How Bittensor (TAO) is Tokenizing Intelligence (Mark Jeffrey)
Mark Jeffrey sees Bittensor as “the third great coin” after Bitcoin and Ethereum because it makes mining—not smart contracts—programmable. His thesis is that TAO can subsidize a Cambrian explosion of AI and digital commodities just as Bitcoin incentivized computing resources and Ethereum bootstrapped DeFi: “It worked once. Let’s do it again for AI.”
The catalyst bringing Silicon Valley attention is Templar subnet 3’s claimed decentralized training of a 72-billion-parameter frontier model. Training normally requires tightly co-located GPUs because of constant inter-GPU communication. Jeffrey said he could not explain Templar’s technique, but considered solving that communication problem significant. The announcement drew 2 million views, while Chamath discussed it with Jensen. The host framed the result as moving the objection from impossible to merely too small.
TAO’s design ties subnet creation, tokens, and participation directly back to the base asset. Bittensor has 128 subnets, each with a 21-million-token limit, and Jeffrey says subnet tokens can only be acquired by staking TAO into chain-native liquidity pools—making them “rehypothecated TAO” rather than economically detached app tokens.
Jeffrey’s five-month-old fund ultimately wants to own 1% of all TAO while underwriting subnets like startups rather than buying memes. Announced investments include Ridges subnet 62, Targon subnet 4, Hippius subnet 75, and Score; selection hinges on product maturity, team quality, and whether token value rises with actual usage. Hippius is an example: storage providers must stake its token and can be slashed for poor service.
Jeffrey argues subnets can challenge centralized labs because global contests eliminate payroll, geography, and “dead weight.” Ridges offers 256 mining slots, rewards a daily winner with roughly $25,000-$75,000 of subnet tokens, publishes the winning result, and restarts the competition. He claims this “most ferocious form” of capitalism produced a Claude-and-Cursor competitor for $1 million-$2 million, priced around $29 monthly versus more than $200.
The setup combines powerful scarcity with substantial execution risk: roughly 70% of circulating TAO is staked, while regulation, a chain hack, or bad protocol design could break the thesis. Jeffrey compares post-first-halving TAO around $300 with early Bitcoin and expects the subnet count eventually to rise from 128 to 256, probably within the next year, adding demand when creating one already requires $100,000-$1 million of TAO. His non-advice target is $3,000 “by the end of this year” if TAO merely follows Bitcoin-like dynamics; Barry Silbert’s cited 500x possibility was explicitly “not this year.”
1. TAO makes Bitcoin’s mining engine programmable
Jeffrey grounds his conviction in experience across several cycles: he bought Bitcoin on Mt. Gox around $250, interviewed Vitalik on a podcast before the Ethereum ICO and got in, and watched DeFi Summer unfold. Within months of reading Sammy Keseb’s Messari report, he concluded TAO was “the third great coin.”
His analogy is architectural: Ethereum took Bitcoin’s small smart-contract capability and expanded it into a “world computer,” enabling ICOs, decentralized lending, exchanges, and stablecoins. Bittensor instead expands Bitcoin’s mining side, making incentives programmable across AI and other digital commodities.
Jeffrey sees tokens as the missing ownership layer in conventional open-source development. A Linux contributor may receive no durable stake, while an early Bitcoin miner received coins and therefore participated in future upside: “It’s not stock, but it’s like stock in the sense that it’s ownership.”
2. Templar changed the debate from impossible to scalable
Templar subnet 3’s headline result was a decentralized training run for a 72-billion-parameter frontier model. Jeffrey cited it as the world’s largest decentralized training run and said it proved that the approach could work.
The technical objection was latency: model training requires intensive communication among GPUs, which is why systems such as Elon Musk’s Colossus use roughly 200,000 GPUs. Jeffrey’s honest limitation was: “I couldn’t speak intelligently to the technique,” only that Templar had solved the communication problem.
