SpaceX and Cursor team up to topple Claude Code | E2279

This Week In Startups is made possible by: LinkedIn Jobs - linkedIn.com/twist Grasshopper Bank - grasshopper.bank/twist Notion - notion.com Today's show: This week, SpaceX announced that it was partnering with AI coding startup Cursor on new AI models. xAI's parent company is bringing compute, while Cursor brings developer market share and recent successes, training its own coding models. The deal, while interesting, comes with a steep price tag. SpaceX will pay Cursor $10 billion for their shared work, with an option to buy the entire company for $60 billion later this year. After poking our way through the deal, Chris Zacharia and Brian McRindle of Bitstarter joined Lon and Alex. Bitstarter is a 'Kickstarter for Bittensor,' helping founders get their subnet up and running without tripping over their shoelaces. The Bitstarter crew also broke some news on the show, telling TWIST that they have a new accelerator-ish program kicking off. Next, Ning Ren from Trajectory RL joined the program to explain how Bittensor subnet 11 is using decentralized competitions to design and release better skills. Skills — markdown files with words — have become a critical building tool in the agentic era; how Trajectory will monetize is an open, interesting question. Timestamps: 2:27 Plaud: If your work depends on conversations — interviews, meetings, calls — you need a Plaud NotePin. You can check it out at https://Plaud.ai/twist and use code TWIST for 10% off! 4:07 SpaceX/ xAI "partners" with Cursor! 9:35 Will the Cursor deal help pump a future SpaceX IPO? 9:57 LinkedIn Jobs - Hire right, the first time. Post your first job and get $100 off towards your job post at https://LinkedIn.com/twist. 12:14 How AI coding models like Cursor help xAI grow recursively. 17:24 Chris Zacharia and Brian McRindle of Bitstarter join the show. 20:23 Grasshopper Bank: Time is money. Don't waste either. Go to https://grasshopper.bank/twist and get an exclusive $500 cash bonus just for opening an account. 29:59 Notion - Notion brings all your notes, docs, and projects into one connected space that just works with AI built right in. Try Notion, with Notion Agent, at https://www.notion.com/twist 33:03 How Bittensor subnets monetize and how it compares to VC funds. 37:04 Is Bittensor hard-capped at 128 subnets? 42:37 Bittensor's biggest weakness. 46:10 Ning Ren of TrajectoryRL joins the show. 47:34 Skills now need entire agents just to write them! 48:26 Back up… What are skills? 1:07:38 Amazon and Anthropic's 5 BILLION deal 1:08:48 Google has 2 new chips! 1:09:50 Apple CEO, Tim is COOKED! John Ternus is in! 1:11:37 Alex is bullish on MacBook Neo! 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 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 Check out all our partner offers: https://partners.launch.co/ 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

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

• 0:00Speaker 00

  If you like the AI coding tools you have today, you're going to like them a whole lot more down the road.

• 0:05Speaker 01

  As well as being hyper competitive, Bitens is also extremely cooperative.

• 0:09Speaker 00

  How much money do you need to raise to put together a compelling subnet pitch pre-launch?

• 0:16Speaker 01

  It's less about the amount as a fixed total. It's more about validation. You might be an amazing ML engineer. You might be an incredible full-stack dev, but Bitens is adversarial and the miners are like very, very intense. They're going to tear you apart. You could get wiped out and lose your initial capital.

• 0:35Speaker 00

  This race is going to yield a lot of steel-on-steel sharpening, as we say.

• 0:40Speaker 01

  Sure. We actually have some news that we want to break right here on This Week in Startups with you guys.

• 0:44Speaker 00

  All right.

• 0:47Speaker 00

  This Week in Startups is brought to you by Notion. Bring all your notes, docs, and projects into one space that just works with AI built right in. Try Notion with Notion Agent at notion.com/twist. Grasshopper Bank, time is money. Don't waste either. Go to grasshopper.bank/twist and get an exclusive $500 cash bonus just for opening an account. And LinkedIn jobs, hire right the first time. Post your first job and get $100 off towards your job post at linkedin.com/twist.

• 1:23Speaker 00

  Hello and welcome back to Twist. My name is Alex. I'm joined today by my dear friend Lon Harris. Lon, how are you?

• 1:29Speaker 02

  Doing great. Happy to be here.

• 1:30Speaker 00

  All right. April 22nd, 2026, or as we say here at Twist, AO86. That's how many days it's been.

• 1:37Speaker 02

  That's what we say when we remember to say 80. We're almost at the exact three-month open claw point. And I feel like open claw mania is dying down. That's how I feel.

• 1:48Speaker 00

  Dying down a little bit. Hermes Agent is doing quite well. People are talking about cowork. But I will say, and we're going to get to this at the end of the show, there are some really awesome open weight models that have come out that are incredibly price and intelligence efficient, Lon.

• 2:01Speaker 02

  Yeah.

• 2:01Speaker 00

  So people might want to take a second look at OpenClaw. But on the show today, we're talking SpaceX and Cursor, the biggest deal in the news in the last... Six months, I want to say. And then we have a couple of folks from the realm of Bit Tensor. We have the folks from Bitstarter, and then we're going to talk to the people behind Subnet 11. That's Ning Ren. It's gonna be an absolute bop. Yeah. Uh, but Lon, break down for us the, uh, the headlines here of the big XAI SpaceX news.

• 2:27Speaker 02

  Well, I think first, we should give a shout out to our good friends at Plaude. I don't have my Plaude pin. It's the first time I've made it on the show. I feel naked. My Plaude pin is over there on the desk, and I'm not going to interrupt the show to go right over to get it. But Plaude, folks, incredible technology. We all have a note pin. I have the note S pin. And what's so amazing about it is that it, it will, it, it, it works in the background. You just hit the button, it starts recording, it puts the little, the little light on, so everybody around you can see you're recording. It's not, this is not a spy camera technology. And it not only records notes from you while you're going about your day, bits of the conversation, whoever you're talking to, but it, it sort of organizes them thoughtfully. It's got that AI-powered brain. So it's not

• 3:11Speaker 02

  just, you know, transcribing everything you hear in a big block of text. It's giving you the context, everything you need to go back, search through what was being said, find the nugget of information that you need. It's really like having a, you know, second brain that you can store things in if you are a little forgetful like myself.

• 3:27Speaker 00

  Yeah, it's incredible for me to not forget things. Also, mine's currently charging because I use it all the time. I forgot to take it off the charger and put it back on for the show.

• 3:35Speaker 02

  That's the message you should take, because we're both using our Plaude pins so much that we're having trouble getting them together for the show because they're in use currently, folks.

• 3:44Speaker 00

  And they actually have really great battery life. So I think this is more just you and I being disorganized. But if you want to get your own Plaude note pin S, you can go to plaud.ai, P-L-A-U-D dot AI slash twist. Use the code twist to save 10%. Stop forgetting things. Take excellent notes. Put AI to work for you. Plaude, we love them. Thanks, guys, for sponsoring the show.

• 4:03Speaker 02

  As Jake says, we applaud Plaude.

• 4:05Speaker 00

  Back to the news.

• 4:05Speaker 02

  SpaceX, cursor. Yes. So the big news, yesterday, everybody freaked out in the afternoon. It was, it was like right after we recorded another show, and it was like, ah. So we'll talk about it now. SpaceX and Cursor are partnering on AI models. Of course, Cursor, the popular AI coding model and harness company. They're going to work together to create, and I quote, "the world's best coding and knowledge work AI as a team." Or as Cursor put it, "We're partnering with SpaceX to improve Composer." So the idea is that it's sort of a collaboration, but it's also sort of an early announcement of a potential acquisition. SpaceX is going to either pay Cursor $10 billion for this model collaboration that they're working on,

• 4:50Speaker 02

  or they're going to, at the end of designing this model, just buy Cursor out for $60 billion by the end of 2026 at some point. So it's an interesting, like, the original announcements were all like, "SpaceX buying Cursor," and like, maybe at one point, but they're sort of trial-running it for the next few months.

• 5:10Speaker 00

  So why does this deal make sense from a headline perspective? It's pretty simple. Cursor has done a very good job competing with Codex from OpenAI and also Claude Code from Anthropic, as those two coding products have become really the de facto of the industry. Cursor has continued to grow. It's reached, I think, $2 billion in annualized run rate as of earlier this year. A very impressive number. And I would say most critically, they released Composer 2, which is their latest model that they built for themselves. It was announced a couple of weeks back. And it does seem to perform quite well against industry standard benchmarks, i.e., it's competitive with the models from the best companies.

• 5:47Speaker 02

  Yes.

• 5:47Speaker 00

  All right. So why does that matter if you're XAI, which is now part of SpaceX? Well, XAI had a really big hit coding model called Grok Code Fast 1.

• 5:57Speaker 02

  Right.

• 5:57Speaker 00

  It was incredibly cheap, it was incredibly quick. Everyone used it, it took over OpenRudder for a while. But since then, the company has not been at the tip of the spear, as we might say, in the AI coding game. So what does XAI have? A lot of compute. What does Cursor have? A model that's quite good and the chops to make more. You put the two together, you take XAI's GPU clusters and Composer's AI model-making skills, and in theory, Lon, it's a match made in heaven.

