Transcript: Tommy Eastman: Own Your Intelligence Stack

Tommy Eastman [0:07] You've had a dynamic where money's become freer than free. Let me talk about a Fed just gone nuts, all, all the central banks going nuts. So it's all acting like safe haven. I believe that in a world where central bankers are tripping over themselves to devalue their currency, Bitcoin wins.

Marty Bent [0:25] In the world of fiat currencies, Bitcoin is the victor. I mean, that's part of the bull case for Bitcoin. If you're not paying attention, you probably should be.

Tommy Eastman [0:34] Probably should be.

Marty Bent [0:35] Probably should be. I've been, uh, I've been very much looking forward to that. I was very excited when we first talked a couple weeks ago because I've been using, uh, your product for 4 months now and it's changed my life. You saw me when you walked in here. You thought I was on the phone. I was talking to my Hermes agent.

Tommy Eastman [0:52] Talking to your Hermes agent. Better than talking to somebody, some would say.

Marty Bent [0:56] I like the human, I like the human element. Okay. I do like talking to my wife, Greg, who's off camera here. He's okay to talk to every once in a while. But, uh, it's, uh, it's changed how I work pretty, pretty quickly. I mean, I'm 35. I've been doing TFTC for almost a decade now, and within 6 months, my whole workflow has changed. And Hermes is a critical part of that.

Tommy Eastman [1:21] Yeah.

Marty Bent [1:22] What— let's take a step back and talk about you personally, how you ended up at Noose Research, which built the Hermes agent. Um, you were in the Bitcoin industry, the crypto industry at Foundry before this, and that's— I mean, that's a whole nother conversation. I think it's really interesting how a lot of these up-and-coming AI companies are seeded with people that have been in the Bitcoin and crypto industry before.

Tommy Eastman [1:48] Yep.

Marty Bent [1:48] But how did you end up at Noose? What drew you to it? And what have you been doing there since you got there?

Tommy Eastman [1:56] Yeah, so I was at Foundry, touched the Bitcoin stuff a fair bit, but was really focused on distributed and decentralized AI there. I just thought that AI, obviously an incredibly powerful tool, very important that we get the ideological part of AI shaped correctly. That was my first real exposure to that thinking about the importance of AI for people, for the individual, the sovereignty that AI enables. I didn't really like a lot of the kind of first manifestations of that, like the first projects that kind of tried to champion that. I wasn't that impressed with. I found Noose eventually. They were focused on post-training open models, um, to make them more pliable, more human-like.

Tommy Eastman ⋮ This was when Meta was— the Meta models were state-of-the-art, right? The LLaMA models. Um, I, I quickly found that the team was just incredible. One, very ideologically driven, right? They Like, at Noose, we truly believe that this— the ability to own your intelligence stack is the most important technological innovation that we've ever faced as humans. But also that the team was just incredibly sharp. Like, everybody at Noose is just a killer, in love with AI, very driven. It's just an incredible incredible experience. And yeah, for me, I focus on a handful of things. We all kind of wear a bunch of different hats, right? We're still pretty small, pretty grassroots.

Tommy Eastman ⋮ But so I touch a bunch of stuff on the product side, onboarding enterprises, and manage all of our compute relationships as well. So we have our managed product, which is News Portal, which powers— which can power Hermes Agent and powers Hermes Agent for a lot of users. So managing all the inference and tools behind that.

Marty Bent [4:06] So let's take a step back and basically explain Hermes. Let's focus on Hermes specifically. And let's, let's, because we've had this conversation off air a couple of times now, but speaking to the person who thinks that the crème de la crème of their interaction with AI is opening ChatGPT and hitting chat and and thinking that they're getting an experience. What does Hermes bring to the table and how should people view the Hermes harness and how to utilize it?