The host framed the shift as critics moving from “decentralized training is impossible” to “it’s too small.” Jeffrey agreed the result was significant, while the host described it as working in a “petri dish” with scaling left to solve.
Mainstream attention followed: the announcement received 2 million views, Chamath raised it with Jensen, and AI figures such as J.J. discussed Bittensor despite not being crypto advocates. Jeffrey’s explanation: Bittensor resembles what OpenAI “should have been, but did not become”—open AI with native contributor ownership.
3. Chain-native economics bind every subnet back to TAO
Bittensor’s 128 subnets each run a different contest and issue their own token, also limited to 21 million, into a chain-native liquidity pool. Jeffrey stressed that this exchange mechanism is “inside” the chain, not an application layered above it.
The only route to subnet tokens, in his telling, is staking TAO into those pools. Unlike tokens built over Ethereum or Solana without a necessary economic link to the gas asset, subnet tokens are “tied at the hip” to TAO and amount to another form of it.
The host challenged how a subnet could beat billion-dollar AI labs. Jeffrey answered with Ridges: 256 entrants worldwide submit software-agent improvements, the winner receives roughly $25,000-$75,000 in subnet tokens, the result becomes public, and the contest begins again.
Contributors need not relocate, accept salaries, or remain indefinitely; they can compete from Turkey or India and sell their rewards immediately or retain exposure to Ridges. “Nobody gets paid unless they win,” Jeffrey argued, calling contest economics the “most efficient” and “most ferocious” form of capitalism.
4. Product economics—not subnet hype—drive the fund’s selection
The five-month-old fund’s stated ambition is to accumulate 1% of all TAO, echoing the Winklevoss twins’ Bitcoin position. It evaluates subnets like startups: product quality, market maturity, team strength, and a token whose value is more than “just a meme coin.”
Ridges subnet 62 is building a Claude-and-Cursor alternative that Jeffrey says beats them on SWE-bench tests while charging about $29 monthly versus more than $200. He claims it achieved this with “a million or two dollars,” compared with the hundreds of billions he associates with what Claude and Cursor had done.
Targon subnet 4 focuses on confidential computing and inference; Intel recently published a paper with the project. Hippius subnet 75 supplies decentralized storage at a claimed 1/400 of competing prices. Providers stake Hippius tokens to gain the right to mine the subnet, supply storage, and face slashing when service is unreliable.
Other examples broaden the thesis beyond language models. Jeffrey likes Nova for AI-driven pharmaceutical molecule discovery, while Score applies computer vision to sports scouting, offering European teams unable to afford large AI systems comparable “moneyballing” capabilities at one-tenth the cost or less.
5. Regulation and protocol mistakes are the credible bear cases
Asked where the thesis fails, Jeffrey led with regulation: governments might prohibit unlicensed AI or reserve it for approved operators such as OpenAI, Google, and possibly Grok. He doubts Bittensor itself could be shut down, but an American crackdown could make funding subnets illegal for his firm.
Ordinary crypto failure remains possible—a chain hack or a damaging protocol change. Proposed chain-native lending and shorting could let smaller holders bet against bad subnets or offset large holders continually supporting their own subnet, but Jeffrey cited ThorChain lending becoming insolvent and threatening the broader chain as the cautionary example.
He has nevertheless repeatedly changed his mind after worrying about decisions associated with Cons: “I’ve gone through like six worry fests,” only to decide two weeks later that Cons was right. His confidence is high, but his discussion preserved uncertainty about lending’s system-level consequences.
The bull case compounds scarcity: TAO had completed its first halving and traded around $300; launching a subnet consumes roughly $100,000-$1 million of TAO; a probable expansion from 128 to 256 subnets, likely within the next year, would add demand; and approximately 20% of TAO was subnet-staked plus another 50% staked on root.