• 6:23Speaker 02

  Yeah. We've seen so much discussion just in the last few weeks. There's more in the docket about this. About how every one of these companies now feels like they need their own AI coding product. That's locked in, that's best in class. Like, that's what's driving so much of this industry. Everybody, again, as you said, trying to compete with the Claude codes of the world, the codexes of the world. We had that Google All Hands red alert from Sergey Brin the other day. He's basically saying the same thing, like, where are we? Why isn't Gemini best of class and the thing every developer is using? So I think it's interesting, sort of looking at it from outside, that that particular tool,

• 7:02Speaker 02

  that that form function of the AI coding assistant has become essentially what's driving the entire AI industry at this point.

• 7:10Speaker 00

  Absolutely. Here is the benchmarks that Cursor put up when they put out Composer 2, their recent model. And as you can see, if you're on the audio version, it's basically a little bit behind GPT-5.4, but it's ahead of Opus 4645 and Composer 1.5, of course, the preceding generation.

• 7:25Speaker 02

  This was not updated for 4.7, though. How dare they?

• 7:28Speaker 00

  No, no, it's not. It's not our fault that Anthropic's been cooking quite a lot in Cursor's.

• 7:34Speaker 02

  Those teens in Discord who are already using Mythos. I hope they can tell us how that stacks up. I don't know if you followed that, sir.

• 7:41Speaker 00

  Oh, yeah, we'll get through that. But the other thing that's really important here is that Cursor has a lot of developer market share.

• 7:47Speaker 02

  Yes.

• 7:47Speaker 00

  And what that unlocks for the company is a lot of information about how people are using its models in a production environment. You can learn from the logs, the traces, call it what you will. There is an opt-out built into how Cursor functions along, so you can't just expect them to have every piece of data from every single user or customer. But probably, there's enough people opting in to share, that they have a pretty good corpus of information on a day-to-day basis.

• 8:09Speaker 02

  Yeah.

• 8:09Speaker 00

  So XAI doesn't have that, because their coding models have not been as well-received as those from other companies.

• 8:16Speaker 02

  Right.

• 8:16Speaker 00

  So data and models from Cursor, and then a lot of compute from XAI, SpaceX.

• 8:23Speaker 00

  I think that there's two prices here that are different. So the $10 billion number is very expensive. Like to partner with a company, to work on some stuff.

• 8:33Speaker 02

  For a single product. If you're like, we got this new model out of it. We really love it. Like 10 peanuts is a big number. Yeah.

• 8:39Speaker 00

  10 peanuts is a big number and we don't know exactly how costs will be shared. You know, is Cursor going to pay for some of the power bill over at XAI's Colossus, you know, supercomputers or not. But $60 billion is not a large number because as we've seen recently, Cursor is considering raising capital today at a $50 billion.

• 8:56Speaker 02

  Right. And so exactly to the end of the year, presumably you would be well above the 60 billion. So theoretically SpaceX could be getting a little bit of a discount on that by where we expect Cursor to be in December.

• 9:07Speaker 00

  Absolutely. So it's kind of a call option on buying Cursor.

• 9:10Speaker 02

  Yeah.

• 9:11Speaker 00

  It's a big old, big old call option. So the risk that I would say SpaceX slash XAI are taking is what if this partnership doesn't bear the fruit they're hoping it does? And they're still on the hook for $10 billion.

• 9:24Speaker 02

  Right. I did have one other financial question and I look to you, Alex, as somebody who's a little bit smarter about this than me. We also have been hearing a whole lot about a SpaceX IPO in the imminent future. Is there a chance that this is narrative in some way? That this is part of the storytelling as we go into the IPO? Like, look at these massive deals. Maybe if you were a little skeptical about XAI because of the model situation, well, now you have this very reassuring news that they're going to be teaming with one of the leaders in that space and so forth.

• 9:56Speaker 00

  Yeah.

• 9:57Jason Calacanis?

  Hiring can be its own full-time job. And hey, guess what? I already have a full-time job. I make podcasts and I invest. But when you're running a small company, we both know every hire matters. You don't want to waste any of the seats you have at your company. And the best partner you can have is LinkedIn Hiring Pro. Why? There's a billion people using LinkedIn. All of the great talent are there. If you're proud of your work, you build a LinkedIn page and you update it. LinkedIn Hiring Pro is going to streamline and simplify the entire process for you. Nearly 60% of companies using LinkedIn Hiring Pro. You're going to get an incredible candidate to interview in the first week. And, you know, we're looking for a new producer for the pod. We did shout outs here on the show. We posted it on my social media. We asked friends. You know where we found our next great hire? LinkedIn. And it was competitive.

• 10:41Jason Calacanis?

  We had like three or four really good choices. So hire right the first time. Post your first job and get $100 off towards your post at LinkedIn.com/hiringprooffer.

• 10:51Speaker 02

  That's LinkedIn.com slash hiring pro offer. Terms and conditions apply.

• 10:57Speaker 00

  So SpaceX going public by itself is a two-part business. It's a launch company and it's also a satellite internet company. And the latter half of that's been very, very profitable for SpaceX.

• 11:08Speaker 02

  And XAI and X. I mean, that's also sort of part and part.

• 11:12Speaker 00

  And then, then you have the other two things. XAI and X, as you said, X, let's just go ahead and say it's break even. Probably somewhere in and around that. Or the losses or profits from it are not really material compared to the scale of space launch, Starlink and XAI. But the problem is XAI brings a lot of costs with it. It brings, I think, a little bit of debt. It spends a lot of money on GPUs. It is not cheap to build essentially overnight. One of the world's largest compute clusters. So if you're an investor looking at this kind of Elon conglomerate, if you will, there are some clear financial winners today and there are some bets that may pay off later on, but you're going to pay for those bets now. So I think you're dead on. This is a way to change the narrative a little bit.

• 11:54Speaker 00

  XAI is not merely the third or fourth place company in the current AI model game. It is now the partner or potential owner of Cursor, a multi-billion dollar revenue company that has a lot more developer mindshare. So it does, I think, ameliorate some concerns, but it's doing so at the cost of 10 or 60 billion dollars. And we don't know long today if those sums are predicated on cash, stock or a mix. Because it could either be debt you have to raise, cash you have to burn, or shares you have to issue or a combination.

• 12:23Speaker 02

  As is so often in the AI industry, it's sort of purely theoretical at this. Like, we could talk about it. It's on paper, but it is, it's not really anything concrete that we could sort of look at the, look at the numbers and break down at this point. It's a promise.

• 12:38Speaker 00

  I also, it is, it is a promise, but I do think that when you're thinking about the size of the prize, it's worth taking some expensive swings. And so the reason why I'm not shouting about the $10 billion fee essentially is because I do think that if you get very good at writing AI, creating AI models that can do coding, you're much closer to. recursive self-improvement.

• 13:02Speaker 02

  Right.

• 13:03Speaker 00

  Which is when an AI model can work on itself and improve itself. So, right now, I think we consider the cursors and the Claude codes of the world as individual accelerants for developers and development teams. But if you want to build the AI model that can improve itself long-term, you're going to need to have, at a minimum, state-of-the-art coding shops, if not, the market-leading option. And XAI just isn't there.

• 13:26Speaker 02

  Right.

• 13:27Speaker 00

  So, a way to turn the page.

• 13:28Speaker 02

  It's that flywheel. It's that the more developers that are using it to code, the more data you're getting about good coding, the better the model becomes and so on. And so, as we look to potentially AGI or models that can write brilliant, beautiful code without a human in the loop ever, whoever has the most data theoretically wins.

• 13:48Speaker 00

  And then there's the future component to this. Here's a tweet from Jason, who's out today. He'll be back later on, don't worry. He's not off the show, just off for today.

• 13:57Speaker 02

  We kicked him off.

• 13:57Speaker 00

  He said, "I mean, everyone gets a day off during that."

• 14:00Speaker 02

  Hostile takeover, folks, hostile takeover.

• 14:02Speaker 00

  So, Jason says, "Fire emoji, wow. Very strategic and bold move. Colossus, which is the XAI supercomputer, is a superweapon for SpaceX already. Can you imagine when it scales to the stars?"

• 14:14Speaker 02

  Right.

• 14:14Speaker 00

  So, the other part of this is, let's say you do get, let's just say XAI buys Cursor. SpaceX buys Cursor. The experiment works out. They take all that data and learning and model prowess, and they make something fantastic. Okay, then what? Right now, XAI has, I think, the only example of compute glut in the AI game. But if they make a model that is as good as they hope, that's going to become a compute shortage overnight.

• 14:38Speaker 02

  As everybody switches over from the Claude's of the world to the Grok's of the world, and then, all of a sudden, they're at the center of everything.

• 14:45Speaker 00

  But today, Anthropic is throttling, blocking, turning people off, trying to just keep itself online. GitHub co-pilots stopped signing up new individual paid accounts to hold back compute. Everyone's struggling.

• 14:59Speaker 02

  I'm not even doing code. I'm like doing tweets in Claude. It's like... Hang on, brother. I need a break. Give me 45 minutes. And I'm not, I'm not taking apart our backend or anything.