Tommy Eastman [4:37] Yeah, well, that's the incredible piece, right? Is that we're so early. We feel like AI is everywhere and everybody's talking about AI, but there's only a small slice of people actually using AI. And then the vast majority of that slice of people are just using AI basically as advanced Google, right? Google on steroids. Like my mom loves Perplexity. She uses Perplexity all the time, but she's basically just, she likes it 'cause it's Google, but a little nicer. So where you start, where you make that jump from AI chatbot to agentic AI is when you start to enable actual autonomy. So these agents start to actually be able to make some decisions for you and carry out tasks without you having to sit there and monitor them 24/7.

Tommy Eastman ⋮ You can go and have an agent, you know, book reservations for you. You can have an agent look at data that you have and build dashboards. You can start to really automate real tasks. At Noose, we use it for a bunch of different things ranging from, you know, managing our CRM of enterprise customers to taking ideas that we have for content generation and working through a whole creative pipeline to create our end product. Why Hermes Agent itself is, I think, very special, 2 major reasons. One being that, I'll say 3 major reasons. One, the first being that it's very simple to use. It really just works.

Tommy Eastman ⋮ I think a lot of open-source projects end up with this issue where the repo gets bloated. They wanna be inclusive of everything, But we've taken a stance where, yes, we want Hermes Agent to be able to bend to your will and be completely pliable, but that it's really important that we maintain the sanctity of that repo and are somewhat opinionated in what kind of exists in that core repo to protect the user experience. So it working out of the box is a huge reason why it's been successful. 2 is the memory piece, the self-evolution piece. So as Hermes Agent, As you use Hermes Agent, you'll notice marked improvements in the quality of output over time.

Tommy Eastman ⋮ And this is a really important piece because I think where people end up frustrated and what prevents people from using ChatGPT in autonomous ways is you can't do tasks reproducibly with the same results, right? So you ask chat to go do a task, it tries to do the task, It, it might figure it out the first day, and then the next day you have it do the same task and it can't figure it out, right? And it's a super frustrating experience. Hermes Agent stores the primitives of that path where it found the right solution and then recalls them every single time. So if you figure something out once with Hermes Agent, you're gonna be able to do it again and again and again and again.

Tommy Eastman ⋮ And that's where you can truly say, okay, agent, go do this, and you don't have to sit there and monitor and worry. And you can have other tasks be dependent on that task.

Marty Bent [7:39] Right.

Tommy Eastman [7:40] The third piece of why Hermes Agent, I think, is so beautiful, and this is like the ideological holy grail, right, is it's able to be fully model agnostic. And that is important for a lot of reasons. And we've thought it's been important for a really long time at Noose. You've seen more and more attention come to this issue now, though, of data sovereignty. and provider lock-in. Nobody wants to be locked into a single big lab. Nobody wants these labs training on their data. People want to own that stuff because that's the secret sauce, right? That's the sauce of my company is this data. And if I'm sending all of that to a lab that's going to use that to train in the next model, well, I'm giving away the secret codes.

Tommy Eastman ⋮ So Hermes Agent enables you to to own your full stack. You can choose to have stuff managed if you want, your cloud instances managed or whatever. You can basically craft whatever solution meets your sovereignty and privacy needs, and you can go implement that. And if things change, you can pivot it as well, right? So there's no provider lock, and you can use any model in the world. You can use much cheaper models. Like there's so many open source models that are incredibly performant for the vast majority of tasks now and at a fraction of the price point. So yeah, I think it enables you to just have a much more sovereign AI experience and really own the full stack from the floor up.

Marty Bent [9:13] And it's, I mean, we, the, so my Hermes story, my name's Marty Bent, I'm a Hermes user. So I, OpenClaw, Over Christmas break, people are like, OpenCLaw. I'm like, one, it snowed like 30 inches in Philly one Sunday and the kids were watching a movie. I was like, all right, I'll try this out. So like first time I ever set up a, uh, VM and set up a cloud server, set up the Hetzner server, like went through this YouTube tutorial, set up OpenCLaw and connected it to Anthropic at the time when you could OAuth in before they, uh, before they prevented that from happening. And was immediately blown away, like, holy crap, this thing is insane.