Jeffrey therefore considers $3,000 TAO by year-end “pretty conservative” if it does only what Bitcoin did after its first halving, while emphasizing that this is opinion, not financial advice. He also cited Barry Silbert’s suggestion that TAO could eventually rise 500x, carefully preserving the condition: “Not this year, but just for fun.”
Verification Notes
- The transcript names Jeffrey’s firm as “Stillmark Capital” early on and “Still Core Capital” at sign-off, with “Criterion” also mentioned during the investment discussion; the digest avoids resolving that discrepancy.
Full transcript
We have Mark coming on. He wants to tell funds with Jason Calacanis and Rob. Really sharp guys. Obviously everybody knows Jason and he's pretty like generational. I don't know. I heard about a pod. I I was really into it. He's a really sharp guy and so he's going to come on. He can talk about crypto, Tao, all of it. All right, let's get it. Boom.
Mark Jeffrey, welcome to the stream, man. How are you?
I'm doing well, sir. Thanks for having me.
Likewise. Thanks for coming on, man. It's an absolute pleasure. We're all kind of all over the place. There's a lot happening. We're talking Trump and geopolitics. We haven't been doing a lot of crypto, but over the last 2 or 3 weeks, Bittensor TAO has been all over my feed. It's honestly been refreshing to tap back in, talk about some crypto, and talk about everything going on in that world.
Happy to have you. Welcome. Do you want to start with a quick introduction to who you are, and then we can talk about some fun market stuff?
Sure. I've been kicking around for about 30 years doing tech companies. I'm a little older, and I founded my first company in 1995. I was an engineer to begin with, so I was around for the dot-com boom and bust and worked with Jason Calacanis in those days. That's how I know him from that era.
Then I founded a bunch of companies and ended up being CTO at a company that Jason founded. Elon was on the board, so I used to have to give him a report once a quarter.
Really? Directly to him?
Yeah, when he showed up at the board meetings. He was like, "Okay, Mark. Okay, CTO guy. Tell me what you're doing." He'd pull it apart, of course, because it's Elon. I'd have to dance and answer questions.
Sequoia was on the board, too, so we got some face time with unbelievably amazing people. It was like Warhol's loft. All these characters came through. You have to remember, back then Elon wasn't Elon. He was just a PayPal guy. He was successful, but he wasn't the Messiah. We didn't know all the things that were coming, so it wasn't quite like addressing the throne the way it would be now.
Were you conscious, at the time, that Elon was actually going to be the GOAT, or not really?
No. I was very conscious of the fact that he was a very smart guy, but so were the Sequoia guys, and so were a lot of other people. I also worked briefly with a guy named Travis Kalanick, who founded Uber.
Whoa.
Before Uber, Travis had a company called Red Swoosh. This was after the dot-com boom and bust, so I was looking around for a job, and there weren't many jobs. Travis said, "Hey, come work for me." I went and worked at Red Swoosh for about a year and a half. It was just me, Travis, and 2 or 3 other guys in a room for about a year and a half.
There’s a great line in Amadeus where Salieri meets Mozart and doesn’t know what he looks like. He says, "I played a game with myself. Is genius visible on the face?" For me, the answer was no. I was hanging out with Travis every day, and I didn't realize who I was hanging out with until later.
We might have to work on this identifying-talent thing. I don't know.
Yeah.
You ended up with that. That's crazy lore. What a story. That's awesome.
I'll just finish it real quick. I got into Bitcoin in 2013, hence the Bitcoin books behind me. I wrote a couple of Bitcoin books, and then I was in the Ethereum ICO. I interviewed Vitalik on a podcast right before it happened, so I got in on that. I was there for DeFi Summer. I've been kicking around in crypto basically since 2013.
Okay, cool. You're super-early Bitcoin, and you're running—
And then today, right? I have to talk about today. Right now, I'm a partner at Stillmark Capital, and we're a fund investing in Bittensor subnets.
Beautiful. That's kind of a crazy move. We see a lot of Bitcoin funds and ETH funds. We had the DOT mania for a little while, which got pretty far out on the risk curve: Berachain, DOT, AVAX, and Hyperliquid.
