Bittensor's Rise, Meta's Llama Goes Cloud, & AI Now Writes Your Code | E2119

Today's show: Jason, Alex, Lon and Special Guest Mark Jeffrey of Hash Rate, cover the explosive rise of Bittensor, a decentralized AI compute network some are calling the "third great coin" after Bitcoin and Ethereum, explore Meta's bold move to host its open-source LLaMA models via partnerships with Groq and Cerebras—potentially setting the stage for a future AWS competitor—and unpack shocking revelations from the Wall Street Journal about Meta AI chatbots engaging in inappropriate conversations with underage users. Plus, we explore how AI is now writing up to 30% of code at major tech firms like Google and Microsoft, signaling a radical shift in how software gets built. Timestamps: (0:00) Episode Teaser(1:28) Introduction to the episode and guests(2:31) Mark Jeffrey's involvement in crypto and Bittensor project(5:06) Bitcoin vs. Bittensor: Stability and efficiency(10:20) Hubspot for Startups - Visit hubspot.com/startups and join the founders who are turning growth challenges into opportunities.(15:16) Governance, staking, and starting a subnet in Bittensor(17:52) Exploring Ready. AI and its impact on the future of AI(20:08) Squarespace - Use offer code TWIST to save 10% off your first purchase of a website or domain at https://www. Squarespace.com/TWIST(27:17) Trump's influence on crypto regulations and the stablecoin act(30:03) Oracle - Try OCI and save up to 50% on your cloud bill at https://w⁠⁠⁠⁠ww.oracle.com/twist(38:42) AI-driven VC outreach and Alexis Ohanian's advice on cold emailing(45:03) Introducing LayerNext with CEO Buddhika Madduma and customer onboarding challenges(49:04) Ikigai for startups and balancing bespoke work with scalable product development(55:38) Strategies for securing lighthouse customers and the 'bear hug' approach(56:43) Reddit rapid response: Debating the return to office for young professionals(1:04:05) Closing remarks and guest plugs Subscribe to the TWiST500 newsletter: https://ticker.thisweekinstartups.com Check out the TWIST500: https://www.twist500.com Subscribe to This Week in Startups on Apple: https://rb.gy/v19fcp Links from episode: Hash Rate Podcast: https://www.youtube.com/@markjeffrey LayerNext: https://www.layernext.ai/ r/antiwork: https://www.reddit.com/r/antiwork/ Follow Mark: X: https://x.com/markjeffrey LinkedIn: https://www.linkedin.com/in/markjeffrey/ Follow Lon: X: https://x.com/lons Follow Alex: X: https://x.com/alex LinkedIn: ⁠https://www.linkedin.com/in/alexwilhelm Follow Jason: X: https://twitter.com/Jason LinkedIn: https://www.linkedin.com/in/jasoncalacanis Thank you to our partners: (10:20) Hubspot for Startups - Visit hubspot.com/startups and join the founders who are turning growth challenges into opportunities. (20:08) Squarespace - Use offer code TWIST to save 10% off your first purchase of a website or domain at https://www. Squarespace.com/TWIST (30:03) Oracle - Try OCI and save up to 50% on your cloud bill at https://w⁠⁠⁠⁠ww.oracle.com/twist Great TWIST interviews: Will Guidara, Eoghan McCabe, Steve Huffman, Brian Chesky, Bob Moesta, Aaron Levie, Sophia Amoruso, Reid Hoffman, Frank Slootman, Billy McFarland Check out Jason's suite of newsletters: https://substack.com/@calacanis Follow TWiST: Twitter: https://twitter.com/TWiStartups YouTube: https://www.youtube.com/thisweekin Instagram: https://www.instagram.com/thisweekinstartups TikTok: https://www.tiktok.com/@thisweekinstartups Substack: https://twistartups.substack.com Subscribe to the Founder University Podcast: https://www.youtube.com/@founderuniversity1916

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

• 0:00Jason Calacanis?

  Is there like a chance that like Tether, which is used for, according to 60 Minutes and, and Congress and all those hearings, used for really dark stuff in the world, terrorists, uh, human traffickers allegedly, uh, are using it, or maybe confirmed, and they've been banned in only states. Like, is that gonna become a legit thing?

• 0:19Speaker 01

  Yeah, I think it will. I mean, I, and just to, you know, back up.

• 0:22Jason Calacanis?

  Yeah.

• 0:23Speaker 01

  Yes, Tether's been used for those, I'm sure has been used for crimes.

• 0:26Jason Calacanis?

  Sure.

• 0:26Speaker 01

  So is, you know, United States dollars in briefcases, right?

• 0:29Jason Calacanis?

  Of course, yeah.

• 0:29Speaker 01

  Uh, by a much larger margin.

• 0:31Jason Calacanis?

  If we were to look at it, that, that historically is correct, because Tether hasn't existed, but today, like, the average criminal?

• 0:36Speaker 02

  Cryptocurrency is being used for between 40 and 50 billion dollars of illicit transactions per year.

• 0:44Jason Calacanis?

  Uh huh.

• 0:45Speaker 02

  That would be a magnitude less than US dollars.

• 0:49Speaker 03

  This Week in Startups is brought to you by HubSpot for Startups. Smart founders aren't piecing together random tools. HubSpot is the customer platform that thousands of startups use to scale efficiently. Get up to 75% off plus three months of perplexity AI for free. Go to hubspot.com/startups. Squarespace. Turn your idea into a new website. Go to squarespace.com/twist for a free trial. When you're ready to launch, use offer code TWIST to save 10% off your first purchase of a website or domain. And Oracle. Oracle Cloud Infrastructure, or OCI, is a single platform for your infrastructure, database, application development, and AI needs. Save up to 50% on your cloud bill at oracle.com/twist.

• 1:28Jason Calacanis?

  All right, everybody, welcome back to This Week in Startups. Very exciting show today. We've got an office hours at the end with one of our founders, but we're very lucky to have with us again, of course, Alex Wilhelm. You know him from TechCrunch and Cautionist Optimism, his Substack. And Lon Harris is here, original Twist, uh, co-host. And super lucky to have one of my oldest, dearest friends from Web 1.0 in the 90s, Mark Jeffrey, when I... Would go to LA and I was broke doing my magazine. Mark let me sleep quite literally on his couch. A very famous couch, in fact, in the history of entrepreneurship. Welcome to the program, Mark.

• 2:05Speaker 01

  It is the Excalibur of couches. So yeah, Travis actually slept on that couch a few times.

• 2:09Jason Calacanis?

  Okay, Travis from Uber, Travis Kalanick, myself. Mark had an apartment, you know, which when we were in our twenties was a big deal in LA. We would go to LA. Hey, crash on Mark's couch.

• 2:19Speaker 02

  The history of Silicon Beach here.

• 2:21Jason Calacanis?

  Silicon Beach, yes. For people who don't know, I had Digital Coast Reporter and Silicon Valley Reporter. I had two different magazines at the time, print magazines, and I would do Digital Coast events and Silicon Valley events. So I took the two cities that were in Silicon Valley and featured the startups there. It was an interesting model. Mark, I wanted to have you on today because you're down the crypto rabbit hole, but you are a crypto realist. You actually look for crypto projects that have some reality to them. And you're here in town in Austin because there's something going on with a very specific crypto project. So maybe you could just tell us what that is.

• 2:53Speaker 01

  Yeah, so I'm here in town for a crypto project called Bittensor. They had their first big event. Now, Bittensor is Bitcoin meets AI and Tau is the coin. And there's 21 million Tau coins only, of which like eight million have been admitted so far.

• 3:11Jason Calacanis?

  That's the exact same as Bitcoin.

• 3:13Speaker 01

  Yes, that is correct.

• 3:14Jason Calacanis?

  Does it use the same open source project or do they just thought that would be like a clever thing to do?

• 3:20Speaker 01

  They thought that the Bitcoin ethos was the right one to adopt, so it draws very heavily. It's very heavily inspired by Bitcoin.

• 3:26Jason Calacanis?

  Got it. Okay, so they're disciples of Bitcoin.

• 3:28Speaker 01

  Yes.

• 3:29Jason Calacanis?

  They're doing 21 tokens or coins.

• 3:32Speaker 01

  21 million, but yes.

• 3:33Jason Calacanis?

  21 million, what do they call them? Tokens? Coins?

• 3:36Speaker 01

  Coins.

• 3:37Jason Calacanis?

  Coins, got it.

• 3:37Speaker 01

  Sure.

• 3:38Jason Calacanis?

  Okay, what is the purpose of the project?

• 3:40Speaker 01

  So the purpose is to build an incentivization network, mostly for AI, but not necessarily totally for AI.

• 3:48Jason Calacanis?

  When you say a network, you mean a network of computers and CPU GPUs?

• 3:53Speaker 01

  Yes, I do. I do. So what did Bitcoin do really well, right? Like, why did it succeed? Well, Satoshi started off saying, I want to create kind of this alternative gold and I want to be able Move it around the world.