• 15:10Speaker 00

  But if you do believe that SpaceX has a chance at building orbital data centers, which we've talked about the Star Cloud, which was 500 company, then you can kind of sketch out a future in which they have the best coding model and the most compute.

• 15:24Speaker 02

  Right. Which is a lot, a lot of, clearly that's Elon's vision as we become a, you know, I forget what the, what the Russian name is, like as we pursue becoming a various higher level civilization, empowering our data centers directly from the sun. Obviously, we would need to have the best compute and the best models in space. We're trying to become a Khadgar level two civilization.

• 15:46Speaker 00

  And if you don't know what that means, you are not spending enough time reading science fiction. Fix that. This is a data set from OpenRadar. And what it shows is the most popular coding models. I think this is the last week, maybe the last day. But Lon, if you take a look at this, you see some open models from folks like Moonshot, which is Chinese, Minimax Chinese, Step1 Chinese, Nvidia, Anthropic, OpenAI, and that's it. And so I think that this is probably the fire they're trying to put out. They have to get back on this board. They have to become competitive. And so maybe a $10 billion bet for a company that's supposed to be worth 1.25 trillion is, and this is an odd thing to say, it's, it's pocket change. It's not that much money in that context. It's three MLB teams, I guess, given the reasons to help us.

• 16:30Speaker 02

  Still a lot of money, but yes, in, in perspective of what these companies are doing, it might make more sense.

• 16:36Speaker 00

  Well, no matter what, I think the takeaway for folks out there is that if you like the AI coding tools you have today, you're going to like them a whole lot more down the road because lord above, there is more improvement coming. This race is going to yield a lot of steel on steel sharpening, as we say. And I think it's going to turn everyone into, I mean, just superhuman developers. I can't wait.

• 16:56Speaker 02

  We're, we're already seeing it. I mean, these, these products are coming out at an insane, insanely rapid rate. OpenClaw, I feel like is updated every other day. There's a new version. So yeah, like the, the drive to become the new Claude code is massive and incredibly intense. As, as intense as any race I think we've seen in tech since I've been following it.

• 17:18Speaker 00

  In fact, you know, Lon, why don't we talk to a couple of folks from the world of BitTensor and see what AI coding model and harness they are using.

• 17:25Speaker 02

  I would love to do that.

• 17:25Speaker 00

  So I want to bring up. Here to the stage are our dear friends Chris Zakaria and Brian McRindall from Bitstarter, and they are in the Gen Z Hype House Podcast Studio with Mood Lighting. Boys, welcome to the show.

• 17:39Speaker 02

  Look at that.

• 17:40Speaker 01

  Thank you very much. Great to be here.

• 17:42Speaker 04

  Yeah, doesn't it look beautiful?

• 17:43Speaker 02

  It does. What does orange lighting signify? What mood is that?

• 17:48Speaker 01

  Our logo is orange. Actually, it looks like we've set it up this way, but that was pure charm.

• 17:54Speaker 04

  Completely plain.

• 17:55Speaker 02

  Yeah, I feel like it's calming. It's giving me a calming, soothing vibe.

• 17:59Speaker 00

  I was getting Halloween vibes. But listen, guys, before we get into what Bitstarter does, I'm curious, for your own development work for the company, what are you guys using these days?

• 18:08Speaker 01

  You mean in terms of AI tools?

• 18:10Speaker 00

  Yeah.

• 18:11Speaker 01

  Opus 4.7, tooled up to the max, code and co-work 24/7.

• 18:17Speaker 02

  They're token-maxing, Alex.

• 18:20Speaker 04

  I'm like consistently on like three instances of Cloud Code and Composer and like making them fight against each other.

• 18:26Speaker 02

  Wow.

• 18:27Speaker 00

  Oh, wow.

• 18:27Speaker 04

  Yeah.

• 18:28Speaker 00

  So what would it take for you guys to swap out your Anthropic and Composer models for something from XAI? Like, how much better would they have to get this, the starting story of the show?

• 18:40Speaker 01

  Ooh, well, Brian's the founding engineer, so I think that's one for you.

• 18:45Speaker 04

  Yeah, honestly, for me, it's always just like ease of use in the sense of like whatever. One of the most valuable things is not impeding someone's workflow. Like, I wouldn't want to go have to download another tool that's not Klee-based or something that's, you know, isn't clearly better. Like, there's a bunch of people who are like at the edge of everything and they want to use absolutely every single tool, but that's not the vast majority of engineers, right? It just needs to be known to be the best. I need to see it on the leaderboards. I need to see it on places like Arena. If you guys know where Arena, LM Arena.

• 19:11Speaker 00

  Oh, yeah. Oh, yeah.

• 19:12Speaker 04

  You know, it just needs to be like, I think there was a whole push for Claude Code, and it was very clear that it was the best. And then I moved over and said, yep, that's obvious.

• 19:20Speaker 00

  I have some Arena data here for anyone curious. So this is a rundown of the leading AI labs in the coding context grouped. And so the current leaderboard is Anthropic, then Z.ai, the Chinese company behind the Really solid GLM 5.1 model Alibaba with the Quinn family, OpenAI, of course, GPT 5.4, Codex, Google, Moonshot, Xiaomi, Minimax, then XAI, then DeepSeek. That's the top 10 in the world today. Kind of a shocking list. A lot of Chinese companies, they're doing quite well. I'm encouraged by that. But guys, let's talk about Bitstarter. So we have been going deep in the world of BitTensor. I have talked to so many subnets. We've learned so much and

• 20:03Speaker 00

  it's been an absolute treat to see how the economics function. But you guys have put together kind of an on-ramp, if you will, to BitTensor via Bitstarter, which you guys kind of called the Kickstarter program. So what we want to know is, why couldn't we use Kickstarter for this? Why?

• 20:20Speaker 02

  Is there, yeah, is there something in the Kickstarter rules that's like no subnets?

• 20:23Jason Calacanis?

  Here's a startup truth bomb. A lot of founders have no idea what's actually going on with their money. If that's true of your company, hey, no judgments. I know you're busy hiring, building your product, go to market, all that important stuff. But your company needs a reliable financial partner, not a lifestyle brand, okay? Grasshopper is a real federally chartered digital bank that's not trying to win you over with a rewards program. Instead, they're building deep integrations, treasury products that are going to actually help you expand your runway, and innovative tools, like an MC-based AI connector. Oh, man, that's awesome. You can connect it to all of our agents and do reporting. And that will put you in command of your money. As a Twist listener, you're going to get $500 cash bonus just for opening an account. Think of that. You open

• 21:08Jason Calacanis?

  an account, boom, there's $500 in it. So leap on over to grasshopper.bank/twist and use the promo code TWIST. As a Twist listener, you're going to get a $500 cash bonus just for opening an account. Grasshopper.bank/twist.

• 21:23Speaker 01

  I'd love to see someone try, and maybe that should have been the prototype. But for a decentralized network, BitTensor's launches back, say, a year ago were really opaque and had an information asymmetry where it was investors who were in the know, who could decide whether or not a team got launched. And it was retail chasing after once the The subnet had already gone to the protocol and was already pumping. So that was one big reason why we wanted to create a system whereby, hey, what if we could launch teams together in a distributed way and give retail the same chance as investors get, the same

• 22:04Speaker 01

  OTC style terms that you'd normally only get if you're an investor in return for crowdfunding a team to the protocol and getting them over that initial investment hump and building on BitTensor.

• 22:15Speaker 00

  Okay, so it's kind of community, it's kind of being a purpose driven product in terms of it does one thing very well. I guess my question is, how much money do you need to raise to put together a compelling subnet pitch pre-launch? And then is that raised in USD, a stable or tau?

• 22:38Speaker 01

  Right.

• 22:38Speaker 00

  Which is the BitTensor token, if you didn't know.

• 22:40Speaker 01

  Great question. So it's less about the amount as a fixed total, it's more about validation. And what I mean by that is, would this actually work on BitTensor? You might be an amazing ML engineer, you might be an incredible full stack dev, but BitTensor is different. It's adversarial. You're designing for a game theoretic AI environment and the miners are like very, very intense. They're going to tear you apart. So you might think you've got an amazing business idea and a great white paper, you've got the GitHub repo. But if you don't validate that it's going to work in a distributed adversarial system, then it's more like you could get wiped out and lose your initial capital, right? So yeah, go ahead, Alex.

• 23:25Speaker 00

  Well, the reason why I like this lawn is that it sets up a way to kind of screen out the crap. And then therefore allows people to have more confidence in both backing new subnets, but also investing in the ones that have already made it. But here's the thing, it doesn't feel super decentralized to need bespoke on-ramps, if that makes sense. So tell me, tell me if I'm being overly precious here, but it does seem like when I talk to folks in the realm of BitTensor, we talk about community and kind of caring for the ecosystem, which is all well and good, but it sounds a bit more like a gardener pruning a tree than letting a forest grow wild.