Marty Bent [9:56] Mm-hmm. So for about 4 months, I was building out that OpenCLAW instance and integrating more of our workflows into the agent setup and the harness in the cloud and like seeding the file system in the cloud with everything that I wanted this computer to be able to access. Along the way, like April, May, um, I was talking about OpenClaw and I heard people, uh, it was probably actually March, April, people beginning to be like, hey, you're using OpenClaw, you should like try out Hermes. And then like another similar situation where it was just a Sunday afternoon and, uh, I was sitting there and I was like, okay, like I've had 10 people like reply to some of my tweets, like you should try Hermes. And I was like, okay.

Tommy Eastman [10:41] We love our community.

Marty Bent [10:42] Literally went to my OpenClaw agent on Telegram. I was like, hey, Spin up a Hermes agent in your server and let me know when that's finished. And then I hooked up Telegram. And then within like 24 hours, I was like, okay, Hermes agent, shut down the OpenClaw agent. And we're gonna begin working. And it's been insane what we've been able to do, what I've been able to do on the team at TFTC over the last 4 or 5 months, just really seeding. the Hermes agent. But to your point, I think that's what, um, I really want to get through to people when we discussed this on our call a couple weeks ago is I view— I'm interested to get your thoughts on how you view this.

Marty Bent ⋮ Like, I think there's 3 legs to the stool of an agentic system, particularly if you're doing it for a business. You have, uh, the file system or the second brain, and there's, there's ways in which you can, uh, make that second brain stronger with things like semantic search for QMD or an Obsidian vault for a knowledge graph with associations, but I would bucket those into one thing. Second brain, essentially a file system. The harness, the agentic system, so in our case, Hermes, and then the models. The 2 most important things are the second brain and the harness and the models. Like you said, you can be model agnostic.

Marty Bent ⋮ And that's what I love about Hermes is it makes it extremely easy to switch models.

Marty Bent [12:07] Mm-hmm. And I'm hitting /model changing for different task when I don't want to burn tokens or burn expensive tokens, or if I want to use a more private open-source model. I don't think most people understand. Like, I think we're at this— it's not that I don't think, I know most people don't understand that this sort of 3-pronged approach and what is the value, what is the relative value of the different prongs within that 3-pronged approach. And I think that's where the opportunity lies and why I love Hermes. Because I think you mentioned like the self-referential learning is part of the memory system. And I think there's a ton of people out there saying like, all right, AI's here.

Marty Bent ⋮ I've been convinced it's not going away. I need to implement it in my business. So just focusing on businesses specifically, like how would you, like, is that, is my inclination of that 3-prong approach right in your mind? And if so, how do you articulate that, particularly to enterprise clients, to walk them through this?

Tommy Eastman [13:10] Yeah, yeah, I think you're completely right. There's so much value. The returns are compounding. The quality of intelligence is compounding the more and more as the agent gets more and more intelligence, right? So that file system is incredibly valuable. The more The agents are only as good as the data that they are able to access, right? There's no— it's not some magic. And so the ability to give your agent access to as much context as possible and basically just let it go to work is the secret sauce. That's the real value in these systems. And I think it's almost hard to articulate sometimes to enterprises, like, Why would I use Hermes Agent? It's like, well, you can use it for everything. And that can— that's— it's like, it's almost too abstract, right?

Marty Bent [14:07] Or too good to be true.

Tommy Eastman [14:08] Yeah, yeah, yeah. It's like, okay, what does that mean? And it's like, the reality is though, you really can. And you've seen it, I'm sure. You really can use it for anything. Any monotonous task you may have, um, anything you want done, just throw it at your Hermes Agent and see what happens, right? I think the The low-hanging fruit where a lot of people immediately say, wow, this is incredible, is working with big data. If you have, whether it's your Stripe data, your customer data, the ability to create, to organize that, to create visualizations, to do modeling is stuff that these agentic systems excel at, right?

Tommy Eastman ⋮ They are just so much better than we can possibly be at. And so, I think that's where you see a lot of the time people immediately go, okay, this is a game changer, is when they have some big data problem and they make visualizations out of it, it works right away in one shot. But yes, to your original point, the structure is your company, in its entirety, it should serve as your company brain, right? Like those 3 pieces of the stool, like you said, are the company brain. I think I agree with you that it's context or file system harness and then model. I don't want to discount the model too much because model quality does matter a lot, right?