I'm not sure I've seen a Bittensor fund like this. It's a unique ecosystem because you have this subnet ecosystem, which we actually haven't talked that much about on the stream. How did you get TAO-pilled, and why are you working on this?
It was about 2 years ago. I read a report by Messari, written by a guy named Sammy Keseb.
Oh, hell yeah. He's been on the stream.
Okay, so you know him. He himself is also doing a Bittensor fund. His paper started me suspecting that there was something very important going on here.
As I said, I was there early for Bitcoin in 2013 and then again for Ethereum. The more I read about it and understood what was going on, the more I started gaining conviction, over a couple of months, that this was the third great coin: Bitcoin, Ethereum, and then this.
This is the most important thing that's happened since Ethereum. Having bought my first Bitcoin on Mt. Gox for $250 back in the day and seeing how that spiraled up, and then seeing the same thing with Ethereum, my opinion quickly became: it's going to happen again, and it's going to happen with this Bittensor TAO thing.
How do I get as much TAO as possible? How do I become like the Winklevosses and own 1% of Bitcoin? Of this TAO thing. That was the thinking.
I have my own stack from my Bitcoin and Ethereum adventures, but how can I get more? Running a fund was the best way to do that. I had a couple of partners who were thinking about doing it approach me, and then I approached Jason about investing in the fund. Jason Calacanis came back and said, "Can I be a partner in the fund?" We quickly said yes to that.
Why is it the most important crypto since ETH?
If you look at what Bitcoin did and what Ethereum did, Ethereum looked at Bitcoin and said, "This is super interesting, but this little tiny smart-contracts thing—let's blow that up. Let's make a Turing-complete machine. Let's make the world computer," as Vitalik was calling it.
It was a great idea, and it led first to the explosion of ICOs and then to DeFi Summer. We got decentralized lending, decentralized exchanges, and stablecoins. There was this whole rich Cambrian explosion that happened inside the Ethereum and EVM ecosystem.
What Bittensor does is take the other side of Bitcoin—the mining side—and make that programmable. It allows the Bittensor chain to subsidize all these AI and other digital commodities into existence and lets this whole other Cambrian explosion happen.
I fully buy into the theory that this was going to happen, and it started to happen. The reason you've been hearing about Bittensor so much is that the successes are now becoming obvious to the rest of the world for the first time.
Templar Subnet 3 just announced that it completed a 72-billion-parameter training run of a frontier model. It was fully decentralized.
So, what does that mean? You and I, if we want to make a new ChatGPT or a new Grok, have to have 200,000 GPUs, which is what Elon has.
Disgusting. Colossus.
Imagine a Napsterized Colossus coordinated and incentivized by the emissions in a Bittensor subnet called Templar Subnet 3. A lot of people thought it couldn't be done. You could not do AI training in that fashion. Subnet 3 just proved they could do it.
It got a huge amount of attention—2 million views on the tweet. They talked about it on the All-In podcast. Chamath brought it up on the All-In podcast while talking to Jensen, and that clip went viral.
The CEO, or one of the co-founders, has talked about it twice now and put Templar and that training run in the paper he wrote, calling it out as, "This is the world's largest decentralized training run. We didn't really think this was possible. Now that we know it is, in the future…"
The other thing to remember about this is: what is Bitcoin? It's a lot of things, but it's also Earth's largest supercomputer. It's 500 times larger than its nearest competitor.
What do we need to train AI? Earth's largest supercomputer. So, how did Bitcoin grow? It incentivized itself into existence. It convinced all these people to donate CPU and electricity to try to mine these coins.
Let's do that. It worked once. Let's do it again for AI and all these other projects that need intense amounts of GPU.
One of the tweets I saw and liked was from a guy who also used to work at Messari. He tweeted in response, basically saying that the idea of a decentralized training run was initially thought impossible. Now that it's been done, the discourse has switched to saying it's too small, which is a real step-function forward.