• 24:04Speaker 01

  Well, I want to get Brian's take on this as well, but my take on it would be BitTensor, Alex is absolutely right. It's meant to be that way. It's meant to be super competitive, right? But BitTensor is also, as well as being hyper competitive, it's also extremely cooperative in that there's a lot of like cross pollination. There's a lot of openness between the teams. There's a lot of collaboration there too, right? There's a lot of like shared resources. We go to the same conferences. People know each other. And it's the combination of the two. It's the integration of competition and collaboration that really succeeds. The thing that was getting me about the, about launches was that because the funding to get the subnet slot was really concentrated

• 24:45Speaker 01

  in about maybe four different types of investors, a subnet slot can cost, say, quarter of a million dollars, maybe more in Tau. And that's burnt now. So that's, that's a sunk cost. So if you have to go to investors to say, hey, can you give me that initial startup capital so I can get some net? Their terms are often like, okay, we'll give it to you. We'll give you that initial hundred K, but you have to give us 20% of emissions in perpetuity. And then suddenly you get like a small group of investors owning like 80% of the teams on the protocol. Hence, hey, what if we crowdfunded it? That way you don't have these investors who have to put up that first quarter of a mill.

• 25:22Speaker 01

  And the teams aren't weighed down by having to give away 20, 30% of their emissions forever, which means they've got less to spend on stuff. Yeah, that's an insane cut.

• 25:33Speaker 02

  There are only like 128, I believe, subnets in total. So how competitive is it for each of those slots? Is there like a long waiting list for like some company has to go out of business for you to take over the subnet? Like what, what is that marketplace like?

• 25:49Speaker 04

  Yeah, I mean, there, there definitely is a process of like subnet deregistration.

• 25:53Speaker 02

  Right.

• 25:54Speaker 04

  So, you know, there needs to be, there, there is like, people have been deregistered in the past. Sorry about that. People have been deregistered in the past. But really, when it comes down to it is that like, you know, the competitiveness comes down to like the price of actually registering a slot fluctuates. It's not a fixed cost, right? It's this dynamic number that changes. Like if I register, okay, well, it's going to double the next time someone else wants to register. So there's like a market value to registering and it becomes basically like, can you register something before somebody else had a certain amount of money? And if you need that amount of capital.

• 26:28Speaker 00

  Yeah, so it's a bit like the the sports franchise model like there's a new NWSL team. They had to pay a $205 million fee to join a limited number of teams. So you're kind of buying, you know, the the Boston basketball team equivalent slot as part of the BitDancer subnet group.

• 26:45Speaker 01

  Exactly, and some slots have more liquidity than others. So one of the first subnets, if you get, say, you know, one of the first 20 or 40 subnets, it will probably have a lot more alpha in it than a subnet that was registered later. So Handshake 58, what you're on now, this is on subnet 58. This slot has a lot more alpha on it than, say, subnet 120. So that means more liquidity, which means more capital to spend upfront on the things that you need. So there's also competition there.

• 27:16Speaker 00

  Why does it have more alpha? I thought alpha tokens were the the subsidiary tokens on a per subnet basis that were used to incentivize the miners and validators. I didn't know that they were that they varied in quantity based on subnet number. I feel like I'm missing something here.

• 27:28Speaker 01

  It's when they were registered, they start emitting alpha. So some of them got registered over a year ago, so they've emitted more in that time. They all have the same fixed total.

• 27:37Speaker 00

  Yeah, there's always a new corner in the Dancer land for me to look around and go, I didn't know that.

• 27:42Speaker 01

  Well, can you imagine starting a subnet, Alex, and not knowing this stuff and being like, wait, hold on a minute, what?

• 27:47Speaker 04

  I think there's there's like some really strong intrinsic value to what BitStarter is trying to do, right? Like, there's, you know, so I primarily work at MacroCosmos. You guys have had Will and Stefan on here in the past.

• 28:00Speaker 00

  Great folks.

• 28:01Speaker 04

  And just learning how to go through the process of creating a subnet and doing everything from two years ago, like when there was almost nobody in the ecosystem and people knew and like, but there's a lot of tribal knowledge. Like BitStarter was like the very first really official initiative that was trying to give back to the community and say, okay, I there's this whole treasure trove of information that you need. Like, you need to go from zero to one really, really fast, and that's how you're going to be successful.

• 28:25Speaker 00

  Yeah, so you guys add credibility and guidance, but also I feel like if a subnet goes through BitStarter, given your guys' you know, place inside the ecosystem, it's a really big stamp of approval. It's credibility essentially instantly.

• 28:38Speaker 01

  We try and bring together a mixture of experts, of the best people on the protocol, to give free discretionary advice to the applications that come in, the ones that pass our initial review. We help them build up their proposal. We then share it with a cross section of the ecosystem. People have run validators, miners. Jacob, the co-founder of BitTensor, is on the advisory panel. And it's through their advice and their commentary that helps improve the application. If you're a prospective subnet owner, you don't have to take their advice, but it means that lots of senior people in the protocol have had a chance to help you if you want it.

• 29:20Speaker 01

  And then even if not, you get to pitch it live on air through our show so that you can find your people. And at the beginning, it can be really hard to get attention on your subnet. Like Lon said, there are 128 of them. So by starting out by, you've got the best people in the protocol looking it over. You've got backing from people who've built it before to improve your proposal. And then you go live on air with a crowdfunding behind you. We've gotten like up to 2,000 people before. It was like the second most watched show on BitTensor after novelty search, which Jacob posts. So you get a chance to find your people, make your case, and then hit the ground running.

• 30:00Jason Calacanis?

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• 30:41Jason Calacanis?

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• 31:14Speaker 02

  Have you noticed any, I mean, you've run a lot of these competitions now or a lot of these sort of projects. Are there certain kinds of projects or certain kinds of pitches that get everybody's attention and sort of do better naturally on the system? Like I know Kickstarter always worked that way. People were always like, oh, you got to fuck like a horror short. The horror does great over there. You know, that kind of stuff.

• 31:33Speaker 01

  Right. That's the exciting thing is that what are the parameters? What are the best startups for building on distributed systems? What does a community like BitTenser really respond to? What turns them on? And a lot of it actually comes down to the founders and the founding team. And there was a team we launched back in January, we did it live from Davos, and no one had heard of them. They'd been in stealth mode. They were two tenured professors from an East Coast university. And then the other one has a chair at Harvard in philosophy, and they also have an AI podcast and run a hedge fund. And they've got a, they had a business already built and launched in the same sector that they were going to build the subnet in. And that, we completed their raise in under an hour. That was 600

• 32:16Speaker 01

  tau. So that, when you have great founders, no one's heard of them. There's this element of like surprise. We dial people in from different parts of BitTenser to give their perspective. That can be great. But long-term, what you're looking for is what are the types of problems that are best solved on a distributed system? And what do they need to succeed when they hit the protocol? There's the liquidity pool management. There's the social media aspect. They're managing the miners and the validators. So it's a really complex entity. We're tracking every team we launch so we can learn as we go what really leads to success.

• 32:48Speaker 02

  It's a little bit, it's like subnet university. It's a little bit like we're seeing students for founders, but for people specifically in subnets. That's what it makes me think.

• 32:56Speaker 00

  But you know, if Jason gives you money, he gets stock in return. So I'm curious, Bitstarter as a project makes sense to me now. Really appreciate the explanation. Is it designed to be a revenue generating business? Or is it more a community arm of the BitTensor folks to help get people onto subnets that are being either misused or underused?

• 33:16Speaker 01

  We take 3% of emissions for the first 90 days after they get to post-launch. That's a lot smaller than what a lot of other incubators take. But we, our mission was to build BitTensor better. I know that actually subnet owners only get 18% of total emissions because 41% goes to miners, 41% goes to validators. If you take more than that, right? What tends to happen is that they don't have as much disposable capital to spend on things like recruitment or infrastructure, which means that they tend to struggle a bit more when they get to mainnet. Whereas my gamble was, well, if we take less from them and we bring in more partners at the start, they can spend the money on the partnerships that will help them to thrive.

• 33:59Speaker 01

  They'll be less weighed down by someone taking passive income from them.

• 34:03Speaker 04

  Yeah, and I think there's also a big, big bet in there too, right? Where you're, you're investing in them, taking less with, with the hope that their alpha also appreciates, right? Like you want them to be successful. You want them to go through the whole process of like being, creating something state of the art, creating something that's going to change BitTensor or change technology in some way.

• 34:22Speaker 01

  Because then the relative value of that 3% is way higher.

• 34:25Speaker 00

  Yeah, yeah, yeah, yeah. But it's kind of staggering that people would want to take 20 or 30% of emissions in perpetuity and you're taking 3% for 90 days. Is, how do the economics work out on your end? Because that could be a, a smaller sum of money if those tokens don't appreciate greatly in the future. So are you willing to just kind of eat the work just for the sake of the, the network's overall health?

• 34:49Speaker 01

  At, at the beginning, it was really important to prove that this works. No one ever tried this on BitTensor before. You're, you're pledging towel for future alpha emissions and we wanted to prove that it would work. 3% thing, it's perfectly viable, but it's harder to work with teams long term. What happens when we've launched 12 teams or 20, right? Will we be able to work with each one long term? So we actually are setting up a venture studio so that we can put upfront more of the investment in launching a team and then be able to incubate and accelerate teams for much longer periods of time. And in fact, we actually have some news that we want to break right here on this week in startups with you guys. All right, let's do it. Look at that.