Tommy Eastman ⋮ But they're very additive.

Marty Bent [15:35] But they're becoming commoditized. That's where I'm—

Tommy Eastman [15:38] Oh, in the long tail, for sure.

Marty Bent [15:40] I think in the long tail, for sure. Over time, the ability to be model agnostic is only going to increase.

Tommy Eastman [15:45] Yes. Yeah, I mean—

Marty Bent [15:46] Because they're reaching parity.

Tommy Eastman [15:47] 9 months ago, you couldn't use an open model for anything. Like, they were basically worthless, right? Um, and now you— I like to say, I think about, you know, 90% of users can do 90% of their work with open models, right? Like, there is definitely stuff that you want the, the biggest guns for, but tons of work can go to open models. And yes, that gap is continuing to close, and it's only going to become more and more commoditized.

Marty Bent [16:15] Yeah. And at what point do, like, do you, like, what is the, uh, the minimum AI IQ level that you need to do all the tasks? Like, do you really, like, say a year from now, are you gonna need a frontier model to do your modeling or your CRM?

Tommy Eastman [16:30] Yeah, the vast majority of people are never gonna do tasks that require these top-tier models. It's just not part of what they do.

Marty Bent [16:37] No. And the, So let's take a step back and talk about AI broadly. Like, where do you think we are? What trends are you most interested right now? Is it the data center compute side? Is it this model race? Is it the harness? What are you most interested right now in the world of AI outside of Hermes and Noose?

Tommy Eastman [17:01] Yeah, I mean, I think it's really interesting to follow how the open-source models have changed the market, right? Like I said, 9 months ago, you really couldn't use open-source AI. Now, if we transport back to January, February, you saw a bunch of prominent CEOs talking about, oh, our employees need a token max, token max, token max, like unlimited spend. Very quickly, they were like, whoa, way too much money, and want to find cheaper solutions, right? And that timed well with open models reaching the point where they can be these cheaper solutions. I think there's a lot of stigma around them for some people still about being, you know, mostly Chinese models, right?

Tommy Eastman ⋮ Like China is completely championing the open source model, the model race. Um, but you're seeing, you know, numbers on— in Hermes Agent on open models go up and up, on OpenRouter open source models going up and up. Companies are recognizing that that AI spend is out of control, that being locked into OpenAI and Anthropic is prohibitively expensive to power your business, and open models are really the only solution. And there's such an incredible free market of these open models, right? Like there's so many different GPU providers in different locations, different compliance requirements. So you can tailor whatever you need. If you need SOC 2, if you need GDPR, If you need them in the US, there's all these different things that you can tailor to fit your needs.

Tommy Eastman ⋮ But it's a much just more freer market, right? So you're seeing that price discovery, you're seeing model prices decrease, and you're seeing people be able to access intelligence much, much cheaper, which is obviously just incredible for the economy, for business, for small businesses especially.

Marty Bent [18:55] No, and I think I just discussed this with Jordy Visser, who was on before you rolled in, but I think the Latham& Watkins story from a couple weeks ago, the law firm basically said, we're not using Anthropic or OpenAI, we're gonna buy our own GPUs and self-host our model. Yeah. I mean, that's a massive signal. Not only the models are good enough to do that, but also I think a trend that many people are not appreciating enough. And I think Alex Karp's been beating the drum about this, but like particularly if you're enterprise the size of Latham& Watkins or any Fortune 500 company, like the feeding of your company IP to Anthropic and OpenAI is, I think it's gonna get to a point where shareholders or boards of directors are gonna say, this is like a breach of fiduciary responsibility. Like you're just handing over the secret sauce to—

Tommy Eastman [19:49] Yeah.

Marty Bent [19:49] These model providers who are proving or who are literally launching products that they're training off of companies that are doing this, like that they're going to try to compete with you and cannibalize your business while it's providing you value in the interim. And so to your point about open models, like I think there will be a massive inflow of usage for increased usage of these open models from like a fiduciary perspective just to preserve your IP. Yeah.

