly good. And, um, you can see that the animation is very unique. The animation was created

SPEAKER_142: because they did some, um, watercolor paintings, and then they put that into the animation software and they created a very unique new look that I've never seen. The Clone Wars had its own style, but if you look at this, it's very cyberpunk. Yeah. Reminds you of Blade Runner. And this is like Andor in that it's telling another story that occurred during the timeline. And this is the story of Darth Maul who survives when he gets cut in half, uh, by a young Obi-Wan Kenobi. It's like a dark, underworld, underbelly show. Now, why is this also important? It turns out that the sequels, episodes seven, eight, nine of Star Wars were supposed to be having Darth Maul as the lead,

SPEAKER_15: not bringing the Emperor back, not all this nonsense. They threw away George Lucas's treatment.

SPEAKER_14: They destroyed the franchise with these Disgratziad episodes, seven, eight, nine. Those should be

SPEAKER_00: decanonized, but instead they took the elements of George Lucas's sequel, and they just placed it between episodes three and four when Andor occurs, when Rogue One occurs, when the Han Solo movie

SPEAKER_15: occurs. Essentially when Luke and Leia are, you know, babies or toddlers, uh, before Obi-Wan goes and,

SPEAKER_87: starts teaching Luke Skywalker to be a Jedi. It's extraordinary, uh, already. I have great hopes for this one. And, um, you know, they're, they're just trying to get this, uh, Kathleen Kennedy

SPEAKER_254: disaster of a, uh, and JJ Abrams, who basically these guys just, they took Star Wars off the rails.

SPEAKER_15: They're trying to fix that with Andor, Maul, et cetera. And I am here for fixing the, uh, you know,

SPEAKER_87: Disgratziad of Kathleen Kennedy's horrible reign post George Lucas and throwing Lucas's genius in

SPEAKER_356: the garbage. Um, yeah. And so. Which one had Ray in it? That was the Disgratziad, uh, sequels.

SPEAKER_14: So four or five and six are the original Star Wars. Uh-huh. Seven, eight, nine were supposed to be the

SPEAKER_15: Darth Maul ones that would have Luke and Leia reestablishing the Jedi Academy, training a new series of Jedi. We didn't get any of that. We didn't get any of that while, um, Carrie Fisher was alive. There's a lot of resentment in the Star Wars community because of all of this. They didn't even have the story arc for seven, eight, nine, you know, done. They just did a money grab because Star Wars was bought for whatever, four or five billion by Disney. And they just killed the entire IP. Now they're going back trying to fix it. Um, and I think they just have to, yeah, go ahead.

SPEAKER_360: Jar Jar Binks though was in the prequels. So these are one, two, and three post schools. Okay. Thank

David Friedberg: you for that. There's the original trilogy. Yes. There's the prequels. And then there's the sequels,

SPEAKER_212: the sequels. Some people will refer to the prequels as, but if you look at it as a timeline, it's episodes one through nine, he released four or five and six, the most interesting piece in the

SPEAKER_112: seventies and eighties and into the nineties. Then he released the prequels in the 2000 era. And then they released, um, the, the sequels. And, uh, anyway, it's well worth checking out. And if you

SPEAKER_142: want to, if you've got kids or if you're just a Star Wars fan and you're on the treadmill, highly recommend Clone Wars, Bad Batch, Rebels, and now, uh, Maul. These are like the animations that fill in the series, but these are serious animations telling serious stories in the way

SPEAKER_112: Japanese, uh, folks do with their anime. So it's very influenced by all of that. And then Mandalorian, uh, and Ashoka, the TV show Ashoka, those are live action. Those kind of thread into here

SPEAKER_14: and or is live action and those thread into this awesomeness. Uh, the second thing I'll give you is I just bought the new Mac book pro and here it is. I bought the 14 inch. I spent $3,500 on a computer

SPEAKER_212: on a laptop for the first time in a while. Actually I have a Dell, uh, alien where that

SPEAKER_15: I spent a similar amount on, but this Mac book pro two with a great screen is amazing. And I think the future is going to be SML, small model languages. I think, uh, doubling your spending,

SPEAKER_112: getting one of these M fives, you don't need the M five max that's for video, but the real key is getting to that 48 gigs of Ram and, you know, very simple things in your workflow. You'll notice are much faster on the other end. There's this, uh, Neo, uh, Mac book that uses

SPEAKER_14: like a mic, uh, uh, uh, a mobile chip that's for $600. And then here's your six times more like a $3,600 laptop. When you put it at max memory for that M five chip and get to 48. There's like a

SPEAKER_15: larger one you can get to with 128, but then you're in the 16 inch, which is like five pounds. It turns out the Mac book pro is essentially the same weight as the Mac book air. I was a huge Mac book air fans.