On a different note, one of my questions for you is: We trade crypto. I trade a lot of crypto, and not all crypto is garbage, but you trade a lot of things based on attention. Not fundamentals, not P/E ratios, not forward earnings—a lot of attention.
What was interesting about Bittensor, and why I’ve been talking about it, is that I think it’s the first crypto in a while that has gotten this mainstream tech and Silicon Valley attention. Obviously Jason Calacanis, but then you see Chamath talking about the Templar run to Jensen, and you see—was it Jack Joseph or Joseph Jack, one of these AI guys?
J.J.
J.J., who’s not a crypto person. If anything, they’re anti-crypto. They’re like, “Okay, cool. TAO.” Why are these tech-adjacent, anti-crypto people talking about Bittensor? What just happened?
I think they realized that Bitcoin’s success could potentially be replicated for AI—for doing open-source AI. Bittensor is, in a lot of ways, OpenAI. It’s what OpenAI, the company, should have been but did not become.
Part of the reason for that is that with open projects, like open software projects—Linux, maybe, or something like that—the early contributors don’t get anything. There’s no ownership layer. Bitcoin was the first open-source project that had an ownership layer from day one.
If you were just some kid in your bedroom mining coins in 2010, you got coins, which meant you had an ownership layer. You were invested in Bitcoin’s success and its future. It’s not stock, but it’s like stock in the sense that it’s ownership.
By making mining programmable, Bittensor is basically saying, “Let’s do Bitcoin again.” It has the same economics: 21 million coins in the TAO token, the base layer.
It’s also true that there are 128 subnets, each one a different AI project with its own mining contest. They’re all totally different, but each of those subnets also has a coin. Again, those are limited to 21 million.
Just like Bitcoin, they’re emitted into a liquidity pool. The only way you can get subnet tokens—and this is extremely important—is by staking TAO into the liquidity pool, which is like a Uniswap system baked into the chain. It’s not an app on top; it’s inside the chain.
What that means is that all of the subnet tokens are rehypothecated TAO. It’s another form of the same thing. The subnet-token pools can grow and shrink depending on how well that subnet does in the marketplace, just like any marketplace.
But the subnet token itself is very different from Ethereum, Solana, and everything else. They build smart contracts and tokens on top of the gas token, but there is no economic connection. These are tied at the hip. It’s a very different dynamic.
If you look at Bitcoin and say, “Bitcoin incentivized Earth to donate absolutely insane amounts of GPU, CPU, and electricity to mine with these incentive economics and contest economics,” it worked really well once. It should work again for this other thing, which requires a lot of GPU, otherwise known as AI.
I think people are cluing into that narrative. They’re like, “Oh, yeah, we’ve never tried to do it again. Capitalism worked once. Let’s try it again.”
Yeah, let’s run it back. What are you investing in? How are you figuring that out? The subnet scene has a lot there. It took me a while to understand Bittensor, and then I was like, “Geez, there’s a lot under the hood.” What are you guys investing in? How are you figuring out how much capital to allocate to what? How does the fund actually work?
Our goal is to raise enough to own 1% of all TAO. Again, just like the Winklevoss twins, that’s the game plan.
We’re only 5 months old, so it’s early days. We’ve raised a decent amount so far. We haven’t made any announcements yet. We will at some point, but it’s not quite time yet.
However, we have announced that we’ve invested in a couple of subnets. One of them is Ridges, subnet 62, which makes a Claude and Cursor killer. It’s beating them on the SWE-bench tests, and it costs $29 a month versus more than $200 for Claude and Cursor. It’s about 1/10 the cost.
We’ve also announced an investment in Targon, subnet 4, which is confidential compute and inference. Intel just published a paper with them that was announced a couple of days ago.
I suppose I think I saw you post it.
Yeah, I did.