Tommy Eastman [20:18] Yeah, I mean, people are just throwing their trade secrets. It's actually a really interesting psychological phenomenon, right? Like, yeah, businesses are doing it, but also the average user, the ChatGPT user, the Anthropic user, people share so, so much with these models and almost like completely unaware of privacy or how that obviously could backfire and the different ends that that could go to. It's happening at the— at the individual level. It is happening at the business level as well. But I think at least now, more and more businesses are very aware of that. That's something that really resonates, um, with businesses that we talk to about, about Hermes Agent, is they want to— ever since that Alex Karp, um, spiel he went on, businesses want to own this. They're very, very aware. Um, they're very, very concerned about where their data is going. I think the general public is lagging behind, but I think there'll be a rude awakening for them as well.

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Marty Bent ⋮ io/tftc. io/tftc.

Marty Bent [24:02] It's funny, I was taking the Meta Muse agent for a spin this morning. I was like, wow, this thing's powerful. But then how much of this information do I want to give to Meta and Zuck? And I think that's a question that a lot of people are going to have to grapple with. But I mean, history shows, particularly in the digital age, most people don't care. That's why I think a focus on enterprise where you have to care Eric, because money and shareholder value, for lack of a better term, is on, on the line. Um, but then for the individual, like running individual agents, like I think, uh, hopefully, uh, team at Noose Research and others can get the, the UX, uh, to parity with something like a Muse agent where it just works out of the box, which I think to your point, like that was one of the most impressive things.

Marty Bent ⋮ So like I literally told my OpenCLaw agent to set up a Hermes agent and had it working within like 10 minutes.

Tommy Eastman [24:50] Yep. Yeah, I think that, um, it's really important to make the product easier and easier for people to use, right? Because if it's, you know, hours of setup versus instant setup and the privacy is the only differentiator, that's, that's been proven time and time again that, that that's not enough. I do think on the individual privacy aspect, I think It probably needs some sort of massive event to catalyze people growing aware of this, of this concern. But I do think we're at a stage where, yes, it was bad when you shared all of your information in this digital age previously, but now the ability for agents to access it, to compile it, access it, spread it, In seconds, right?

Tommy Eastman ⋮ So I think there are way worse potential outcomes on the table now that agentic AI is as powerful as it is, if people continue to be so, so free with their, with their data. I mean, I'm— imagine what percentage of ChatGPT users would be horrified if their chats all got, all got leaked.

Marty Bent [26:03] Wasn't there the ability to like Google's like if you were sharing The, uh, the output and you create like a share link that was getting cached in Google search. Yeah.

Tommy Eastman [26:12] Yes, yes, yes.

Marty Bent [26:13] Something similar happened to Meta as well. Um, yeah, where they thought they were like having a private conversation with the AI, but they're posting it publicly. Uh, yeah, it's horrifying.

Tommy Eastman [26:22] Horrifying, horrifying.

Marty Bent [26:23] Yeah. And it's— so how would you just like— that's what I'm— I've been trying to discern because things are changing so quickly. Like last year at this time, like Opus 4.6 wasn't even out yet. Correct. So you didn't have, like, there was that Frontier model sort of breakthrough moment where it was like, oh wow, now this stuff can like really cook. And then a month later it was like, they were working on Open Claw. You guys have been working on Hermes, but like people didn't become aware of like this harness thing until that happened. So we're only like 9 months into this. What, where does it, like, how do you think this looks? Uh, even 3 months from now, a year from now? And what trends should people be paying attention to, particularly around user experience and workflows that they can incorporate using this stuff?

Tommy Eastman [27:11] Yeah, well, what you said is exactly right, right? Like, at this time last year, Opus 4.6 wasn't out. I think the best way to describe that change, that clear step function increase in AI capability was, At this time last year, like, my top— the top 10 developers I knew, 0% of their code was written with AI. And it wasn't better than them. Too many issues, too many hallucinations, no ability to do long-running tasks. Now, 100% of their code is written with AI, right? Almost nobody— there's almost no reason to be writing code except with AI now. And people are doing incredibly long-running tasks with agents. And that was less than a year ago, like you said, like 9 months ago that change happened. And so to think about where we are from the next 9 months, it's really, really hard to be predictive. I think that— I think what's very clear is we're early on the adoption of AI.