• 4:06Jason Calacanis?

  Hmm.

• 4:06Speaker 01

  So I have to also create this alternative universe SWIFT system, right? So how do I do that? And what he decided to do was he decided to incentivize people out there to donate electricity and GPU. They didn't pay them.

• 4:21Jason Calacanis?

  CPU. Oh, no, GPU.

• 4:22Speaker 01

  It was GPU later, CPU in the beginning.

• 4:25Jason Calacanis?

  Got it.

• 4:25Speaker 01

  So you could mine, you know, on your home computer. In the early days, not.

• 4:28Jason Calacanis?

  Right. Didn't work too well.

• 4:30Speaker 01

  So later on, no. But this, this whole idea of, of, you know, look, I'm not going to pay you. We're not going to make a company. I'm just going to give you Bitcoin coins that, that are generated by the network with every block.

• 4:43Jason Calacanis?

  For solving a math equation.

• 4:45Speaker 01

  Correct. Well, yeah. And so for finding the hash of the previous block, which I'm not going to get into the technical explanation of that. But bottom line, it boils down to guessing the number of gumballs in a jar.

• 4:55Jason Calacanis?

  Yes.

• 4:55Speaker 01

  That's really, you know.

• 4:57Jason Calacanis?

  In a way, it was busy work.

• 4:58Speaker 01

  It's busy work, right? It's trying to force your CPU to peg up and to prove that it has the computing power that it says that it has, right?

• 5:06Jason Calacanis?

  And for people who don't know with Bitcoin, the reason they created that was so that you would have a network of computers that essentially act like the SWIFT network, like a banking network. So the need was to build infrastructure and rails to move money around and to make sure you were sending it to the right person. Therefore, we'll just have you sit here and, you know, solve this, how many gumballs in the jar?

• 5:30Speaker 01

  Yeah.

• 5:31Jason Calacanis?

  Which also forces you to have a computer on the network with power.

• 5:36Speaker 01

  Yes.

• 5:37Jason Calacanis?

  And I think most people don't understand the intent of Satoshi. I haven't told anybody my intent when I did it, so.

• 5:44Speaker 01

  Yes.

• 5:49Speaker 01

  So basically Satoshi proved the point. So what was the end result of this, right? In aggregate, Satoshi created the world's largest supercomputer by several orders of magnitude. Even AI GPU, you know, in aggregate is, is not going to catch up to the Bitcoin network's computing power for at least five years. If, you know, if they, if all the chips that are created go to AI, that still won't catch up to Bitcoin for a very long time. So Bitcoin succeeded at it creating this incredible network through these incentives. So BitTensor looked at that and said, that's a really interesting dynamic. How can we harness that to do two things? One, let's do something useful with that GPU instead of guessing the gumballs in a jar. That's dumb. You know, I don't want to belittle Bitcoin because it's very useful for security.

• 6:34Speaker 01

  But as an activity, it's very dumb.

• 6:36Jason Calacanis?

  That has been the criticism. Hey, we're burning a bunch of electricity. We're putting up all these GPUs. But conversely, it does create a global, stable network. So, okay, we could debate it, but actually I think it was worth it.

• 6:50Speaker 01

  Yes.

• 6:50Jason Calacanis?

  BitTensor is the open source project to replicate this. Tau is the coin.

• 6:56Speaker 01

  Yes.

• 6:57Jason Calacanis?

  Tau is the coin that you essentially earn by putting GPUs on the network and then giving them primarily to people who are looking for a distributed computer network, a distributed compute network to run AI jobs on.

• 7:13Speaker 01

  Sort of, yeah. Yeah, so you're right up, right up to the end, you're right.

• 7:16Jason Calacanis?

  Okay, great.

• 7:17Speaker 01

  So, yes.

• 7:18Jason Calacanis?

  I'm trying, I'm recapping this for our audience because sometimes.

• 7:21Speaker 01

  Yes, I know.

• 7:22Jason Calacanis?

  Crypto people. I know, I know. No, no, it's not that they babble on. They start, you know, on the, in the red zone. They're on like the 20 yard line and I think people can't keep up with it. So I think we've set the stage here really nicely. Who are the people behind the BitTensor project? Are there notable individuals who created this and when was it created?

• 7:42Speaker 01

  Yeah, so it's, I think it's about four years old. Maybe, maybe as much, you know, it's about four years old. We do, we do know the founders. We do know the people who, it's a team of like five or six engineer people all over the world. I just met with one of them this past, you know, at the, at the conference. And then yesterday we spent like three or four hours. I was clarifying about just stuff that I didn't understand about the, the innards. They are doxed, so it's not like they're anonymous like Satoshi.

• 8:10Jason Calacanis?

  Got it. Okay, so BitTensor is the project. Tau is the coin. The network, instead of doing gumball math. Is doing, here is a competitor to AWS.

• 8:23Speaker 01

  They're doing many things at once. So there's actually, under the, under the, it's an incentivization network, primarily used to incentivize creation of great AI, not only that, but mostly that at the moment. And beneath that are 100 projects. And each of them are mostly AI, but not all of them are AI.

• 8:40Jason Calacanis?

  Got it.

• 8:40Speaker 01

  Right? And we can have a look at those projects if you'd like.

• 8:43Jason Calacanis?

  Absolutely. So this platform then allows you in a way to plug in your project as an individual with server capacity. So if I happen to be running, I don't know, Squarespace, and I have a bunch of servers that I stood up for whatever reason, I wasn't using AWS, I could say, hey, you know what, I'm going to allocate a couple of these H100s, whatever, to the tau, to the BitTensor network to earn tau.

• 9:08Speaker 01

  Yes.

• 9:08Jason Calacanis?

  And then other people could come in and say, yeah, I need some compute. And the goal would be it's cheaper, faster, or better, or just cheaper?

• 9:15Speaker 01

  Yeah, so it's

• 9:16Jason Calacanis?

  Then using AWS.

• 9:18Speaker 01

  So yeah, so let's talk about your specific example that you just gave is, are like, two of the, of the biggest subnets in

• 9:25Jason Calacanis?

  Oh, okay, I just guessed it, yeah.

• 9:26Speaker 01

  Yeah, so you got it right.

• 9:27Jason Calacanis?

  Okay.

• 9:28Speaker 01

  Um, so if you go to, if you show backprop, so I said there was a, there's, there's a hundred, um, uh, subnets in, in the BitTensor universe. Each one, each one of the subnets has its own coin inside, you know, that, that is also part of the, the BitTensor network, sort of like Ethereum, right? Now Ethereum has Other coins inside of it, the same

• 9:47Jason Calacanis?

  So if we're looking at this, just, we'll pause it for a second here, these are the subnets. So the network, BitTensor, the subnets, the number one one is called Chutes, as in Chutes and Ladders. It's been around for 129 days. It has a market cap itself of 89 million. The price of their coin is $98. Their emissions are 16%. Um, what does, say, Chutes do? Because I see there, there's a GitHub logo, there's a, a network logo, I don't know what that means. What is, what does this all mean?

• 10:21Jason Calacanis?

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• 11:06Jason Calacanis?

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• 11:50Speaker 01

  So the, so Chutes does exactly what you were just describing. So they're, they're a decentralized network of, of compute for AI. So if you want to run, you want to run DeepSeek, you want to run Mistral. Yeah, serverless, there we go.

• 12:03Jason Calacanis?

  Yeah, I'm watching it. I got it.

• 12:04Speaker 01

  So all of these, so basically you just come here. Normally you'd go to AWS, right? And you rent some instances and then you would load up your AI. This actually, you know, the, the shoots will allow you to just go there, click a button, pay a little bit of tau and start running your instance. And it's about 85% less than what it costs on AWS.

• 12:25Jason Calacanis?

  Got it. So if you were running an AI job and you didn't need the stability corporate five nines of say, AWS where, you know, at a company, maybe you have to use AWS because nobody gets fired for using AWS, Azure, Oracle, whatever.

• 12:42Jason Calacanis?

  You could use this network that nobody owns and that is an open source distributed project.

• 12:48Speaker 01

  Yes.

• 12:49Jason Calacanis?

  How stable is it?

• 12:50Speaker 01

  Uh, very stable. I mean, it's people, people are very happy with it. People are, people think it's better. Not only cheaper, but there are some benchmarks where it's actually quite a bit better than what you're, you're seeing out of AWS.

• 13:01Jason Calacanis?

  Got it.

• 13:01Speaker 01

  And typically they have the models up and running. When Deepsea came out with their latest model, it was up and running on Chute before it was up and running on any, anywhere else.

• 13:08Jason Calacanis?

  Hmm.

• 13:08Speaker 01

  And yeah.

• 13:09Jason Calacanis?

  So let's pull up the Chute's website again. I'm just want to give them a shout out here and make sure I understand it. We're looking at the Chute's website. It's basically a distributed peer-to-peer subnet that competes with other cloud computing resources out there. You can just basically as a developer deploy to it. And then I pay them in Tau.