• 35:32Speaker 01

  Which I wanted it to be enough of a surprise. I didn't even tell you guys beforehand, like in the backstage, but. Thanks, by the way. Totally nothing. Next. There's nothing like doing things live, huh? So we, our second team that we launched, subnet 24 Quasar, they do long context models and intelligence. That means that they're looking to expand context windows for L L Ms. We launched them in January, three months later, they're about to release their own model. And they were, they're, they're close to being in the top 10 subnets. They have a fully diluted value of about $84 million.

• 36:07Speaker 01

  And what they were doing impressed Jacob so much that he decided to back them himself. And that happened to another team that we launched as well. And so when we were talking to Jacob about it, Jacob said, I want you guys to help bring more machine learning research teams onto the protocol. And I want us to be able to build like a fully decentralized tech stack for BitTensor, where we bring in the top machine learning startups and research teams to build on the protocol. So Jacob has given us funding to register subnet slots for machine learning research teams in a new machine learning track on BitStarter, where we'll be working with teams across the protocol to deliver state of the art

• 36:52Speaker 01

  across a number of benchmarks, working with teams like Mac Cosmos, like Targon, who have already pushed the boundaries to bring in the best machine learning researchers, incubate them and help them to succeed on BitTensor.

• 37:05Speaker 00

  So to help them succeed on BitTensor though implies that, well, one, congratulations. Should have started with that.

• 37:10Speaker 04

  Thank you.

• 37:11Speaker 00

  But implies that there's enough room for them. And one thing that I keep kind of looping back to is this hard cap of 128 subnet slots. I know it was 64 back in the day, but to get all these ML engineers that you're hoping to have into the ecosystem, to me implies you're going to need more total parking spots. So is that something that's being discussed? Is that coming or is much like the 21 million Bitcoin cap, is 128 the end of it?

• 37:34Speaker 01

  It definitely isn't the end of it. There, it will expand. And when Jacob was on Novelty Search to talk about conviction, he said that it will, they're definitely going to expand it to 256 soon. I think when we went up to 128, it, the quality got a little bit uneven and you're spreading out emissions over more subnets. There, there isn't really a hard limit. It's already a very, very large chain, BitTensor for a layer one, but it can handle more and it will go up again. Subnets get deregistered right now every couple of weeks and other subnets are for sale. So we've had a lot of new entrants. In the past week alone, we've had about three new subnets come in. So the recycling is actually quite strong. It's like what you were saying earlier, Alex, it's really intense competition.

• 38:18Speaker 01

  So with the de-red, the deregistration, we can get a new team in every month.

• 38:23Speaker 04

  Yeah, it's, okay, there's a, sustainably, it's very hard to run a subnet. Like the, the, the process of trying to do everything from the marketing to the engineering, to the socials, to the, to the organizing of your own company, right? Like, there's a lot of different components there. So like it just naturally, the churn is going to be high. Yeah. So, you know, like institutions like, or like macro cosmos or, or, yeah, like Targon or the Chutes or the, the Quasars of the world, you know, they've gone through that process and been able to be successful. And again, that's what, you know, Bitstarter is trying to do is to like pull out you out from the churn, right? But there is, there's still a lot. But yeah, fundamentally, like you should be able to go to like, you know, eventually it'll be to 256 and then it'll be 1028 and whatever that, whatever that comes to being.

• 39:06Speaker 04

  But there's definitely space within the ecosystem of BitTensor to have more machine learning. Like, I think for me, for what I've seen in the past couple of years, there was like, A few really good nuggets of ideas and research, LLMs. And then we went through this huge, massive product phase of like expanding the number of subnets and people trying to find product market fit and finding revenue and doing all these sorts of things. It almost feels in some way, shape or form like the predominant energy feels like, okay, we need to do more machine learning, we need to do more of this stuff. And like, that doesn't necessarily mean that there won't be more products in the future of BitTensor. But there definitely is a lot of space, a growing space, to do more like fundamental research, to do more collaborative research, to do more like fundamental things on BitTensor to like, you know, push the field of machine learning and artificial intelligence forward.

• 39:49Speaker 00

  Well, this answers the question that Lon and I had in our notes, which is, you know, how many more ideas are feasible for this adversarial decentralized model? And it sounds like even inside of the very niche area of ML in particular, because there are different projects out there, tons of space left to build, to work and to host these competitions. So Lon, I guess, you know, maybe we're going to end up with, you know, two, five, six subnets out there. More, more fun. Bashy, run another, try to make better stuff. Future twist episodes, I'm happy to hear it.

• 40:16Speaker 04

  Yeah, yeah. I think, I think also too, just like putting another note in there, right? Like, I think the founders, Jake and Allah, and particularly Jake, like, they're very amenable to what the next generation is going to look like, right?

• 40:29Speaker 00

  Yeah.

• 40:30Speaker 04

  Something happens in the ecosystem and they want to make the right move as fast as they can, right? And sometimes that goes well, sometimes it goes poorly, but I think like that gradient of improvement is really fast, it's accelerating. And if we find ourselves in a situation where like, oh, we have so much talent, we don't have the space, like, that, that day will come where we just, we increase it.

• 40:48Speaker 01

  Yeah.

• 40:48Speaker 00

  Yeah.

• 40:50Speaker 01

  I wanted to just touch on what people actually will get when they submit to the incubator if they're chosen, because we will register the subnet for them. So that's the upfront cost, that's several hundred tau paid for. We also have a partnership with subnet for Targon, which is run by Manifold Labs. They're offering free compute to our incubated teams for their post-launch period. We're also in talks with Crucible Labs, which is run by Allah, who's the other co-founder of BitTensor with Jacob.

• 41:21Speaker 01

  Exactly. It's confidential compute. Targon just published a paper with Intel. They are about to launch Targon OS. They have the Targon virtual machine. And by all accounts, it's highly reliable, which is what you need when you're doing, say, pre-training of a model. Quasar already have a partnership with Targon and it's helped them to train their models. So we're creating a system whereby we've got a cross-protocol selection of existing infrastructure that can help power the latest ML researchers to success. Long-term for these other subnets, it's good for them commercially and it helps to create like a network effect of machine learning research on BitTensor.

• 42:02Speaker 00

  So there's several kind of like individual loops that improve things. As you make better models, you can bring those to bear another subnet competitions. Therefore, those will yield better results, therefore bring in more people. Competition for emissions goes up, TAL becomes more valuable, the ecosystem is worth more, and then suddenly more people show up. It's a great idea. Here's the thing that I want to flip around though. Jason's a huge ball. We talk about it all the time on the show. What's BitTensor's weakness? Like if you had to pick one, the thing that keeps you up at night, what's the other side of this coin?

• 42:34Speaker 04

  With every technology, there's always some weakness. I think one of the things is like, it's very difficult to find the right project. Right? Like, I think it can be very difficult to find, parameterize your problem in the right way to get the actual most benefit out of it. It's kind of an art and it takes a lot, again, it takes a lot of time to figure out what that looks like. Sometimes you can find a problem where if you're not expressive enough, like you just won't be, you won't be better than the version that you created because you've been the one thinking about this problem for many months, if not years, and then trying to launch it on BitTensor. If you don't do that in the right way, you won't end up in a good place, right? So again, like places like Bitstarter are trying to circumvent this where, you know, you can talk to someone like myself

• 43:18Speaker 04

  or talk to someone else in the community and be like, oh, obviously that won't work and you can go further with this. Yeah. Do you have anything that you want to say, Chris?

• 43:26Speaker 01

  I think its biggest weakness is the same as its biggest strength. And it's captured in this phrase, which is, if your system only works when people play by the rules, your system doesn't really work. BitTensor, you have to design your product as if it's for the people exploiting it. Because you know that they're going to get, it's going to get exploited. You have to think in this really unusual inverse way where you're like, you have to design it with the exploit in mind so that it's almost like a jujitsu move whereby when people go to exploit you, you use that power against them and it gets stronger, right? And thinking like that is very unusual. We don't think like that in most of life.

• 44:06Speaker 02

  Because your miners are your users and normally you'd be like, we gotta do everything we can to make this as smooth and clean and enjoyable for them as possible. But in this case, it's like, yeah, but they're also trying to screw me. And so I have to like navigate around that in advance. Yeah.

• 44:22Speaker 01

  So you're creating, you're not launching a business or a startup, you're launching a network, right? And actually, networks are the more appropriate home for AI than a business, which is limited, proprietary, closed bot. That's not where AI is eventually going to live. And the clue is in nature, right? Look at how intelligence develops in the natural world. It didn't develop in a single place. It developed through the survival of the fittest, natural selection in a distributed system of predator and prey. That's exactly how we're building intelligence of BitTensor, miner validator, right? You're creating, you're distributing the roles and you're creating the adversarial environment for that to grow.

• 45:05Speaker 01

  So it is the better home for it. It's just, if you thought running a startup was hard, try running a BitTensor subnet.

• 45:11Speaker 02

  Try running the process of evolution.

• 45:14Speaker 00

  Yeah, I was gonna say Darwinian evolution via natural selection, AKA BitTensor. That's gonna bring in all the founders, man. It sounds super easy. But if people do want to find out more about the program you just announced, apart from going to bitstarter.ai, your main site, where can they go to learn more?