Marty Bent [28:17] Mm-hmm.

Tommy Eastman [28:18] And we're going to start to see like just those basic levels, like engineers all using AI. We're going to start to see that all be integrated into Every enterprise. This year from this time now, this time next year, I think every enterprise, all code is written by AI, right? There's really no— there will be really no excuse at that point. I think it will be abundantly clear that you have to do this to keep up, to ship, because the companies that choose to do it are going to— it won't happen overnight, but it will happen fairly quickly, will drastically outperform and be able to cut expenses.

Tommy Eastman ⋮ and be able to ship faster than companies who do not choose to use AI. I think as far as novel behavior that emerges, I think we're just gonna start to— I think we're getting close to starting to see more and more autonomy be dropped into the hands of AI, right? Like, there's always the examples of, oh, my AI's shopping for me. That stuff, it really isn't happening. Yet for the most part, right? Like, you can kind of manufacture some text, but it's by no means a smooth user experience. And so that plumbing has to continue to improve for you to actually make that transformation where it is as simple as text your Hermes agent like, oh, I need this purchased, and the Hermes agent goes and purchases it.

Tommy Eastman ⋮ The next iteration of that, which is even cooler, and this is where we're heading, is Hermes Agent is always on and actually being predictive, right? So if I, for example, and this kind of can happen now, but I think it's gonna become more and more prevalent is, I have to go to SF next week. It's on my calendar. I forgot to book flights. I forgot to book hotel. Hermes Agent just goes and does all of that for me and it's handled and I don't even have to worry about it. And then I get in a routine where, yep. Oh, Marty texted me and said he wants to hang out in Philly.

Tommy Eastman ⋮ Hermes agent's gonna go, it's gonna book my flights, it's gonna book my hotels, it's gonna do it all correctly. It's gonna send Marty the information that he needs to know. It's gonna send Marty's Hermes agent the information it needs to know, right? So I think, um, all of these minor tasks that you have to do in your life can be pushed off to agents, right? It can be foisted onto agents and clear you up. So I, like, I hate booking hotels. I'm terrible at it. I book wrong hotels all the time. I book wrong flights all the time. Hermes agent should do all that for me.

Tommy Eastman ⋮ And I think we're getting really close. to it being able to. And I think like that 3 to 6 month window of where it's in an always-on state, it's being predictive and it's being autonomous. I think that's, that's very, very reasonable.

Marty Bent [30:54] I'm a massive flight, hotel, train procrastinator.

Tommy Eastman [31:00] Yeah, same. It's horrible.

Marty Bent [31:01] I've got to go to— I've got to go somewhere in a couple of weeks and I should have booked the flight months ago. Yeah, I booked it yesterday. I was like, I'm paying the premium for this because it's been— and it's been on my calendar. And it's, uh, what, what are you seeing inter— like, so this is one thing selfishly I wanna get out. Like, obviously you interact with a ton of individuals and enterprises leveraging Hermes Agent. What are some of the most creative or mind-blowing ways or workflows that people have incorporated using Hermes?

Tommy Eastman [31:32] Yeah, it's a good question. Um, or who—

Marty Bent [31:35] or another way to frame it is like, who's utilizing it the best and why is the way they're utilizing it the best way?

Tommy Eastman [31:40] Yeah, well, I think Noose Research utilizes it the best. No, but, but in all seriousness, we— I think we— it's really, really important for us, right, if we're gonna deliver this product to enterprise, that we are the number one power user of it. Um, and so we use it, we use it for everything. Um, I couldn't even try to quantify the productivity increase that Hermes Agent has applied to Noose. But it's funny when people ask us how many, you know, how big is the team, and we say, you know, 30 people, 35 people, they're often blown away just because if you've watched the rate that we've shipped on the Hermes Agent repo and the cloud products and the enterprise offering, it's something that would, you know, take an order of magnitude more people in the past.