• 13:30Speaker 01

  Yes.

• 13:31Jason Calacanis?

  So instead of me putting my credit card on file with my cloud computing company.

• 13:36Speaker 01

  They're gonna have that later, but right now, yes, they, you pay in Tau.

• 13:38Jason Calacanis?

  I pay them in Tau.

• 13:39Speaker 01

  Targon also, Targon is the, the other one that does.

• 13:42Jason Calacanis?

  Great.

• 13:42Speaker 01

  The other network that does, the other subnet that does the same thing as Chute's.

• 13:45Jason Calacanis?

  Great. Um, so let's pull up that top level of all the projects again, Alex, if you don't mind, we'll leave that up. So there's another one.

• 13:53Speaker 01

  Yes.

• 13:53Jason Calacanis?

  Called.

• 13:54Speaker 01

  Targon.

• 13:54Jason Calacanis?

  Targon.

• 13:55Speaker 01

  And they're very, uh, I think they're a little bit further along in terms of having the, the fiat rails up and running.

• 14:00Jason Calacanis?

  I see they're number three here with a $44 million market cap.

• 14:03Speaker 01

  Yes. Correct.

• 14:04Jason Calacanis?

  Um, and so we can load their page and we would see it. And these just look like any other hosting company in the world. But instead of using dollars and having an office, it's a distributed project, but somebody does own Targon, right?

• 14:19Speaker 01

  There, there is a subnet owner. Yeah. So good question. So, um, somebody has defined the Targon subnet and said, I want people to supply GPU to my network to host these AI models, right?

• 14:31Jason Calacanis?

  Got it.

• 14:32Speaker 01

  And load them up. And, you know, there are 256 miners that are competing to provide the, you know, this, this, whatever the, the subnet owner has requested. So it is a competition, right? Whoever supplies the most, the best, depending on how the subnet owner defines the competition. Um, the miners, uh, the people who are supplying. The computers or this decentralized network, they earn tau.

• 14:56Jason Calacanis?

  Hmm.

• 14:56Speaker 01

  So they're earning emissions from the network. So just like Bitcoin miners.

• 14:59Jason Calacanis?

  Sure.

• 14:59Speaker 01

  Earn tau, subnet miners.

• 15:01Jason Calacanis?

  Got it.

• 15:02Speaker 01

  Tau in the, in this system.

• 15:03Jason Calacanis?

  Who decides who can have a subnet? This is always really interesting to me is governance. So let's pause for a second here. I think we can all follow along. You could start essentially a project, AKA a company. Um, now would Targon also be a company in a way?

• 15:19Speaker 01

  Targon is a company, not all of them are. Some, some of them are not companies, some of them are.

• 15:23Jason Calacanis?

  So Targon is a company. They put this up. They are making tau by providing this resource to people who want it. Cloud computing resources on the network. And there are 33 of these projects currently.

• 15:37Speaker 01

  There's a hundred.

• 15:37Jason Calacanis?

  Is a hundred.

• 15:38Speaker 01

  A hundred.

• 15:39Jason Calacanis?

  Is there a limit to the number of projects?

• 15:40Speaker 01

  Uh, there is not. Uh, so you asked, how, how do you do a subnet?

• 15:44Jason Calacanis?

  Yeah, governance wise.

• 15:45Speaker 01

  You stake tau. Anybody can start a subnet for any reason, right? So you stake, you stake tau, you define your subnet.

• 15:51Jason Calacanis?

  Define what staking tau means. You know, when somebody's not in crypto, the, the term stake means you buy it or you put it up for people to earn.

• 15:58Speaker 01

  You basically, you, you, you, you put it in a suspended state. So it's like an escrow, right? So you take your tau, you have to have a certain amount of it. You, you give it to the chain. The chain has a process for doing this. The chain locks it up and says, okay, great. I've got it. And you can't have it back. Uh, until you, you know, unless there's some time in the future where you want to, you know, get rid of your subnet. And I'm not sure the process is for that.

• 16:17Jason Calacanis?

  Got it.

• 16:17Speaker 01

  But you can get it back.

• 16:19Jason Calacanis?

  So they're asking you to make a commitment.

• 16:20Speaker 01

  Yes.

• 16:21Jason Calacanis?

  In tau. What's the commitment level ballpark? Is it $10,000? Is it a million dollars to join the network?

• 16:27Speaker 01

  It's 400 tau right now.

• 16:29Jason Calacanis?

  Got it.

• 16:29Speaker 01

  And that, and that, and tau is worth about 377 or so dollars.

• 16:33Jason Calacanis?

  Got it.

• 16:34Speaker 01

  Per coin at the moment.

• 16:35Jason Calacanis?

  So maybe it's a hundred grand and change to put up one of them. Okay. So we're in the very early days of this project.

• 16:40Speaker 01

  Yeah.

• 16:41Jason Calacanis?

  What's like the second most interesting use case? You have obviously AI clouds. What else is in there? What else do you got?

• 16:48Speaker 01

  Yes, there's ready AI, which is a subnet version of scale.ai.

• 16:52Jason Calacanis?

  Got it.

• 16:52Speaker 01

  11 billion dollar company. Uh, what scale did was they, um, they basically created annotated data. You know, when you feed data to an AI. AI, it's better if it's given context and it's annotated in some way by humans. Right. But you have to do that at scale. It takes a lot of humans. So scale that AI had a lot of humans around the world, paying them to annotate data, which was then sold to AI companies to train their AIs.

• 17:16Jason Calacanis?

  Yes, we know this company. I think actually Alex is scale AI in our twist 500.

• 17:20Speaker 02

  It absolutely is.

• 17:22Jason Calacanis?

  We talked about it at some point. Yeah. So annotating data, doing reinforcement learning. This is something Google was doing a long time ago. You may have heard of. What's the Amazon project? Mechanical Turk? Mechanical Turk was another project where they would say, hey, we're going to show you an image. Tag it with three things and you'd be like, okay, that is. A bottle with orange liquid in it with a, you know, red cap. And it's orange juice and it's 190 calories, whatever. And in the background is a plastic cup and iPhone. And then they would have somebody else do the same task, look for which tags they got in common. And then that would be how Google would. Know that there's a smiling face in an image. It wasn't that they were reading the image for a smiling face. It was that it was tagged.

• 18:08Jason Calacanis?

  Then the AI and the machine learning learned what a smile is versus a frown. Okay. We all know that history. So they're created a tower instance for people to participate in the tagging and. Learning. So I guess I could go in there as an individual with no job. But more time on my hand, or maybe I'm in Manila or a developing country. Frontier market and I could just. Get jobs on the tower network.

• 18:31Speaker 01

  Yes, but there's also, but what ready AI is focused on is actually having AI do the tagging for training the data for.

• 18:38Jason Calacanis?

  Got it. Okay. So even better. Yeah.

• 18:40Speaker 01

  And, and, um, you know, the, the CEO is, is in, is CV is amazing. These are very serious people who are building subnets.

• 18:47Jason Calacanis?

  Got it.

• 18:47Speaker 01

  The guy who, uh, who, uh, built and sold AdWords to Google is part of ready AI.

• 18:53Jason Calacanis?

  Gil.

• 18:53Speaker 01

  So again, yes, Elbaz.

• 18:55Jason Calacanis?

  Yeah, Gil Elbaz has been on the program. We know Gil. This may or may not be the next Bitcoin. You, by the way, have your own podcast about this topic. You can maybe tell everybody about your podcast if they want to learn more and.

• 19:06Speaker 01

  Yeah, sure. Uh, my podcast is called Hash Rate and I have done about 110 episodes. Today it's about crypto. It's about crypto, but I added AI things in here and there.

• 19:17Jason Calacanis?

  Got it.

• 19:18Speaker 01

  I've done about thirty episodes on Bittensor and Tau.

• 19:21Jason Calacanis?

  Wow.

• 19:22Speaker 01

  Which has spanned over the last, you know, year, year and a half as I became more and more interested in this. You know, I've been looking for, you know, what is the next big thing, right? Like what's going to be the next Ethereum? You know, next Solana. And I looked at a lot of things that I, you know, I did a lot of deep dives that went nowhere, right? Or I came up and said, I'm not sure. This is the first thing that I've seen since Ethereum. Where I feel like I'm seeing, you know, the third great coin, right?

• 19:47Jason Calacanis?

  Got it.

• 19:47Speaker 01

  Alongside Bitcoin and Ethereum. So I

• 19:49Jason Calacanis?

  Got it.

• 19:49Speaker 01

  That's my opinion.

• 19:50Jason Calacanis?

  And you're an investor in crypto projects. You're early in Bitcoin. You first bought Bitcoin when it was at what dollar amount?

• 19:57Speaker 01

  It was two fifty when I bought my first one.

• 19:59Jason Calacanis?

  Two hundred and fifty thousand.

• 20:00Speaker 01

  Yeah, it was on Mt. Gox.