• 45:30Speaker 01

  So we will be opening submissions next week. We have a submissions portal for that. We are going to be incubating three teams a quarter. So applications will open app-bitstarter.ai. You can also follow us on X. I'm at MattRazak, also at bitstarter.ai. So we will be announcing the eligibility process there. And we already have a couple of applications that we had beforehand that we put into the track. We'll be publishing the guidelines as well.

• 45:59Speaker 00

  All right. Well, guys, we're super stoked about it. When you have your first three, come back on the show and tell us all about them. Cause we're always here to learn more about awesome subnets. Thank you both so much for your time and you can now turn off the Halloween light behind you.

• 46:11Speaker 01

  Thank you very much.

• 46:11Speaker 00

  Next up, we're going to bring Ning Ren up from trajectory RL Ning. Welcome to the show.

• 46:16Speaker 05

  Yeah, hi. I'm very happy to join the podcast.

• 46:19Speaker 00

  We're delighted to have you. We're absolutely stoked. So we're going to go from the macro picture of the bit tensor economy down to a single subnet. What we'd love to hear from you first is the pitch. What does subnet 11 trajectory RL do?

• 46:32Speaker 05

  Yeah. Okay. Let me introduce myself a little bit. I'm a founder and CEO at Traditor RL. So Traditor RL is a new like a company running on bit tensor. So if I put one sentence to describe the Traditor RL, so it is a new type of software company, software company. It's building softwares for, not for humans, but for AI agents. So nowadays we call it, we call them skills. But the future like we become like a better name. But now like we are like running a company. Like continuously producing such skills on softwares for AI agents. But like, like now everybody's talking about like cloud code Hermes and you talk about coworkers, like everybody using it.

• 47:16Speaker 05

  So if you think about it, so we are in a middle and very early days of a paradigm of platform shift. Like those AI agents become the new, like computer platform, become the new smartphone, become the new operating system. Just like any other existed operating system before, like they will need the software to power them up to be useful. Like now, like if you stay around, like there are some skill hubs like all around world, like people still writing skills by hand. Like using some like code your tools, like yeah, like, but like we envision like future, most of those skills will be written.

• 47:58Speaker 05

  Not by human, but by AI agents. So this is a, yeah.

• 48:02Speaker 00

  For some people out there who are a little bit behind, a skill is a skill dot N D file. It's essentially. Plain text, it's the written word, not code. And it's essentially a set of instructions to help an AI model or agent do one thing in particular. Is that fair, Ning?

• 48:19Speaker 05

  Oh, yeah. So like, it's not necessarily be only a skilled MD. It can be a combination like a skill, like some like MD files, combine some Python file, like coding examples. I can some like a logic to tell the agent how to do some like business in a domain. Yeah. I think it could be like your personal CRM. It could be a Twitter post, like a writing tool. It could be a website creating tool.

• 48:45Speaker 00

  Yeah, we've had a lot of these in our open clock conversations, for example. So we just had the folks on from Bitstarter talking about the economics of running a subnet. So tell us how trajectory RL uses BitTensor to create and encourage the creation of better skills.

• 49:04Speaker 05

  If you think about it, it's very like an interesting problem, like how we can organize. So basically, we use BitTensor to, I'll just treat like the agents all around the world to compete, to collaborate, to write a good skill MD, or like a skill pack. Like, I think the first challenge we have is to create a good benchmark tools. Because now, if you see around, there's no good way to measure like how a skill, like running on an agent, right? People just post, like many people download use. Like, this is a very like innovation we create. And so we, basically, we create a sandbox, like technically we call it sandbox. But you can think of it as a puzzle, puzzle box.

• 49:46Speaker 05

  Like the agent come, any agent can come, like a code Hermes can come and open the puzzle box. And there are some tools included in the box. And it just gave a puzzle to solve. Like, we just compare, like compete this solving, like the miner can, you can write, using any technique to write a good skill MD and the power of agents and to solve this puzzle. We just rank and the score.

• 50:13Speaker 00

  But in this sandbox, though, each agent would have the same model and harness. So that way, the individual skill file would shine versus something else influencing the performance.

• 50:25Speaker 05

  Basically, same model, but like a different harness. So we compare across different harness.

• 50:33Speaker 05

  Like the harmony is called, yeah, but we we want basically know like the skills, how it performs with like different harness as well.

• 50:43Speaker 00

  Okay, so Lon is a writer and I'm a writer, which means that skill files make a lot of sense to us because when it comes to typing out words and sentences, that's our bag. But I'm curious if that inherent method of creating skills, these these markdown files, these text files, gives them a lower ceiling in terms of improvement than if they were done with code? Or alternatively, does it create a higher ceiling for improvement because they are written in English, for example, versus in code?

• 51:12Speaker 05

  So I see like there is a higher ceiling for the skill. So if you see like there is a theory called the fat skills in harness. Like it means that so like people think that the harness, yeah, it's more like the operating system. It's only handle like the file reading and the like talking to the different IMs, the like the input output. And there is a core component called reserver to just decide the right time to load the right empty file. And all this does like the harness is doing this well. And and the other, the rest, really magic happened and all the intelligence will happen in the in the skill layer, in the skill space.

• 51:54Speaker 05

  Like, like if you think it like open, you can, you can think like you, the people will have their own CRM. Like it's a, it's a skill, like a different people, people will have, will have different CRM a little bit. And like eventually there would be like an infinite kind of, kind of skills.

• 52:13Speaker 02

  I mean, I guess my question would be, I I have a few skills that I've made and I'm not a coder, but just like, hey, help me with YouTube titles or whatever. And the way I make them is, you know, I sort of work on them with Claude together until we're happy with how the skill is written up. And then it's trial and error. I I'm trying it. Oh, I forgot to tell it to capitalize or it's using too many M dashes or, and we sort of vibe code the skill together for a few hours until it's like perfectly tight. So is that essentially the same process that your agents are now replicating? Or is it more of like thinking about it in advance and taking out the sort of vibe coding time waste period?

• 52:52Speaker 05

  It's kind of like the similar process, but just like nowadays, like you, like using right to the skills I'm deep by hands. Like, but we want to like replace by using agents. Like we designed the mechanism like minor already using agents to writing skilled I'm D this way. When they use agents, they also use the web, but they run their benchmark. Like they mirror the, the result of the, of the, of the skill that I'm D and they use the agents to iterate. Like, like you do, but they deliver, like they hand more and more work to the agent to automate this flow, this workflow. So this is, you know, what we will.

• 53:38Speaker 00

  I think, I think I get this. The question then becomes what skills are the most interesting to set up competitions for? To improve because Lon just mentioned he's got this YouTube title skill, a bit niche, interesting. A lot of people make YouTube videos. They all need titles, man. But maybe it's a good point. Is that, is that the, the, the type of skill that is a good fit for trajectory RL? Or is it more general skills that are going to be the early product market fit use case?

• 54:10Speaker 05

  Good question, good question. So there, there can, could be like a very different type of, of, of skills. And so we are still, we are also exploring like which one could like it's better to mirror. And the, so, so, so that's why we, we set up, set up seasons, like the, the first few seasons, we want to explore some like a meta skill. Like it's easy to measure and it's more widely, can be widely used. Like the self learning skills that this is the first season. So we just launched our first season for like less than a week. And yeah. I can, so I can.

• 54:49Speaker 00

  Please.

• 54:49Speaker 05

  Skinshare, I can show you. So you can see, so there are like a different type of skill we can, we can mirror. So like the first season, we do like, do some like a meta skills called the self learning. And we want to enable the, the agents can just, uh, when, when they like encounter some errors, they can learn. And they can fix them themselves. This is the first season, we just launched it for like, let's, let's now week. So you can see we create our benchmark.

• 55:19Speaker 00

  Yeah, tell people what this chart um shows, because a lot of folks are on the audio version. So tell them what they're seeing here.

• 55:26Speaker 05

  So basically, we bring like some popular uh self learning skills, because they are already on the skill hub, like many other places. Like to run our benchmark and we also pick the, the winner in our like subnet. To do a like side by side apples to apples comparison. Like how, um, like, like how, how they work. So because, because we can mirror, like we create a benchmark, so we know, so we, so we can improve. Like if you can, you, you can not mirror, you can not improve. So we can, so, so, uh, if you see the leaderboard, like we only run for a week.

• 56:06Speaker 05

  We already see some very promising results, like our subnet winner already performed a little bit better than the, the sort of on the market. So just by keep running this season, we will get our very good like SOTA self learning skills. Yeah, so to answer your, your question, to back to your question, yes. So we will like uh, uh, compete on more and more different type of skills. But we will start from the, the like, the meta, like more like a general meta skills first.

• 56:41Speaker 00

  So we have companies in the world line, building AI models, both open and closed source. We have BitTensor having several subnets that are working on training models in a decentralized basis and open spaces. And now with trajectory, we have a way to. Apply the same competitive logic to skills, essentially turning each skill file or skill that you can use into an improving process similar to what we see elsewhere. Okay, so the result of this Ning is that everyone's agent is going to be more capable and more performant out of the box because the skills you can bring to them are already better. Okay, that makes a lot of sense to me and I would love that. I've made some skills too, but they're garbage. So I would love to get some help from the experts.