SPEAKER_112: That's what we're standardized on. But I think in the future, we're going to be putting everybody on higher powered ones so we can run open claw and local language models in the future. So I just

SPEAKER_371: want to let folks know who are wondering if they should do it. In my opinion, you should just go ahead

SPEAKER_112: and upgrade it to a Mac book pro and spend the 3,500 bucks. 3,500 bucks is like a month of child

SPEAKER_09: care. Get yourself a real computer. Although I will say my Mac book Neo that I bought very recently,

SPEAKER_27: just because I wanted to have what you bought the Neo. I bought the Neo. I have one. Well, what are your impressions? Oh my God, this is like a perfect off duty. Go.

SPEAKER_191: All right. So what color did you pick and you paid 600 bucks for this thing?

SPEAKER_07: I got the pink one. I got the cheapest one. Uh, I got pink for two reasons. One, it's my second favorite color after blue. And also you wear pink shirts. Yeah. Yeah. I can give it to my, my oldest daughter when she's computer age because she loves pink. So problem solved. Uh, I bought it because I wanted something that I could just throw and take with me. Um, I have a lot of big, heavy computers, desktops, large monitors, my twist Mac book pro.

SPEAKER_207: What does that thing weigh? A pound and a half, two pounds, something like that.

SPEAKER_07: Well, it's not in the case of the twist computer. It's not that I care about the way it's

SPEAKER_207: more that I don't want to do. No, no. The Neo. What is the Neo way? The Neo way. I will find that out for you. Uh, but it, the problem is Jason, it is the first Apple computer or Apple device I have ever used 2.7 pounds.

SPEAKER_18: That feels so cheap. Like when you type on it, it does not have that Mac.

SPEAKER_14: Ah, so not. Okay. Yeah. So making a $600 computers means it's going to be compromises.

SPEAKER_87: Yes. But clearly they're going after the Chromebook market and, uh, you know, kudos to them. I said years ago, what should they do with their, you know, massive, uh, cash, um, war chest, you know, hundreds of billions of dollars. They probably still do. It was the largest hedge fund in the world at a point in time, like their treasury. I just said, why don't they just lose money on iPad pros with keyboards and put that into the education sector and come up with a $200 iPad and just make it the standard. Cause remember the iPad was kind of like

SPEAKER_142: this forgotten kind of a compute device. And I was like, what if they can just get many more of those into the operating system and make the money downstream on services? I believe that's what they're doing with the Neo. I don't, maybe they make a hundred bucks on this thing or 150 bucks, whatever they make on, it's not going to change the fate of Apple, but it's going to train young people. It's going to get them onto iCloud. It's going to get them to buy additional storage. It's going to get them to buy Apple music. It's going to help the app store. Why not get another billion people in the emerging world to use Apple computers, as opposed to windows or Chromebooks?

SPEAKER_14: Brilliant idea by them. But Hey, listen, there's going to be some compromises, but 600 bucks is the right price. That's the price of the Mac mini. So here we are folks, you know, Apple is really trying to get market share away from windows and Android.

SPEAKER_09: And I'll just say it's the first cheaper Apple device. It's still great, but you can just tell if you go from living in a, in a very Apple heavy world, that this is a step up from HP and a step down from your Mac book area, Mac book pro. But also here's the other thing is I'm an enormous nerd. Like I use computers all day long, different keyboards, different setups, whatever. Most people think AI is chat GPT. And so for them, I'm pretty sure this computer is amazing. And I don't think, I cannot imagine recommending any windows laptop when the Mac book Neo exists. It's too cheap. It's

SPEAKER_158: too good. And it comes in fun colors. What more do you want in life?

SPEAKER_347: I mean, it's, it's pretty great. I'm going to give one more shout out here.

SPEAKER_15: Um, so, um, I have been looking for, uh, you know, I, I like to understand the seminal, uh, works in an industry, but a lot of them are out of, uh, print and a lot of them, you don't even know about them. So I asked Claude or Grok or Gemini, what are the seminal works in advertising, in topography, in design. And so we're, we're building a newsletter for this week at AI. We're

SPEAKER_13: going to launch a paid newsletter. And I was just trying to get some, um, inspiration. And we had,

SPEAKER_356: um, the guy, um, from, uh, uh, the hustle and my first million on gosh, I'm sorry.