• 20:01Jason Calacanis?

  You're stuck.

• 20:02Speaker 01

  Yeah.

• 20:02Jason Calacanis?

  Two hundred and fifty dollars.

• 20:03Speaker 01

  Two hundred and fifty dollars.

• 20:04Jason Calacanis?

  Okay, wow, incredible. All right, Alex, any questions from you for Mark about this? All right, founders, let's talk about your website, huh? It might be a little bit of a sensitive subject. You might be a little embarrassed about it. Let's fix that right now. If you're launching something new, give your brand the refresh it deserves. You're working so hard on your company and your website looks terrible. Do what I do, use Squarespace. It's the all-in-one platform to make a stunning professional website. And it's ridiculously easy to use. It's going to work for everything. If you're selling products, it's got all that e-commerce built in. If you're selling services, it works perfectly. And they have a new AI product called Blueprint. Want more control? Well, of course, you can choose one of the award-winning templates.

• 20:49Jason Calacanis?

  And use the intuitive drag and drop tools to make it your own. Easy peasy. Squarespace equals the most functional and beautiful website on planet Earth. Go ahead, squarespace.com/twist to get a free trial. And when you're ready to launch, go to squarespace.com/twist to get ten percent off your first website or domain purchase. That's squarespace.com/twist.

• 21:10Speaker 04

  Absolutely. First of all, Jason Gil Elbaz is the founder of Common Crawl, not Open Crawl.

• 21:16Jason Calacanis?

  Common.

• 21:16Speaker 04

  But you were, you were very, very close there. My question is, is pretty simple. I understand the major concept here, you know, crypto attracts compute, AI needs compute, put the two together, huzzah. I'm curious why there are sub tokens that are more than just Tau. So when we look at the market cap of these projects, it seems that you said they had different tokens to themselves. Why complicate the overall economics here and not just stay true to just the Tau token, which is capped and so forth?

• 21:41Speaker 01

  Yeah, great question. The reason why is because it's basically to figure out where the emissions should be directed. So it's to create a market and competition between the subnets. So which projects, because before there was a lot of, there were some subnets that were just extractive, right? They were just creating subnets to collect tau, but not really contributing much to the network, right? This forces a marketplace to, when you buy the, when you buy the subnet tokens, the market cap of the subnet goes up, which determines how much, how much emissions they get.

• 22:16Speaker 04

  How much of the tau emissions they get?

• 22:18Speaker 01

  Correct. So Chutes is, has the biggest market cap. So they get the lion's share of the tau emissions from the chain. It's 17% at the moment. That's what that number meant.

• 22:28Speaker 04

  So the market cap on a per subnet basis is effectively a voting mechanism to say, hey, this product is the most useful and therefore it should get the largest piece of the next tau emission.

• 22:37Speaker 01

  Correct. Because the tau emissions are a subsidy for, you know, all these projects, right? Why can Chutes give you 85% savings? Because it's being subsidized by all the tau that's being kicked off by the chain.

• 22:47Speaker 04

  Mark, can I tell you what I think about that? I think it's too clever by half. I think there's gotta be a simpler way to hand out the tau than to have 85 or I guess 100 different sub, sub economies to this. But I have to say, I think it's a pretty cool idea. And I'm, I think if I was a startup, Jason, and I could get 85% cheaper compute, it'd be hard to not look at that in the eye and go, well, I'm going to try it. Because if I could save, you know, that much of my total cloud bill.

• 23:12Jason Calacanis?

  I'm gonna, I'm gonna take the other side of it. I think it's like, it is too clever in the same way the United States of America was too clever. People are like, what are you doing? Why do all these like states have these state rights? And how are you going to divvy up rights between the states? And, you know, it turns out like, sometimes if you do things that are not efficient, then you gain some other qualities like resilience or competition. And so one of the great things about the United States is like, we have different taxes in each state. Like, that's actually kind of interesting. Or we have different rights. Like, gosh, I don't want to bring up reproductive rights, but, or gun rights, but like, people can pick their state based on, hey, maybe I prefer this

• 23:53Jason Calacanis?

  level of freedom, or this level of control, or this dystopian thing, or, you know, and everybody's definition is different. It's a very fascinating project, and we're going to keep our eye on it. We have some other thing. Oh, a lot of any questions for Mark about the project that we've been talking about?

• 24:09Speaker 02

  It's a little, it's a little over, it's a little over my head, but I guess the, the one thing I am curious about is, are, are, do you guys see this as a rival to Bitcoin? Like ultimately, we want everybody to use Tau as their store of value, not Bitcoin? Or is this like, they're both going to exist long-term and it's just which, which project you find more intriguing?

• 24:31Speaker 01

  That's a very interesting and very debatable question. Uh, yeah. So, so Barry Silbert, uh, right? Who is, who became a billionaire, uh, investing very early in Bitcoin after hearing about it on, on this show.

• 24:42Jason Calacanis?

  The famous episode I did in 2011.

• 24:45Speaker 01

  2011.

• 24:45Jason Calacanis?

  Yeah, about Bitcoin.

• 24:46Speaker 01

  Yeah. So he-

• 24:47Jason Calacanis?

  Should have backed up the truck. Yeah.

• 24:48Speaker 01

  He is now, as all in as he was on that back then, he is equally all in on BitTensor now. And he has a, he has several companies, one of which is Yuma, uh, which is basically a BitTensor Y combinator. He's basically, you know, firing these things up and sending them out like companies, right? So, and he has said several times that he thinks that BitTensor may become more valuable than Bitcoin. Not because there's anything wrong with Bitcoin.

• 25:13Jason Calacanis?

  Right.

• 25:13Speaker 01

  But because BitTensor has Bitcoin-like qualities and it's extremely useful for real things.

• 25:19Jason Calacanis?

  Well, this has always been my problem with crypto in general. You know, you and I have talked about this, Mark, many times personally, where, you know, in the early days of crypto, I met with a hundred projects and we actually tracked it. And in 95, 96, 97 of them, it was unqualified people.

• 25:37Speaker 01

  Yeah.

• 25:38Jason Calacanis?

  Building outlandish things with spelling errors in their white papers. And I was like, well, I'm going to, I'm going to compare this to like the startups I'm seeing in Silicon Valley and abroad and everywhere else. And they just didn't make any sense. And there were two or three, I was like, these are really smart guys. There's less typos and they're actually making something that might work, but like this idea that a decentralized Uber or a decentralized Google or a decentralized Twitter is gonna, or decentralized Facebook is gonna beat all those things. I was like, that's not- Possible or not probable, but probably more not possible because if you're going to stay on somebody's couch, like you probably want a company with a board and insurance to be

• 26:21Jason Calacanis?

  responsible for that, right? Like, that's like way too high stakes for people to want to use. And listen, maybe I'll turn out to be wrong. But what I like about this project you've identified is it seems like there's real entrepreneurs there, which is great. And it seems like they're building actual products and services with utility from, in some cases, companies that exist in the real world that have a board of directors, that have a domiciled location. And that was always the, the, the red screaming red flags in crypto. This company's not domiciled anywhere. There's some nonprofit foundation in Panama.

• 26:58Speaker 01

  But most of it, but I mean, yes, I totally get what you're saying.

• 27:01Jason Calacanis?

  Yeah.

• 27:01Speaker 01

  The flip side of that is, is that that environment was created by Gary Gensler, who forced these companies out of the United States. There was no other way to operate.

• 27:09Jason Calacanis?

  Sure.

• 27:10Speaker 01

  Right? So.

• 27:10Jason Calacanis?

  But operating in the shadows also gave them the advantage of just absconding with the money.

• 27:15Speaker 01

  And that is also true. There was a lot of bad stuff. I mean, I'm not denying that at all.

• 27:18Jason Calacanis?

  So what do you think now about what Trump has done so far with crypto? You know, when you saw the meme coin, uh, stuff like that obviously seemed like they were writing SEC code around, you know, the Trump meme coin to kind of maybe, you know, not to basically retroactively give Trump a pass. Am I right about that one?

• 27:39Speaker 01

  I, I don't, I actually disagree with you on that.

• 27:42Jason Calacanis?

  Okay.

• 27:42Speaker 01

  But I do agree with you that what Trump did with his meme coin was crass. It was, it was, it was not something that we in crypto liked. All of our stomachs all fell because we, because we don't like, the, the ones of us who have been in this for a long time and who believe in, in it, you know, we, we love Ethereum, we love DeFi.

• 27:58Jason Calacanis?

  Yeah.

• 27:58Speaker 01

  Decentralized finance. Um, we love Bitcoin. We think this world should exist. We think Gary Gensler should not have been so, um, predatory on the environment. And we fought hard, right? And, and, and suffered for a long time in some cases, right? Some, some people went to jail.

• 28:13Jason Calacanis?

  So it felt like it's a grift.

• 28:14Speaker 01

  Yes. And what Trump did, did what he did, we all just, it just felt like a gut punch. It didn't feel good at all. It felt like betrayal, right? It didn't feel good.