We’ve also announced an investment in Hippius, subnet 75. They’re decentralized storage, which would seem like it has nothing to do with AI, but AI needs a lot of storage to crunch things. You have to put the data somewhere at scale.
Hippius provides storage for literally 1/400th the price of any other competitor, so it’s extraordinarily cheaper.
One of the things we look for at Criterion is obviously a great product. We look for some market maturity, very much like you do when investing in startups. We also look at how the subnet token is going to grow in value.
If the subnet token is just a meme coin for that subnet, that’s not good enough. With Hippius, you have to stake Hippius tokens in order to gain the right to mine the Hippius subnet. How do you mine the Hippius subnet? You supply storage to Hippius, and you get slashed if you’re not performing. You have to be responsive and do all that stuff.
It deterministically ties the value of the Hippius token to a rise in usage and revenue of Hippius as a product. We like that, and the team was great. We love the people behind it.
Other things that I like include Nova, which is AI pharmaceutical molecule discovery.
Okay. They were just on This Week in Startups, right?
Yes, they were just on This Week in Startups yesterday. So, yes, we like them.
We’ve also invested in Score, which is computer vision.
Okay.
It’s not enough just to slap a camera on an AI. The AI has to understand how to see. What is that blob walking around? Oh, that’s a human.
Yeah, what am I looking at?
Yeah, this is a car. It has to understand perspective and sight, just like a baby learns how to see. Babies can see, but they don’t know how to see yet. They don’t know how to map the input to the world.
We really like Score. Score started out by using its visual mapping for Moneyballing sports.
Moneyballing, yeah. I followed the first one; it just took me a second.
Yeah, I reversed it.
They basically went to European soccer teams that couldn’t afford these big AI scouting systems. Because they can provide the same thing for 1/10th or less of the cost, all of a sudden amateur sporting teams could afford AI Moneyballing and AI visual scouting of great players.
Those are just a handful of subnets out of the 128.
Okay, so you’re really deep on a lot of these.
Oh, yeah. I run a podcast called Hashrate. I’ve interviewed most of these people at least once, from most of the subnets.
Nice. I want to watch a couple of the ones you’re invested in.
On the LLM side specifically, why would it be possible for a subnet to theoretically beat Claude or Cursor—one of these major AI labs building out either LLMs or some sort of organizational system? Why would a subnet be able to compete with these billion- or trillion-dollar companies?
Let me explain it in Bitcoin terms first.
Cool. Rip it.
Imagine Satoshi didn’t do this decentralized thing. He just woke up one morning, went to Sequoia, raised a bunch of money, and said, “Okay, we’re going to make this alternate-universe SWIFT system and this alternate-universe digital gold. We have to buy a lot of servers all over Earth to run this network.”
Imagine the insane amount of cash it would have taken. On top of that, you’d have to hire in Silicon Valley, because that’s where your offices are. If you’re an engineer, you have to move there. If you’re dead weight, you might be able to hide in the company for a long time because there are tons of engineers.
Instead of doing that, in the Bittensor world the proposition is: We’re not going to hire anybody. We’re just going to set up a goal—the thing we want people mining for.
In this case, with Ridges, it’s: “I want you to make a software agent capable of beating Claude and Cursor.” There are 256 mining slots, so there are 256 possible entrants into the contest. They all submit their entries, usually once a day.
Anyone from all over Earth can compete.
Mhm.
There’s no HR department, there are no salaries, and you don’t have to be geographically anywhere specific. You can be in Turkey or India.
You get Earth’s best minds competing against each other, and they don’t have to take a job. They can just do this until they’re bored and leave.
If they win, they win—it depends on when you look, but it’s somewhere between $25,000 and $75,000 worth of subnet tokens. You can sell them immediately, or you can hang on to them because you think Ridges might blow up and be worth as much as Claude or Cursor down the road.
Because of this fierce competition, with Earth’s best minds trying to one-up each other every day, at the end of each day the winning result is published.