SPEAKER_15: And so there's a guy, Nigel Holmes, as an example, and he was the person at business week who came up with infographics, right? Where they would use wine bottles as the bar charts, all that kind of stuff, would use actual slices of pizza. And it just was a way to make graphics more interesting. I love infographics. So I buy, I go online and like, Hey, it's not in print. And it's like, well, you could buy the version from 1983 for five bucks. And then I buy the book and I don't feel guilty about writing my notes right in it. So Nigel Holmes is this, you know, he's the godfather

SPEAKER_13: of a design. You could pull up this book designer's guide to creating charts and diagrams. And I was going to give this, um, but I'll just tell, uh, Oliver and, uh, Ismael who are working on the newsletter to just go ahead and feel free to buy old books, put them in the library.

SPEAKER_12: Um, and this one, you know, came from a thrift bookstore. I don't know what I paid for it,

SPEAKER_212: but I paid, paid basically nothing for it. And I think the book came out in like 83 or 84.

SPEAKER_18: Yeah. You can call me for 54 bucks on Amazon. If you want, that's totally affordable.

David Friedberg: Well, that's 54. I got it for like 20. Oh no. I'm just saying like, usually when I look at a book from

SPEAKER_07: 91, I'm adding a zero to that price. So that this is super affordable for a book that old.

SPEAKER_04: Yeah. I think is, does it say 54 bucks on there? What does it say? There is a, uh,

SPEAKER_93: yeah. So if you look at the use, you'll be able to find one. That's not 54. This is just the first

SPEAKER_142: one that came up. They'll be like, there's a button for other sources or for the original

SPEAKER_18: library version. I'm trying to not accidentally show off my address online.

SPEAKER_04: No problem. No problem. So I'm trying to, then I got Ogilvy on advertising. This was like an old, um, book on advertising. Uh, and then there was this, my life in advertising

SPEAKER_142: and scientific advertising by David. Uh, these are two works by Claude Hopkins. And, you know, my thesis is, um, there are a lot of lessons that were learned in the seventies, eighties, nineties, when people were, uh, using other mediums that I find inspire me to, um, they just

SPEAKER_14: give me great inspiration. And, you know, I have a stack of them sitting there and I'm having a cup

SPEAKER_15: of coffee. I just take one out. I, you know, I get the highlighter. I write some notes in the margin and it's my little workbook. It's my little treat to myself. Maybe I'll bring one of them with me

SPEAKER_112: when I'm on a trip and open it up. And you're a fan of books. I see it. Well, no, I'm a fan of

SPEAKER_07: scribbling in them. Like this is a book I wrote with my dad, democracy in America. If you haven't read it, you should read it, but you should scribble on every page of your books. Like take notes,

SPEAKER_335: people enjoy yourself. Yeah. Uh, do we have time? It's a $10 book. It's a $20 book. Look at it as a

SPEAKER_07: moleskin and just get in there. It's a wear part, as we say at my house. Now, do we have time for one

SPEAKER_207: more, uh, off? Okay. So have you read a book called Hyperion? No, but I'm aware of it. Okay. Well,

SPEAKER_07: first of all, Jason, my gift to you, read it. It'll blow your mind. It's, it's crazy. You've never read anything like it. It's fantastic. And one thing that I'm really excited about that's coming down the road, which we had lawn here. He would know what to say about this, but they're making a movie adaptation and I'm torn because on one hand, I'm excited that they're trying to take this monster story to film, but I really think it would have been better as like a one season game of Thrones length series. So while we're waiting on that though, there's quite a lot going on in the world of science fiction. And what I wanted to give a shout out to on, uh, off topic today is this series of books from a woman named Bethany Jacobs. Uh, I'm reading the audio book version while I push my kids around in strollers. Uh, it's called the kingdom trilogy. First book is these burning stars. I am not a, like, um, I'm not into books that are like thrillers per se. They're like people chasing people around the solar system or whatever. This book has elements of that, but it has some of the best world building and characterization I've ever read. I'm in the middle of book two and I'm just absolutely hooked. It's the type of book where like, I don't want to go to bed because I want more of it, Jason. And I just still making such amazing art. And I just hope also that the mall show you showed off, I hope that in time it becomes cheaper to make stuff that awesome. So that way, not just Hyperion, which has been a famous book for decades, but also things like these books from Bethany Jacobs can also get their treatment because her works here are not nearly

SPEAKER_408: popular enough for HBO to pay attention, but they're good enough, you know? And so I just,

SPEAKER_207: I just want everyone to have the capability to make these awesome stories visual because we'd be so much richer. I think as storytelling humans, if we had that capacity.