• 28:22Jason Calacanis?

  What about stable coins? There's like a stable coin act. This is all going very low under the radar while we talk about sending people to C-COT or the tariff war. It seems like Howard Lutnick's got a deep relationship with Tether or Cantor Fitzgerald does. And there's this new stablecoin act coming out. Is there like a chance that like Tether, which is used for, according to 60 Minutes and Congress and all those hearings, used for really dark stuff in the world? Terrorists, uh, human traffickers allegedly, uh, are using it or maybe confirmed and they've been banned in only states. Like, is that gonna become a legit thing?

• 29:01Speaker 01

  Yeah, I think it will. I mean, I, and just to, you know, back up.

• 29:04Jason Calacanis?

  Yeah.

• 29:04Speaker 01

  Yes, Tether has been used for those, I'm sure has been used for crimes.

• 29:07Jason Calacanis?

  Sure.

• 29:08Speaker 01

  So is, you know, United States dollars in briefcases, right?

• 29:10Jason Calacanis?

  Of course, yeah.

• 29:11Speaker 01

  Uh, by a much larger margin, right?

• 29:12Jason Calacanis?

  Yeah. But you think so by a much more large in today? Do you think people are using, if we were to look at it, that historically is correct because Tether hasn't existed, but today, like the average criminal?

• 29:22Speaker 01

  Yeah, I actually looked at, I don't remember the stats offhand, but it was, it was something like 5% of all cash, uh, is for illicit, uh, business.

• 29:30Jason Calacanis?

  Okay, yeah.

• 29:30Speaker 01

  Tether is mostly used for, you know, to basically store your crypto in a wallet so you don't have to deal with a bank, right? Like with Mt. Gox, before Tether, you had to wire money to Japan.

• 29:40Jason Calacanis?

  Right.

• 29:40Speaker 01

  Right, and that took like a week and maybe it got there, maybe it didn't.

• 29:43Jason Calacanis?

  Yes.

• 29:43Speaker 01

  It was hard. And, you know, with Tether, you're just like, oh, blip, my tether's over there now and I can buy the coins.

• 29:48Speaker 02

  By most, uh, guesses, uh, cryptocurrency is being used for between 40 and 50 billion dollars of illicit transactions per year. That would be a magnitude less than US dollars.

• 30:02Speaker 05

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• 30:46Speaker 05

  for networking, and that's some serious savings.

• 30:48Jason Calacanis?

  Thousands of businesses have already upgraded to OCI, including Vodafone, Thomson Reuters, and Suno AI, who we had in the pod last year. So here's your call to action. Oracle is offering to cut your current cloud bill in half if you move to OCI for new US customers with a minimum financial commitment. But act fast. This offer ends March 31st. So see if your company qualifies at oracle.com/twist. That's oracle.com/twist. What else do we have on the docket today?

• 31:17Speaker 04

  I want to stay on the AI training compute front, Jason. There was some big news from Meta this week at their first ever LamaCon, which was an event dedicated to their open source AI models. They announced that they're going to partner with Groq with a queue and Cerberus, both Twis 500 companies, to offer essentially their models as a hosted service. And when two of our Twis 500 companies get name checked at the same time, it's pretty exciting. Both companies are shouting about this. They're very proud of it. And I think it just goes to show that, one, Meta needs an AI business model, Jason, but also, two, that it's not all going to pool in Nvidia's pockets long term. Now, I don't know how this will stack up against what they're working on with BitTensor, but certainly there are a lot of people out

• 31:59Speaker 04

  there who want traditional AI inference compute. And so it's cool to see two companies that are still private, still smaller, get tapped. And I do think this should help Cerberus go public, Jason?

• 32:10Jason Calacanis?

  Okay, this is super interesting. Obviously Groq, G R O Q, is not Groq from Elon. It's Groq from Chamath, and it's tensor chips. These are inference chips. So Meta does not currently have a cloud computing offering for founders, right? They make their own, obviously, data centers, but they're not in competition with AWS. If what I'm hearing is correct here, Meta is saying we're going to take Lama, their open source project, and they're going to have it hosted. With compute from Grok and Cerebrus. Is Cerebrus a data center company or a chip company?

• 32:52Speaker 04

  Cerebrus is a chip company. They are big with G42 and they filed to go public, but remember their IPO was so single company revenue that it was a little dicey.

• 33:01Jason Calacanis?

  So now, if that does happen, does this mean, is the actual story here that Meta is going to compete with AWS?

• 33:09Speaker 04

  To a degree. I mean, you can host Llama models around, you know, you can run Llama, I think, on AWS or on Azure or GCP. But now they're going to offer their own kind of homegrown solution, if you will, with these partners. So Meta is now, in a way, competing with everyone else. Yes.

• 33:25Jason Calacanis?

  In cloud computing, it's a slice of cloud computing. So then, if they do just that slice, they're probably going to be obligated to offer some storage or some transit. This could be the start of them creating an AWS competitor. That's actually the real news here. Is this could be their wedge. Now, they have a great excuse, Mark. They could just say, well, we, we want to have the freshest, best version of Llama available because we want the project to win. Maybe they offer it at discount. Maybe they offer it as a loss. They could price dump this. What do you think here, Mark? What, Alex, what?

• 33:58Speaker 04

  Sorry, I don't think, sorry, I don't disagree, but then probably not, Jason, because the information reported that Meta had actually reached out to Alphabet and Microsoft. Should I get them to subsidize the money they were putting into Llama? So I doubt they can actually take more of a loss here. I think this is a way to recoup some of their investment, not to further subsidize their market share.

• 34:17Jason Calacanis?

  Well, I mean, if you want your model to win and you've got tons of cash laying around, you could buy back your stock. You could build infrastructure and take a loss on it and they could lose. I mean, they're losing what 10 billion a year on this.

• 34:32Speaker 04

  On VR, yeah.

• 34:33Jason Calacanis?

  On VR. I mean, they could lose 20 billion a year on this. Make it free. The big loser here, Mark, might be OpenAI. What if this is available for less than OpenAI charges? For their compute, what are your thoughts here of Meta's open source? Sort of strategy and standing up hosted compute?

• 34:54Speaker 01

  Yeah, I mean, this is exactly what Shits and Targon do, right? So they take these open source models and stand them up and make them available for quite a bit less than you can get on AWS.

• 35:02Speaker 04

  Yeah.

• 35:03Speaker 01

  So, you know, I think the overall trend is that AI goes towards zero in terms of costs, right?

• 35:09Speaker 04

  Wow.

• 35:10Speaker 01

  And I think that through various, you know, through various mechanisms and various interacting market forces, some of them from BitTensor, some of them from, you know, the open source community, which is very dangerous for OpenAI, right? Like they're, they're incinerating hundreds of billions a year.

• 35:26Speaker 04

  Yeah.

• 35:26Speaker 01

  Right? So how, how is that sustainable in the face of that?

• 35:29Speaker 04

  Single digit billions a year.

• 35:30Speaker 01

  Sorry, single digit.

• 35:31Jason Calacanis?

  Single digit, the company's worth hundreds of billions. Yeah, this could clean up. Um, all right, let's keep moving here. I want to talk a little bit about how much code is being written by AI. Alex, uh, there's some news from Cursor and Lightrun and from Sundar and from Satya.

• 35:46Speaker 04

  Yeah.

• 35:47Jason Calacanis?

  Uh, on exactly how much code is being written by AI now. This, this is a trend that I think we saw coming, but maybe not at the velocity it's coming. I don't know. Cue it up here.

• 36:01Speaker 04

  So I am very impressed by a couple of numbers. So during Google's earnings report, Alphabet's earnings report, Alphabet CEO Sundar Pichai said that right now over 30% of code that is committed from the company now comes from an AI source. Also at LlamaCon, Satya Nadella, CEO of Microsoft, said that right now 20 to 30% of the code that the company puts out is written by AI. Now, this is pretty big news. I think no one thought we'd get here this fast, but Cursor is very, very proud of how much of its, uh, how much of, how much code it's putting out. So the CEO, um, said over on X that Cursor today writes about a billion lines of accepted code per day, and he put that up against a global number of several billion lines per day. People were a little skeptical of that figure, but it just goes to show how fast this is moving.

• 36:46Speaker 04

  Jason, I think once we see companies like Lightrun, which we talked about, I think on Monday, really kind of turn the AI snake back on its own tail and begin to have AI, improve AI-generated code, we're going to get to 80, 90% within probably 18 months.

• 37:00Jason Calacanis?

  Yeah, this is pretty amazing and I think it's going to be great for humanity because the bottleneck for startups has been a moving target over time. When startups and PC revolution, server revolution, there were hardware constraints. We had an incredible constraint of the memory of the computer. We had constraints of the storage of the computer. You know, 15 floppy disks to run it, that everything was too slow, it was too hard to even load up a word processor. You know, if you saved a large file, it was even like the quality of the file get corrupted. Like we had really crazy issues. Then we went to another phase where the bandwidth was the issue. Hey, how do we move this stuff around?