So everybody benefits from the cleverness of the last winner. Right? And then it begins again. You cannot beat contest economics that have financial and ownership incentives that are worldwide. That’s what it turns out, right?
With only a million or two dollars, Ridges has surpassed what Claude and Cursor had done with hundreds of billions within a very short couple of months. This is the most efficient form of capitalism ever invented. It’s the most ferocious form. Nobody gets paid unless they win. Only the winner gets paid, so there is no dead weight.
Can you explain why the decentralized training run was so significant?
Yeah. When you train an AI model, the reason why you have to have 200,000 GPUs co-located is because of the intercommunication between the GPUs. They’re basically building a neural network, so there’s a lot of cross-communication that has to go on in order to build an accurate model while you’re training it.
The concern with a decentralized model is, “Oh, well, these neurons, if you will, are all over the Earth.” It’s too slow. They have to be co-located in order for it to make sense. I couldn’t speak intelligently to the technique other than to say that the problem they solved was the intercommunication. That was significant.
Yeah, so they proved it works in a Petri dish. It’s like, “Well, it worked in the Petri dish. It’s just about scaling up now.” I think they can do it. That was actually a good explanation.
What is the bear case for TAO? In what scenario does this not work and your investment in the fund is just, “We messed up. We were close”?
There could be a new regulatory regime that arises which seeks to kneecap AI or centralize it. You’re already seeing Bernie Sanders out there saying we’ve got to stop building data centers.
By the way, he did the Claude interview, and it was ridiculous.
Yeah, yeah, yeah. It reminds me of those cartoons from the 1900s, when electricity first came around and a bunch of people were like, “Electricity? We’re all going to get electrocuted and die.”
Yeah, exactly. Every 100 years, we go through one of these.
Nonetheless, there are people who could come to power who basically say AI is illegal unless it’s licensed by a national regulator. Maybe only OpenAI, Google, and Grok. Maybe not Grok, because we don’t like Elon. Maybe only licensed AI will be allowed.
That’s a big threat, probably, to everybody.
Yeah.
Could they shut down Bittensor? Probably not. Could they shut us down? Yes. If this was in America, that would affect us, because all of a sudden maybe funding these things would be illegal. I don’t think that’s very likely at this point, but that’s always a danger.
Then there are the normal things, like a chain hack.
Yeah, yeah, yeah. A disaster on-chain or something like that.
I think the regulatory one is really the biggest one that worries me. The other thing is, if we do something stupid in terms of developing new capabilities that adversely affects the way Bittensor operates.
For example, there’s now talk about putting lending and shorting directly on-chain, the same way Uniswap is baked into the heart of the chain. It’s not on top of it; it’s inside of it. There are now talks underway, as of last week—you just had Cons on the show—about having lending that would enable shorting baked into the chain, allowing people to bet against subnets they think suck.
Right now, there’s no way to do that. If somebody has enough TAO to continually keep buying their own subnet, there’s nothing you can do about it. But if there’s lending and shorting, little guys can offset that with bad sentiment, which might be the correct answer. It might be a crappy product, and the chain should be able to vote with its feet, if you will.
This would enable little players to compete against the bigger ones. However, do you remember what happened with ThorChain? Thor Lend? I don’t know if you were around for that.
Yeah, kind of. I used to hold RUNE. Ticker RUNE. I love RUNE. I used to hold RUNE back then.
Yeah, I’m still a big RUNE fan. But for a period of time, they enabled lending on the chain, which became insolvent and threatened to bring the entire chain down.
Wow.
Through baking lending into the chain, right? So things like that worry me a little bit. So far, Cons has not steered us wrong at all, and I’ve been worried about things that were not worth worrying about.
Cons’s solution to these problems tends to be very good. He has never let me down once. I’ve gone through six worry fests where I’m like, “Oh my God, Cons is making a mistake. He’s totally wrong.” Then, 2 weeks later, I’m like, “No, he was totally right. Look what happened.”