SPEAKER_212: Yeah. And, uh, one thing I can recommend to you, which I had on a previous, uh, off duty was the

SPEAKER_142: shocks open ear headphones. And, uh, when you're walking with the baby, right, you don't, you need

SPEAKER_10: to hear if the baby wakes up. Right. Uh, and so wire cutter, which I tried to acquire, but, uh, the New

SPEAKER_112: York times bought it. Um, they have reviews of these, uh, bone conducting ones at the wire cutter. Uh, that's the open air fit. Uh, Oh, do I drive the wrong one? I liked her head. Uh, yeah. I look for

SPEAKER_413: the, uh, the, uh, open run. Yeah. So you see the open run right there. Well, if their website would stop trying to teach me how to use the internet and do everything. Yeah. So anyway, this thing

SPEAKER_142: looks a little weird, but it goes over and it's, it's bone conducting or it will just play it, but your ear is completely open. So now you can be listening to this and you're alert of your

SPEAKER_212: surroundings. So when I'm walking around a city, like in Japan, it doesn't matter if I'm

SPEAKER_15: wearing my fancy, like incredible high-end, um, you know, headphones and not listening to the outside world. But when you're walking in New York or San Francisco and you got to be alert, that could be like, you know, uh, uh, I mean, I'm not being facetious here. You do need to not have your AirPods on. If you're on the New York city subway, you're walking around certain areas of San Francisco, you want to be alert. And when we do with a kid, you want to hear if they're

SPEAKER_146: crying, boom, you wear one of these open air ones and you're good to go. So I just went to New

SPEAKER_59: York city last week for a couple of days. And I was remembering what you've said about it, a little gritty, a little, a little, a little dangerous. Yeah. I'm not going to lie. Jason, I can happily report that it was great. And I even took the subway by myself. I didn't get lost.

SPEAKER_61: It was super clean. There's now that display up that tells you what stops coming up. It's, I don't know. I was kind of, where were you in Manhattan or Brooklyn? Where were you?

SPEAKER_07: I was in towns. Did you stay from midtown to the lower East side and back around that area?

SPEAKER_15: Yeah. I mean, listen, it's, it's a bit of a crap shoot. Um, different like neighborhoods in New York could be phenomenally dangerous, different, uh, subway lines during, and other ones will be totally safe. Um, so, and the same thing for San Francisco, if you're up in the, yeah, if you're in the Marina, you're in pack whites, you're going to be fine. If you're in the tenderloin, you're going to be

SPEAKER_14: murdered. Did you just say pack whites? Yeah. Pack. The joke of pack heights is literally, if you walk around there, it's all whites. I used to live there. Yeah. That's what

SPEAKER_87: they called it. Pack. When I moved there, they're like, oh, you should move to pack whites. I'm like, I'm sorry, pack heights. They're like, no pack whites, because there's no crime there. There's

SPEAKER_14: zero crime. And if you call the police, they show up in 30 seconds. Whereas if you're in any other

SPEAKER_18: part, you know, they might take a little bit longer. When I met the CEO of zoom, uh, it was at a dinner at a venture capitalist house in the, in the fancier part of pack heights. So that tracks. Oh, the Broadway billionaires row. Yeah. Yeah. I mean, billionaires row,

SPEAKER_93: you have like a thousand cameras per block. The other areas of town, they've banned closed

SPEAKER_04: circuit cameras because, you know, uh, privacy. And it's like, trust me, anybody who lives in those areas is willing to give up privacy to be a little bit safer in pack whites. You've got 17 cameras on the front of every house. And like, if you like spit out your gum, you're going to have 16

SPEAKER_18: different videos of it submitted. Whereas when I was in a different neighborhood and someone spit in my mouth while I was walking down the street, not on camera. I mean, literally you could

SPEAKER_112: be shived. Um, all right. This has been another great week for twist. We'll see you on Monday. Bye-bye.