• 37:44Jason Calacanis?

  Then it became standing up servers. So if you were starting a company in the late 90s and the web 1.0 era when Mark and I started, you had to raise three, four, five million. You had to take 18 months, 24 months to build your product and stand up your data center. Now you can build your startup in three weeks, use somebody else's data center. So what has been the blocker the last 10 years, last 20 years? The blocker has been developers. I can't find a developer was what we heard for the last 10 years from founders. I think what we're going to hear now is because you don't need five developers to get your project out the door, you need one and that one is getting 30% faster a year. Maybe your startup ultimately, instead of needing 30 developers, needs five.

• 38:28Jason Calacanis?

  Maybe in order to start, you need one developer, not five, right? You know, like this is a magnitude change and I think it's going to mean we're going to make every piece of software that hasn't been made yet will get made. What else we got on the docket?

• 38:42Speaker 04

  I want to run something by you, Jason. There's a venture capitalist, Charles Hudson from precursor.

• 38:47Jason Calacanis?

  I know Charles, he's great.

• 38:48Speaker 04

  Yeah, everyone knows Charles. He did a post over on Substack, but he says that he's noticed that the combination of AI-generated cold outreach to VCs is pushing people back towards human-driven warm intros and referrals. This was very interesting to me. I can't imagine handing off my VC outreach to AI, but I'm curious how founders can take advantage of this to win more. 2025.

• 39:11Jason Calacanis?

  I've always believed it's a numbers game. You know, in terms of raising capital, especially at the early days, because you are selling the promise. Right. But even though it's a numbers game, because there's so many, we just talked about there's 400 funds formed a year. So there's 1,200 funds active at any one point in time, maybe 1,500 because they tend to have a four year life cycle of primary investing. So let's say there's 1,500 firm funds. They probably have six people working at each, you know, you're getting to five to 10,000 active investors with check writing ability. Somewhere in that group are 10% of them will want to invest in your company.

• 39:50Jason Calacanis?

  5% of them. It's a numbers game in that if it was 10%, you might be talking about 500 qualified targets, 1,000 qualified targets. Then you have to look at, okay, they do invest in my vertical. I'm in marketplaces. I'm in military. Okay, of those, which ones invest at my stage? Seed rounds, pre-seed, series A, series B. Now you have to parse that list and then you have to start a real sales process of going to them. The problem is because of databases like Crunchbase and other ones that exist, sometimes the founder will get overzealous and they will send too many emails. And that upsets people and that's where you get VCs complaining like, I am not doing medical devices.

• 40:35Jason Calacanis?

  I don't invest in pizzerias. So what you want to do is make a nice big list. And then you want to really understand on that list, have they invested in companies adjacent to yours? Do they only invest in certain regions? So it is a numbers game, but you have to also curate that number. So it's very easy to get to a list of, I would say you should have, you know, in your seed round, there should be probably at the top level, 200 firms that you've identified would actually invest in your company. And then you should see of those 200, how many can you get a warm intro to? And then how many do you need to do a cold intro to? And then you should be very thoughtful. When you send that email, instead of trying to do it as quick as possible, go slow.

• 41:19Jason Calacanis?

  Which is if you were to meet somebody at a party, you know, and you were a real estate broker, you wouldn't be like, are you selling your home or buying a new home anytime soon? You'd be like, oh, where do your kids go to school? Oh yeah, no, I'm over here. And you kind of warm up the lead. So you want to warm up the leads?

• 41:36Speaker 02

  We have a, we have a great video from Alexis Ohanian about the perfect cold email.

• 41:41Jason Calacanis?

  Here we go.

• 41:41Speaker 02

  If you want to just throw to that real quick, uh, it's on the from the feed section. Uh, this was shared a few weeks ago. I've had it in the docket in case we ever got to talk about it. This is such a great example. It's only one minute of video and I feel like he lays out exactly how to write the best cold email you've ever heard.

• 41:59Speaker 06

  Tips for cold emailing. I love a good cold email that is to the point.

• 42:05Speaker 06

  It is no longer than like three or four sentences. It very clearly upfront states who you are and why you're real. Basically what value you have to provide to the person that you're reaching out to, and then makes a very specific request.

• 42:18Speaker 06

  And says, thanks. That's it. I mean, upfront, you want to demonstrate value. Why am I going to spend another 30 seconds reading this email? And then immediately follow up with the request and ideally be offering first instead of asking. But if you are asking for something first, there better be a good why. The best cold emails are deeply, deeply empathetic to the person you're emailing. You've taken the time to understand who they are, what they're about, what they like. One of the easiest ways to mess it up is by not doing that work, getting their name wrong.

• 42:48Speaker 06

  Putting 20 paragraphs into an email, keep it tidy, chemistry value upfront, make your clear ask. That's it. Good luck. Good exercise. Get used to the rejection too.

• 42:55Jason Calacanis?

  Yeah, he's, he's nailing it there. You gotta be, you know, concise, to the point. Make sure you don't spell the person's name wrong.

• 43:02Speaker 02

  Yeah.

• 43:02Jason Calacanis?

  I always tell people like, gosh, if you want, it's so easy with a VC who is publicly active to just say, I saw you on this week in startups, or you, you had this tweet. It really resonated with me because I'm building something inspired by that tweet. Boom. And then you're, all of a sudden you've created some commonality, some, some common ground. And then you get to the ask, we're raising our seed round. I also think a chart, if you have, I like leading with what's strong. So a chart is the strongest thing in the world for VCs because we like up and to the right. We like things that are going to grow. So we've been, we've had our product in market for seven weeks. We've grown on average 18% week over week. We're doubling every three to four weeks.

• 43:47Jason Calacanis?

  And, you know, here's a link to our app and here's a link to our deck. Would love to, if you're interested, would love to do a quick follow-up meeting. I always added something extra, which was happy to meet anytime. I know you're in Palo Alto, anytime, you know, Saturday, Sunday, 7:00 a.m. to midnight. Anytime I can meet you for 15 minutes, happy to go where you are. So you're actually even putting out there like you're a dogged, rabid person who will meet anytime, anywhere if you want to do an introductory call. And yeah, I also love sometimes people ask me a question. What do you think of this design?

• 44:23Speaker 01

  Yeah.

• 44:23Jason Calacanis?

  That kind of like, oh, okay, yeah, maybe I'll give you actually some feedback. Go ahead, Mark.

• 44:28Speaker 01

  There's something that you used to say at Mahalo a lot that I, that really made me focus a lot more on this. And, you know, the video talks about clarity, right? Getting, getting to the point.

• 44:37Jason Calacanis?

  Yeah.

• 44:38Speaker 01

  You used to say to people, you know, answer the question. You'd ask someone a question, they wouldn't answer the question. They'd like give you 50 paragraphs.

• 44:44Jason Calacanis?

  Literally, that's my line.

• 44:46Speaker 02

  All the context. You always want to give you context.

• 44:48Speaker 01

  I never really thought about how often people don't answer the question and how rare clarity is. And you kind of, you know, tuned my brain to that a lot more than it had been.

• 44:59Jason Calacanis?

  All right, we have an office hours. We're going to get to our office hours now.

• 45:03Speaker 02

  Let's do it.

• 45:03Speaker 04

  We are. Okay. All right, so the company in question is Layer Next. The co-founder and CEO is Bhutika Madam. Now Layer Next, if you don't know, is taking the world of business intelligence to the next level. Using AI to get all that structured and unstructured corporate data. That way you can figure out what to do next, Jason, and not just look entirely in the rearview mirror. Let's talk to Layer Next.

• 45:23Jason Calacanis?

  All right, how are you, sir? Nice to see you.

• 45:25Speaker 05

  How are you doing?

• 45:26Jason Calacanis?

  Tell us what's going on with Layer Next. What, what's challenging? What are the wins? What are the fails?

• 45:31Speaker 05

  Layer Next is a strategic business intelligence platform. And we are helping CFO to generate strategies to grow their business or increase efficiencies. The challenge is right now with the business onboarding, because every customer has a different data set. We are especially going for this mid-market companies in the manufacturing and transportation.

• 46:00Speaker 04

  The problem is their data is not AI ready. So we have to do a lot of upfront work in order to make our system work with their data. That's the challenge.

• 46:12Jason Calacanis?

  So you have AI that goes in, looks at a CFO's data from their company, and then gives them some strategic intelligence. An example of intelligence or strategy that you've given to a CFO? What would you say is the best example of a wow moment a CFO had when you deployed LayerNext at their company and against their data sets? What was the biggest wow moment?

• 46:38Speaker 04

  So we had a one customer. He want to understand whether we want to hire more salespeople or not. Okay, yeah. So then we analyze how much salespeople they have today, how much sales they're making today, and also the cash flow. So then AI generating strategies. If you add the one sales agent, this could be the revenue. Then how much is your margin would be? Those are the wow, yeah.