• 57:25Speaker 02

  Yeah, I think that leads to my next question, which is, I mean, conventionally, the way I think of skills, they're basically free. Like, somebody designed a skill and then they tweet it out and then they're like, hey, I wrote this X article about how I trained my new open claw skill and da, da, da, da, da. Try it out yourself, here it is. And so, I mean, I think you're sort of looking forward to a future where skills become a lot more dense and a lot more valuable. And then there also is money, sort of, they're actually worth something and people would pay you for a skill. Is that, is that the vision? And how much do you think people are going to be willing to drop on a really amazing, right out of the box skill?

• 58:04Speaker 05

  So I think in future, there definitely will be the business value inside these skills. So if you remind the early like 90s, early PC days, there would be a bunch of free softwares. But later, like the smartphone app, app store, but later there will be super software, there will be Instagram. Like, so if you, like, our current mission is to maximize the distribution and installation of the skills. And later, like, there are hundreds of ways that you can figure out to, to the monetization.

• 58:37Speaker 00

  And do you need to monetize them, Ning? Because the way that I was thinking about the competition, the BitTensor subnet kind of self-funds via emissions. So could you create a system here that doesn't actually need to have a business on the backend? And instead, it's essentially just a recurring competition to create better and better skills? And then everyone can use them because, you know, Tal emissions filtering down to the subnet. Compensate everyone for the work they're doing already.

• 59:07Speaker 05

  Yeah, good question. So this is actually exactly what we are doing now. So we are leveraging the Bitensor incentives to drive the agents to like submit to optimize the skill MD. But like my, my thought would be like in the end of the day, we still need to find the PMF like we still to like, like make money, like make a real, real product. And so we just like take advantage or we should take benefit from the Bitensor to like, like co-start us, like incorporate us to a state like we have like a super massive adoption and we can like find a way to to charge to either to

• 59:51Speaker 05

  like user pay. Or there's also another very good angle like the trajectory data. So when we run so many skills and collect so many data, those data are also valuable as well. So we can sell this to the model. We can even try like finding our models to like.

• 1:00:10Speaker 02

  I got, I got one more. I got one more question. I will let you go, Nick. What is the most valuable or useful skill that's been designed so far on trajectory? Can you, can you walk us through like, I want to get a clearer example of like how, how intense and awesome these skills are going to be?

• 1:00:26Speaker 05

  Oh, okay. Yeah. So since we just, we are relatively new, we are like about more than one month on Bitensor, which launched our first season about less than one week. And the first season about self learning. So we all are already see a good self learning skills, like just about one, one week is, is very impressive. So people already find some good, good, good way to write, have learning skill though, MD. So now you can go to our website and, and try those skills, self learned skills to just to make your agent. So if you use it, use them day to day, make them like make less mistake and save your tokens, solve like a problem more effectively.

• 1:01:07Speaker 00

  All right. Well, we really, really appreciate it, Ning. What's the website? And tell us when season two begins?

• 1:01:14Speaker 05

  Oh, since so the website, the.

• 1:01:18Speaker 05

  RL.com like

• 1:01:19Speaker 00

  Trajectory RL.com

• 1:01:21Speaker 05

  Yeah, so the season two will be hold like in about one month. So we we we plan to like hold the season one for one month and like to start after that. But in the future, like as I said, we want to drive this process all by agents and we want to continuously roll up new seasons just by agents. We we want to build AI native company ourselves.

• 1:01:49Speaker 00

  Oh, well, I I freaking love it because I need better skills. I think everyone does, and I think that this is such a lightweight, easy to share format that if you make a better one, the whole world gets to benefit from it. So to me, there's a lot of really like human positive gains to be had here, and that's just super encouraging, Nick.

• 1:02:07Speaker 05

  Yeah, and thank you. Thank you, guys. Yeah.

• 1:02:09Speaker 00

  All right. Well, Nick, thanks for coming on the show. After season two, come back and tell us what people have built and tell us how much you're improving the world because I want to stop working very soon. So I'm hoping that AI gets me there. Thanks, man. Appreciate it.

• 1:02:20Speaker 05

  Thank you.

• 1:02:21Speaker 02

  I like thinking about companies in terms of seasons. You get to talk about it. It's like it's like TV like, man, I can't wait for season two of Trajectory RL. They're gonna really up the stakes.

• 1:02:29Speaker 00

  The thing that really blows me away here, Lon, is the simple fact that we're now seeing essentially a decentralized network designed for ML competition.

• 1:02:38Speaker 02

  Yeah.

• 1:02:38Speaker 00

  Coming together to have the nerds battle it out to write the best sentences in English.

• 1:02:44Speaker 02

  Yeah, it's it's funny that skills are just just marked out. I did not even realize that when I was first teaching them open claw. I thought it was writing code in there. It was like, hey, Claw, here's what I want you to do. First do that. Like, oh, I could have done this myself.

• 1:02:55Speaker 00

  I remember when Anthropic first announced these. I was reading through the announcement. This is back in like, what, mid 25, late 24, somewhere in there?

• 1:03:02Speaker 02

  Sure.

• 1:03:02Speaker 00

  And they were like, a skill dot M G file is a text file with words in it. And I'm like, what am I missing here? This sounds useless. Why would you ever want that? That doesn't do anything. And then it turns out that, one, they were right, now he's wrong, but also the power of the written word.

• 1:03:14Speaker 02

  I think that that. A lot of the power of open claw initially to doofuses like me, like I'm sure the coders got it immediately like why it was valuable, but it was just that. It was finally delivering on the, you can literally just tell the AI what you want and it'll just do it. Like, we'd been promised that for so long. And then you would use open claw and you would just be in your Slack and you'd be like, do this and it'd go, okay. It wouldn't always work, but it would say, okay.

• 1:03:38Speaker 00

  Yeah.

• 1:03:39Speaker 02

  And it would like act like it understood you.

• 1:03:40Speaker 00

  You know what might be a good model? I, we should have kept Ning on for this, but whatever. I'll just say it now before we move on. Have you heard of the, the humble bundle?

• 1:03:48Speaker 02

  Sure.

• 1:03:48Speaker 00

  Model?

• 1:03:48Speaker 02

  Yeah, the, the gaming, like Valve games, if you buy them, you get a bunch, a bunch of indie games for one low, low price and then you can try them all out.

• 1:03:57Speaker 00

  Yeah. You can get like, you know, 15, 20 games for like 10 bucks.

• 1:03:59Speaker 02

  Yeah.

• 1:04:00Speaker 00

  And so to me, like, I love to contribute to projects that I, that I enjoy, things that I really love to use. If you're a metal band that I follow, I, I own several heavy metal Christmas tree ornaments, not because I really need them, but because I wanted to support the bands, you know? So if they did a humble bundle of skills, I would so happily contribute to paying 15, 20, or even like a hundred bucks, frankly.

• 1:04:23Speaker 02

  Well, I, I do, I will say, I noticed how much my skills get better over ti- as I iterate. Like every time I notice something I don't like, I go back and fix the skill to like, make sure that doesn't happen again, vice versa. And so if that, if, if doofus me who's barely paying attention can bring that kind of iteration over time, I can only imagine that people who were really focused on and incentivized to make these skills much better, they could be a hundred X better. I'm only making it three X better because I got other stuff.

• 1:04:52Speaker 00

  You know, Juan, you gotta stop. You gotta stop with the putting yourself down. You're, oh, I'm a doofus. Oh, I'm not a coder. You have been deep in the open claw trenches to the point in which I know the name of your agent, which is a weird thing to know. It feels a little bit too personal.

• 1:05:05Speaker 02

  It's like the everyday Bladestar character for Blade Runner.

• 1:05:07Speaker 00

  But you, you use open claw a lot. You use AI all the time.

• 1:05:10Speaker 02

  You know, I don't.

• 1:05:10Speaker 00

  You've made your own skills.

• 1:05:12Speaker 02

  I, I did, I did use open claw, but my open claw is locked in an AWS rack somewhere and he has a lot of trouble getting out. Like people are very dubious about a bot that's inside AWS. They're like, get out of here, you. So I actually have switched. I'm mostly using Claude Cowork now because it's much easier to just, you're just like, here, take, you're in my notion now. And Claude goes, okay.

• 1:05:35Speaker 00

  Yeah.

• 1:05:36Speaker 02

  Gaff is like, I can't, I can't get it. What are you trying to show me? Can you copy and paste the whole thing?

• 1:05:41Speaker 00

  The same skill in D file, the same skill in D file works on both, which is incredible.

• 1:05:45Speaker 02

  It is incredible.

• 1:05:46Speaker 00

  That's the power of them. All right. Uh, before we go, a couple of other things to note, folks, from the news tickers out there, uh, Angel List just dropped right before we got on air, a new product called USVC, which is a private market fund designed to give individuals, we who have $500, which is the minimum, uh, exposure, Lon, to a number of major names in the world of venture capital startups.

• 1:06:09Speaker 02

  Yeah, I love that you said individuals who have $500 is like, this is an exclusive group.

• 1:06:15Speaker 00

  No, I mean, that's the whole point. It's not. And like, like, I mean, everyone has, well, I'm not going to say that and get made fun of on the internet, but most people can find $500 somewhere. And then they could take part in, uh, venture economics. I got to read a little bit of the prospectus and what I learned is this actually operates a bit like a venture fund. You put money in, you can't take it out.