Is he in charge? Is he the primary—
Well, he used to be. He used to be the CEO of the foundation. He has stepped away from that now.
Got it.
I could be wrong. I can’t speak intelligently to this because Cons described it, but he has influence and could push it forward.
Yeah, yeah, yeah. The foundation is really the one driving all this now. Got it. Who runs the foundation?
It’s a bunch of early TAO people. I actually don’t recall exactly who’s in charge of that.
Got it.
It’s a lot of brainiacs. They sit up in the tower where these decisions are made, and I’m down in the subnets. I talk to them every once in a while, but not really that much.
Near the end here, can you share a price target for TAO?
I’ll tell you what I think. Not financial advice, but I will tell you what I think because I’ve said it before.
I was around in the early Bitcoin days, and I watched Bitcoin go from around $200 to $1,200. Then it got scared, went back to $600, and all the way back down to $250. It sort of did this bobble thing. At some point, it jumped up to $3,000 and then $10,000. All of that happened within the first year after the first Bitcoin halving, around 2013 or 2014.
Bittensor just had its first halving.
Ah, because you’re looking at it on that halving scale.
I’m looking at it from a couple of dimensions, but halving is absolutely one of them. It’s 2013, if you will, in the Bittensor world. What is its price? It’s around $300, and it’s sort of bobbling around $300 at the moment. It’s exactly like Bitcoin.
On top of that, you have the subnets. To make a subnet requires TAO. How much TAO? Between $100,000 and $1 million worth of TAO, depending on when you look and how much demand there is.
There are also going to be more subnets at some point, probably in the next year. The number is going to go from 128 to 256. That alone is going to create a giant amount of demand for TAO. James Altucher did an analysis of that, and he said, “Oh my God, that alone could drive it up to several thousand dollars,” never mind everything else.
Then you have staking TAO into subnets to get subnet tokens. 20% of all TAO that’s in circulation is currently staked within subnets. Another 50% is staked on root, which is kind of the lazy way to stake and get some rewards. Roughly 70% of it is staked, so it’s not moving around.
You’ve got things which cost TAO and which cause you to stake TAO. Bitcoin doesn’t have that. In addition to the Bitcoin-like dynamics, you have Ethereum-like dynamics. I think all these things are going to start compounding at some point.
I think it’s pretty conservative to think that, if it does only what Bitcoin does, we’ll see something like a $3,000 TAO by the end of this year.
Whoa.
That’s a conservative bet. It’s only my opinion, but still, of course, we are positioning ourselves accordingly based on thinking that.
If you listen to Barry Silbert speak, you become a Bitcoin billionaire. He recently said at a Bitcoin conference that he thinks Bittensor TAO could 500x. It has that kind of potential. Not this year, but just for fun.
I respect someone who comes on and gives a price target. That was a sick price. Dude, I appreciate you coming on. We should get Jay Kell on at some point.
Yeah, he might do it. Every now and then, he’s getting more excited about TAO, as you’ve noticed.
Yeah, maybe we’ll set it up and rip it. I appreciate you coming on. As a sign-off, where do you send people if they want to learn more about it, follow what you’re doing, or watch the interviews you’ve done with founders on the subnets? Where can people learn more about everything you’re doing?
I’m at Mark Jeffrey—J-E-F-F-R-E-Y.
Hashrate is the name of the podcast where I interview all the subnets. Most of my views are on X, but I also have a YouTube channel that replicates them. Just search for Mark Jeffrey, and you’ll find me. The company is called Still Core Capital, so stillcorecapital.com is for accredited investors only. But if you’re curious about what we’re doing, go there.
Sick. Mark Jeffrey, dude, it’s an absolute pleasure. I appreciate you coming on. It was a blast. It was fun to do Cons, then rip you. It was awesome, man. Thanks for the time, bro. I really appreciate you.
My pleasure. Thanks, dude.
All right, have a good one, bud.