• 47:09Jason Calacanis?

  So this is a great idea, but it's hard. And so some ideas are hard. What's hard about this idea? Well, what one CFO wants to solve might be very different than another CFO. If you don't have salespeople, well, and you have retailers, you have a different task to do here. And as you mentioned, there's different stages. Some companies don't have a CFO. Then companies have an outsourced CFO. Then you hire your first CFO. Then you have a public market CFO. You know, you, you have a real range of different stages of companies. You have different goals. And then also you're trying to tell them things, actionable items, that maybe they're not even aware. So that would be like doing a blood test with superpower.

• 47:52Jason Calacanis?

  And it comes back to you and says, hey, and you're doing superpower. Get your blood drawn. You just signed up. Maybe they say to you, oh, you're vitamin D. Now, you would never say to them, I need to take a vitamin D test. So they take all the tests. So this business, you probably do need vitamin D because you're not outside enough. This is your problem. You have.

• 48:15Jason Calacanis?

  Disparate systems and you have insights you can give them that they may not even know they need. So the, it's the value of this product is hard for them to know. And so what you probably have to do is figure out what is the most, which group of CFOs are going to have the most wow moments and get the most value from your product. If it's people with sales teams, you'll know that because Salesforce exists, HubSpot exists. If it's people with retailers, maybe they use SAP, who knows? Maybe they use NetSuite. So I think you have to plan to flag early on, define an ideal customer profile, narrow the focus

• 48:54Jason Calacanis?

  down to, hey, you know, this product, Snowflake, NetSuite is the industry standard, these people have money to spend and we can help them. So Ikigai, do you know that? Ikigai. Ikigai? Yeah. Pull up the Ikigai chart. I'm going to show you something that might blow your mind. Ikigai, have you heard of this before? I have no idea. Okay. Ikigai is a Japanese philosophy. What are you good at? What does the world need? What are people willing to pay for? And there's other circles. People have made all kinds of different spins on it, but somebody's going to pull up the Ikigai. I got it. Chart. Okay, here we go. So we'll look at this for a second and I just want you to slow down. We're not talking about your startup here. We're talking about life. So

• 49:39Jason Calacanis?

  we have what you love. Okay. You love data, don't you? Okay. What the world needs, analysis of that data to get insights. What are you good at? You're good at making that software and will people pay for it, right? Somewhere in here is your Ikigai of your startup. What software the world uses for data, it's going to be HubSpot, it's going to be NetSuite, et cetera. What do they love? They love saving money. They love making money. What are you good at? You're good at telling them how to save money, how to make money, how to avoid maybe one of your value propositions, how to avoid tax issues in the future, or how to save money on taxes. It could be all of those things. And would people pay for it?

• 50:23Jason Calacanis?

  Well, there'll be overlapping circles here. So Ikigai, I K I G A I, is a way for a human being to look at the world. And say, what should I do with my life? What's my purpose? Ikigai for startups is a new concept that I'm just debuting here right now for the first time, but it came to my mind, which is Ikigai for startups is who are these customers? What do they covet? And what can you do with them? Right? So what would you say for that? For that company that got the wow moment and it provided great value for them? Do you think they'd be willing to pay for that? Or is that like a one time insight? Or is that a reoccurring insight? I'm curious.

• 51:06Speaker 04

  It's a reoccurring. Yeah.

• 51:08Jason Calacanis?

  Because. Perfect.

• 51:08Speaker 04

  Yeah.

• 51:09Jason Calacanis?

  Because you have to monitor the salespeople. Sure.

• 51:11Speaker 04

  Yeah.

• 51:11Jason Calacanis?

  So you found something. What data? Where was the data held that you were able to make this insight? Where did you get the data from?

• 51:19Speaker 04

  They have the sales force. They have the sales force and they pump in the data to the data warehouse every night.

• 51:24Jason Calacanis?

  Okay. So they have sales forces where the data resides. Did you cross reference it with any other data?

• 51:29Speaker 04

  They have the county system. It's a legacy county system.

• 51:33Jason Calacanis?

  Oh, so you had the legacy accounting system. Do you know what name of that is? It's not QuickBooks or something or?

• 51:39Speaker 04

  Yeah. For us, it's a transparent. I guess Oracle and it's sort of something.

• 51:42Jason Calacanis?

  Perfect.

• 51:43Speaker 04

  Data coming direct to the data warehouse and we access the data from the warehouse.

• 51:46Jason Calacanis?

  So while you're figuring out your ideal customer profile, you're going to have to figure out how many people have sales force and this accounting thing and maybe start with that group. Now you have identified a subset. Maybe in the future, you want to go in and take every piece of data from every system and give this magical, you know, here's how to run your business. Like it's almost like a shadow CEO, a shadow CFO advising people. It's like a clone, right? You've got this like perfect clone that's out there working as an agent 24 hours a day, trying to figure this stuff out. But maybe we start and say, you know what? There's enough people with sales teams and sales data and customer engagement data that we could just go in and tackle that first.

• 52:31Jason Calacanis?

  So you have a feature you can say to people. Hey, you got Salesforce, you have over 50 salespeople. We can really help you figure out how to make decisions in your sales group. Then you say to the marketing group, hey, we know your CAC. We know where you're spending money. We can help you spend money more efficiently to then get it into the sales group. Then you say, okay, now we're going to work with our accounts and our tax people. We can tell you how to save money internationally, figuring out your tax status and where to put these sales, et cetera. But you start with one, then you build the adjacencies. Does that make sense?

• 53:07Speaker 05

  I think it makes sense, yeah. So we get a lot of custom. Some people, it's the early stage of the data journey, data maturity journey. So we are in the waiting list still. So it makes sense to me.

• 53:20Jason Calacanis?

  Yeah, I mean, the, the good news also is, and most VCs will not say this because they really want you to scale and not build custom software, right? Because custom software is custom and it does, it's not repeatable. But if you did some client engagements where they needed your help with some service-y kind of stuff and it was custom-y and it was bespoke. If that bespoke work gets you a lighthouse customer, I'm going to say, go ahead and do it. If that bespoke custom work for them and consulting, if they're paying for it and it makes your product better and more scalable for the next customer and you own the IP for that stuff,

• 54:01Jason Calacanis?

  I'm going to say, go ahead and do it because this is going to be years of you grinding it out to get this data and normalize it. And if you can make a little bit of money along the way to keep the lights on and have to raise less money from VCs, that can be good too because you keep more of your equity. Now, a VC would tell you, don't do that. You know, build the platform, we'll give you the money, we get your equity. But it's a way for you to not do it. Mark, you have any thoughts here and advice? But I think you've got enough to go on here. You know, let's try to define that ideal customer profile and then I want you to also bear hug them. Did it ever talk to you about the bear hug strategy?

• 54:38Speaker 05

  Yeah, we, we learned from the. Uh, extended program.

• 54:42Jason Calacanis?

  Got it. Okay. So just for people who are listening, the bear hug strategy is when you're trying to find these lighthouse customers, the one who shine this beacon of light that other customers follow. Oh, you know, we got this company. That's got a lot of salespeople in it. It's uh, or it's IBM and IBM uses Salesforce and IBM's got this glow or it's KPMG. KPMG's got all these salespeople all over the world selling, you know, audits or whatever. And you know, we now have them as our lighthouse customers. So Ernst and Young and, you know, other groups might follow their lead. If you can get one of those and then you can embed yourself at their office. So they have this problem. They got data problems. You say, hey, you know what?

• 55:22Jason Calacanis?

  We want you to be our lighthouse customer. You're super upfront with them. Would it be possible for us to get like a war room, a conference room at your office? And we just come there five days a week, four days a week. We work with your team. We clean up this data. We give you insights and we'll do this consulting arrangement or we'll do it for free. But now you're sitting with them and then other opportunities emerge. And those other opportunities could inform you, like these could be circles you didn't, in your ikigai, didn't anticipate emerging. So. I like the idea of like getting really close to a couple of people who love your product and learning from them.

• 55:58Speaker 02

  And you'd learn so much being embedded in that way. There's things you can't pick up just on a phone call or resume. People don't know about themselves and their own business that you'd pick up being in their face all day.

• 56:08Jason Calacanis?

  If you were Panavision or you were the Red Camera Company or one of these, it would be the equivalent of saying like, I make these incredible cameras. Uh, you're making a movie or a television show. Can we send a couple of technicians to hang out on set with you?

• 56:23Speaker 02

  Yeah.

• 56:23Jason Calacanis?

  And answer any questions you have. And you know, when you keep dropping the thing because we, the handles don't work well and. You know, they keep slipping out of people's hands. We're going to make a grip that doesn't fall out and you know, you, you get, you gain some incredible knowledge. So. Great job and we wish you great success.

• 56:41Speaker 05

  Thank you very much.

• 56:43Jason Calacanis?

  Uh, I mean, maybe we'll do one Reddit rapid response.