• 1:06:36Speaker 02

  Right.

• 1:06:36Speaker 00

  There will be some repurchases on a quarterly basis, but mostly you're waiting for exits.

• 1:06:40Speaker 02

  Yeah, I see they have here on the website, the power law. One investment has the potential to generate a higher return than the rest of their portfolio combined. This is why USVC intends to build a bundle, not a single bet. So the idea is even your 500, it's getting spread out. So you're not all in on one thing and then you lose your, you lose your shirt.

• 1:07:00Speaker 00

  Yes. Yeah, I think it's a great idea. We'll have more about it. This is actually one of the two products. Robinhood has a publicly traded venture fund thing. Um, so this does seem to be a growing product category as companies stay private.

• 1:07:12Speaker 02

  I did notice with the Robinhood one, they're, they're kind of locked out of a lot of the most sought after private companies. I wonder if that's going to happen with this as well. Like, like OpenAI, they're not exposed to OpenAI and the Robinhood Venture Fund. And a lot of people were like, why not? That's what I want.

• 1:07:30Speaker 00

  Do you know, do you know where a lot of venture capital funds run their technology? Angel List?

• 1:07:34Speaker 02

  Oh, well.

• 1:07:35Speaker 00

  You know what that means? Angel List has a lot of access.

• 1:07:37Speaker 02

  There you go.

• 1:07:37Speaker 00

  So I'm hoping that this is actually, actually magic.

• 1:07:40Speaker 02

  Yeah.

• 1:07:40Speaker 00

  Frankly, Lon, my, my expectation is, is high for what they expect.

• 1:07:43Speaker 02

  Your expectation is magic.

• 1:07:45Speaker 00

  I'm sorry, high expectations are a gift. They're welcome. Next up, the compute wars continued to absolutely go crazy. Two things of note here for everyone out there paying attention. Lon, first of all, Anthropic and Amazon penned a new deal this week. $5 billion in investment, 5 gigawatts of compute, $100 billion of the spend over the next 10 years, Anthropic to AWS. And maybe, maybe this will solve the Claude crisis in which everyone gets locked out after 10 minutes.

• 1:08:12Speaker 02

  Theoretically, I mean, I think eventually Anthropic's got to be worried about how people will eventually solve it, which is find another model. Like, I feel like they're, they have, they have a limited window here to solve this problem before people are like, ah, okay, I'll try Codex, you know, like it's, it's, the gap is, the gap is closing.

• 1:08:31Speaker 00

  And we're talking about AI timeframes. So whatever you were thinking, divided by 10.

• 1:08:34Speaker 02

  Yeah, exactly.

• 1:08:35Speaker 00

  You know, it's brutal. The other thing, and this came out today, is that Google has two new chips. They make tensor processing units. Don't forget, a scaler is a zero dimensional vector, a, sorry, zero dimensional tensor, a vector is a one dimensional tensor. Tensors have multiple dimensions. Anyways, it matters if you care about data shape versus flatness, but their TPUs are now on generation eight. And they have two different versions, Lon, one built for training.

• 1:08:59Speaker 02

  Yes.

• 1:09:00Speaker 00

  Get this, TPU 8T, and then there's TPU 8I, which is for inference. I think this is brilliant, and I think it goes to show that Nvidia is not going to make all of the money in the world.

• 1:09:09Speaker 02

  Yeah, there's, there's gonna be, I mean, we're seeing, there's so many of these companies now that are working on their own. Isn't there, there's Tranium, Amazon has Tranium. Which they should really work on the name for, because it's just, it's like,

• 1:09:21Speaker 00

  Yeah, it's not, it's inferential.

• 1:09:23Speaker 02

  It's like, it's like,

• 1:09:24Speaker 00

  It sounds like a mineral.

• 1:09:24Speaker 02

  Unobtanium from Avatar, like, go one level deeper on that guy.

• 1:09:28Speaker 00

  We'll go, we'll go get the pickaxe out and figure out what's going on. There's also a lot of companies in the startup world, Etched is working on a LLM, sorry, a transformer specific ASIC.

• 1:09:38Speaker 02

  Right.

• 1:09:39Speaker 00

  For example.

• 1:09:39Speaker 02

  And Cerebras has those like massive room sized chips they're working on, the wafer.

• 1:09:44Speaker 00

  And they refiled to go public last Friday.

• 1:09:47Speaker 02

  Oh, wow.

• 1:09:48Speaker 00

  It's a very interesting return to the markets. And then, I guess, Lon, just one last thing before we go, should we just talk for a moment about? Apple getting a new CEO?

• 1:09:57Speaker 02

  Yeah, Tim Apple is out. John Apple is, uh, is it? I, I'm insisting-

• 1:10:01Speaker 00

  Can we call him Johnny Appleseed?

• 1:10:03Speaker 02

  We have to call the new guy. His name is John Ternus, but I think we should just switch over to calling him John Apple now. I think whoever's the CEO of Apple, you, you get, that becomes your last name. I think that's only fair.

• 1:10:13Speaker 00

  Explain, explain why, why-

• 1:10:15Speaker 02

  Donald Trump messed up one time and called Tim Cook Tim Apple and it's, I, I, I'm not, I literally am not even here to make fun of our president. I just think it's a very funny thing to call the CEO of Apple, uh, Tim Apple or John Apple. So anyway, yes, Apple CEO Tim Cook, uh, he's stepping down as executive, uh, he's up again as CEO and he's going to transition to being Executive Chairman of Apple's Board of Directors, John Ternus, now John Apple. Uh, the current Senior Vice President of Hardware Engineering, he's stepping into the CEO role. I know that a lot of people were very excited that it's a, it's a hardware guy and, and a lot of people are thinking this is going to represent, you know, rather than somebody who's sort of trying to like squeeze as much money as they can out of the Jobs legacy by releasing,

• 1:10:58Speaker 02

  you know, these, these new versions of the classic product lineup. That here's a guy that's going to like rethink the whole company based on, you know, silicon and new devices and where they are right now.

• 1:11:08Speaker 00

  Also, someone with incredibly deep DNA in the world of Apple. I went to his LinkedIn and I pulled this image. Went to school at UPenn, 93 to 97, had four years as a, as an engineer at virtual research. And then since July of 2001, uh, he's been at Apple, which is nearly 25 years.

• 1:11:24Speaker 02

  With him.

• 1:11:25Speaker 00

  And that's an impressive run at one company and just goes to show that in the old days, you could work for one company.

• 1:11:30Speaker 02

  Yeah.

• 1:11:31Speaker 00

  For a while. You didn't get laid off all the time.

• 1:11:33Speaker 02

  I read that he was one of the lead sort of minds behind your new MacBook, your MacBook Neo. He was one of the champions of that, which has been a well-regarded, sort of a rare new Apple product that people like and feel good about. So there you go.

• 1:11:48Speaker 00

  It's, it's magic. It's magic because it's the first Apple product I've ever owned. That if I drop a Dr. Pepper onto it and completely ruin it, I don't have to cry.

• 1:11:57Speaker 02

  I feel like I-

• 1:11:58Speaker 00

  That's very freeing.

• 1:11:59Speaker 02

  I feel like I could drop a Dr. Pepper on my iPhone and it would stand up to that. I don't, I don't-

• 1:12:04Speaker 00

  Oh, I meant something with a keyboard attached to it.

• 1:12:05Speaker 02

  Oh, okay. Yes, yes. Fair enough. Yes. Wait.

• 1:12:08Speaker 00

  Like if I, if I torch my, like my N3 Max Pro Viper, I'll be sad.

• 1:12:11Speaker 02

  I need, I, I know we're wrapping up. I need to stop you right there. So what about the MacBook Neo? If you dropped a, if you poured a Dr. Pepper on it, how would it be fine? I don't understand.

• 1:12:22Speaker 00

  Oh, I don't, I don't care. It's cheap.

• 1:12:24Speaker 02

  Oh, it's so cheap. I understand. Okay. I thought you were saying something about it like a new kind of aluminum that repairs Dr. Pepper?

• 1:12:31Speaker 00

  No, no, no. No, my, my, my, my pink MacBook Neo does not have special anti-soda properties to it.

• 1:12:38Speaker 02

  No, you're just saying you could afford to buy another one because they're not the most expensive thing in the world.

• 1:12:43Speaker 00

  I paid like 600 bucks for it, which for a laptop usually means you're getting some from HP, right? That's plastic and terrible and has gunk all over it.

• 1:12:53Speaker 02

  This is the infamous company that, that, there's that video of Ternus on stage introducing the $1,000 computer stand. So your, your, your, your, uh, your new MacBook costs less than that stand.

• 1:13:04Speaker 00

  Yes. Well, there is two markets for Apple products. There's sane people and insane people. And you know what? They sell the, sell all types. Um, one quick note here from our producer, Salat, who says that Dr. Pepper tastes like medicine. Salat, you're fired.

• 1:13:16Speaker 02

  I love that.

• 1:13:16Speaker 00

  And with that twist, we'll be back on Friday. We'll see you guys then. Lawn and absolute treats. We appreciate everyone tuning into the live show. The NoD Gang, we're back on Friday noon, Texas time, 1:00 PM Eastern. Y'all are lovely. See you then.