• 56:46Speaker 02

  Oh, okay. We got, we got a few of those. We got a few of those. You were hanging out. Uh, so Jason was hanging out on the r/antiwork subreddit.

• 56:53Jason Calacanis?

  Yes, capitalist in the anti-work subreddit.

• 56:57Speaker 02

  Yeah.

• 56:58Speaker 04

  Do you show up and just like, I can imagine your head exploding?

• 57:02Jason Calacanis?

  I have been, we've been working on return to office for our company, you know, and have a certain philosophy. Extremely high performers can be remote. But some jobs need to be in person. So we've been slowly working on this, getting back to in-office and, um, I guess because I was researching ActiveTrack, which is like productivity software and we have to lock all our computers down. I started, I, I think the way I stumbled upon anti-work was people were talking about ActiveTrack in there, which is tracking software that you put on your corporate laptop.

• 57:34Speaker 02

  And it watches everything you do all day.

• 57:36Jason Calacanis?

  Watches everything you do, but it's, it's really for a finance company also to secure your laptop. So if somebody were to...

• 57:41Speaker 02

  Downloading the database, sharing it with people who shouldn't be seeing what's in there.

• 57:45Jason Calacanis?

  So, you know, anyway, people were talking about ActiveTrack on there and I saw this, um, thread and it just resonated with me. So maybe you could queue up the person.

• 57:54Speaker 02

  From user ElectricHorsepower, they're asking, why the big push to return to office? Uh, I get a sense that the majority of domestic employers want everyone to return to office. I understand that leases on buildings need to be maximized, but is there anything other than money that would make a company have all of its employees come back to the office?

• 58:13Jason Calacanis?

  Yeah. So I just thought I would explain to them, what are some of the other reasons that people are actually doing this and the why? And a little bit of my philosophy. So maybe you could just read a little bit of my response. If there's typos or things in there, please feel free. I usually leave my typos in now, like Grammarly tries to correct my typos. I'll clean up egregious ones, but I leave a couple of typos in so people know it's real.

• 58:35Speaker 02

  People know it's not AI, it's you. Uh, so Jason wrote, I wrote a couple of podcasts, All In, This Week at Startups and a venture capital firm, Launch at a University. Over the past year, we started a return to work for everyone but EHPs, extremely high performers, who live outside of Austin. We did it because one, we're in a competitive... space and being in person makes us faster at everything. Two, energy level, intensity and pace is different. Three, after four years of working from home, people had lost their intensity, the culture had disappeared. Four, after starting to meet with founders in person again, it was a huge advantage. Five, on the margin, we had 10 to 20% of folks abusing work from home, uh, which you figured out via active track.

• 59:15Speaker 02

  Uh, great software for teams of high performers because it exposes folks who are phoning it in or abusing the system. Uh, however, that's just one data point important to keep in mind. And finally, creativity, when folks are in creative meetings in person, they bring their A game. But when they're on Zoom, they could get distracted, they could disappear or whatever. Uh, and then you, you, you filled it out with some other important, you know, personal sort of information said happy to do an AMA.

• 59:39Jason Calacanis?

  Yeah. So thoughts on my response?

• 59:41Speaker 02

  I think you're correct. Uh, I actually chimed in and responded to, to this comment myself. And I was, I was very skeptical. I was a, I loved working from home. I thought that was like the dream.

• 59:52Jason Calacanis?

  Yeah.

• 59:52Speaker 02

  Like I can hang out in my PJs all day, just at my computer. I don't have to commute.

• 59:56Jason Calacanis?

  Yes.

• 59:57Speaker 02

  And I, I enjoyed it for a while, but after several years, I think exactly what you said about being distracted, losing some of the intensity and focus. And I'm, I like to work. I don't, you know, I like my job.

• 1:00:09Jason Calacanis?

  For sure. Hard worker.

• 1:00:09Speaker 02

  Yeah. I'm not somebody who's like naturally like, eh, I don't want to do that. I'm going to hang out for an hour. But even I found that after a while, it's very easy to get distracted when you're in your house. When you're never face to face with your coworkers, when everybody is just like a little line of text on your

• 1:00:26Jason Calacanis?

  Yeah.

• 1:00:27Speaker 02

  chat app instead of being in your face, you just lose that personal connection. And when you're in an office with other people, they're your peers and your coworkers. You raise your own game to keep up with all of them.

• 1:00:38Jason Calacanis?

  Yes.

• 1:00:39Speaker 02

  You don't do that when you're at home, you set your own energy level and everybody kind of has to come to you.

• 1:00:44Jason Calacanis?

  And I think it just slowly atrophies. I know it did for me. If you are a young person, I think. And you've been doing this for a while and you're convinced like it's, you know, you're, it's some crazy capitalist and they're forcing you to come to work. It's actually in your benefit. I think not socializing with people is making a generation of very weird people. I've been talking to some parents who have kids older than us, who lost their entire college years or lost their high school years to the COVID lockdown.

• 1:01:14Speaker 04

  Yeah.

• 1:01:15Jason Calacanis?

  So they literally lost graduation of college or graduation of high school. You should demand as a young person to be in office and to be near the locus of power and to be mentored and to be professionally developed. You should be demanding that. You're getting ripped off. Alex and I came up at a time, you know, me a little bit earlier, where we were in rooms with editors, reading our work out loud, telling us we sucked, telling us how to be better. We got to watch other people do the job.

• 1:01:42Speaker 04

  Yeah.

• 1:01:43Jason Calacanis?

  And we, we had people model at first and the professional development that's happening on when we have our Monday editorial meeting for Founder University, which I've been at two or three of them. I mean, what the, the learning on the feedback I'm getting back from people is like, whoa, that is like the best part of the job.

• 1:01:59Speaker 02

  I mean, your first couple of jobs, you, you don't know how to be a good employee, yet you haven't done it. It's your, your first couple of jobs. And yeah, I can't imagine starting my career in a work from home. Like I was doing it after a decade of being in an office every day, being told exactly what to do. I can't imagine just starting your career from that.

• 1:02:19Speaker 04

  I wanna, I wanna double clarify with something Jason said though. Being near the locus of power is the real hack here. People talk about mentorship and culture and all of that to some degree, but if you want your career to accelerate, what you want is time with the SVP or the CEO or whatever, and they're never gonna have time for you on Slack, but you can find them in the office. You can make you guys collide and then get to know them, lever that. I mean, if you're ambitious, I, I don't think promotes for you. If you are an individual contributor who has a defined role and you're very good at it, sure. But I mean, for everyone else who's not that, I mean, it's kind of for senior status employees, I feel.

• 1:02:53Jason Calacanis?

  I think, I think at this point, if you're like a extremely high performer in a specific vertical with a very tight skill set, with a tight arrangement, you're gonna do X, Y, and Z. Perfect. I'm trying to be the- Return to office armistice person.

• 1:03:07Speaker 02

  Right.

• 1:03:07Jason Calacanis?

  Which is, somebody asked me kindly here, a young person. I'm going to New York, I'm going to a wedding. I don't want to use one of my vacation days. I'll work really hard, remote, but I don't want to go see New York. I've been to New York a million times, I don't like the city. So that's a bit of an insult, I'm from there, but I get it. I'm like, I kinda get it. Shout out to Matty. And Matty was like, can I work remote one day?

• 1:03:29Speaker 02

  Doesn't want to spend any time in New York.

• 1:03:31Jason Calacanis?

  I was devastated. I was like, I'll give you 10 things to do.

• 1:03:34Speaker 02

  It doesn't even sleep.

• 1:03:35Jason Calacanis?

  But I think she wants to save the day.

• 1:03:38Speaker 02

  Alright, hey, listen.

• 1:03:40Jason Calacanis?

  For a proper vacation, you know what I said to her? You're a high performer. Certainly fine, just let your team know. If you need to take a remote day.

• 1:03:47Speaker 02

  At least go to Cass's Deli or something while you're in town.

• 1:03:51Jason Calacanis?

  There's some Chinatown, get some Peking duck.

• 1:03:55Speaker 02

  That's what I do.

• 1:03:55Jason Calacanis?

  Go for a walk in Central Park.

• 1:03:57Speaker 04

  I haven't had lunch yet and it's killing me.

• 1:03:59Jason Calacanis?

  Four, Alex Wilhelm, the amazing Alex Wilhelm. He's at Alex on Twitter. Haushus optimist, go give him the hundy, get his insights every day on his newsletter. Mark Jeffrey from Hash Rate, the pod. Search for Hash Rate right now. Pause our pod, go to Hash Rate and sign up and learn. And you'll be a little out of your depth, but you'll catch up pretty quickly. And Lon Harris, he's at Lon's. You're at Mark Jeffrey on the X, you're active. You're a Trump supporter.

• 1:04:26Speaker 01

  Yep.

• 1:04:27Jason Calacanis?

  You have Trump dedication syndrome. T D. Lon and Alex have Trump derangement syndrome. You have Trump dedication syndrome. And I call balls and strikes. See y'all next time. Bye bye.