Tommy Eastman ⋮ So we use Hermes Agent for managing our full sales pipeline. No need for the standard kind of CRM SaaS. Hermes Agent can manage that. For our content creation pipeline, we haven't— I don't know if you've seen our— I'm sure you have our design work and the videos we put out.

Marty Bent [32:53] Very aesthetically pleasing.

Tommy Eastman [32:54] The aesthetic, we want things to look pretty. Stuff we put out, all of that is generated in Hermes agent pipeline. It's, it's very reproducible. It allows our designers to have a ton of, um, a ton of control over the end product, and it takes a ton of, you know, manual, you know, graphic design work and labor off of their plate. Um, one of the most interesting tools we have is, uh, an agent internally that all our employees can use And it basically has a bunch of key data sources of ours. So if a user complains or if a customer complains about a billing issue or, oh, something isn't working correctly, a news portal or my Hermes agent, there's some bug, we can just ask our internal Hermes agent.

Tommy Eastman ⋮ Hermes agent debugs it, can push fixes, and basically is able to access all of our data backends at once, right? Whatever it may need. And it becomes over time really, really capable and competent at accessing this data and turning it into an actionable item for the user, right? So rather than somebody having to manually sift through, you know, infinite logs basically and find issues, Hermes Agent can find it in seconds. And that's actually a good way of describing what Hermes Agent is good at. It can do any task that a human could do but would require infinite patience, right? Like, nobody's actually able to sift through millions of pages of logs.

Tommy Eastman ⋮ Like, you could, but You would go insane. But Hermes Agent does it instantaneously, and Hermes Agent doesn't complain either. So it's a pretty, it's a pretty fun solution.

Marty Bent [34:32] Yeah, that's what I'm wondering. Like, I would love, again selfishly, to like, like give your team access to my Hermes Agents. Like, where am I fucking up? Like, because that's what I'm like continuously like trying to figure out is, all right, how can I better utilize this? Like, I always feel like I'm not utilizing just in AI generally, it's like I'm not utilizing everything to the best of its ability. And it's trying to like explore where the boundaries and the edges are. And I feel like every week I have an aha. I'm like, holy crap. Like I just, like one example, this will be the second time you're hearing this story in 2 consecutive episodes if you listen to the Jordy Visser episode, but I'll tell it again.

Marty Bent ⋮ I was at the bar. We published this Podcast via Fountain, and so like our RSS, our video, our audio file, video file description, everything goes up there. Trans transcript as well. They they have a it's not publicly available yet, and I hope they don't get mad at me for disclosing that they have built an MCP that I have MPC MCP MCP MCP that I have beta access to. And so Fountain has video, the transcripts, and I've connected the MCP to my Hermes agent, and I can literally just voice the text like, hey, uh, Tommy and I, the, the podcast is published now. We were, we were, um, let's get meta here.

Marty Bent ⋮ Let's see if my Hermes agent will pick this up, uh, by reading the transcript. Uh, I want you to use the Fountain MCP to clip out the the section of the conversation with Tommy where we're talking about, uh, how to connect Fountain's MCP, what I, what I use it for, uh, take a, take like the, the most engaging quote from that and then a one-sentence brief description, tag Tommy in it, and then post it on X. And I did something similar to that last night. Within 5 minutes, the Hermes agent had used Fountain to find exactly what I described in the podcast I published yesterday.

Marty Bent ⋮ Clip it out, send it to me to review, and then like send tweet.

Tommy Eastman [36:38] It's incredible.

Marty Bent [36:39] Within 5 minutes.

Tommy Eastman [36:40] It's incredible.

Marty Bent [36:41] Like I'm at the bar having a beer and getting work done. Yeah. For a media company, it's like, hey, that is work.

Tommy Eastman [36:47] We're getting— Yeah, well, no, right? I mean, that's a non-negligible amount of labor that you would have had to do. It's kind of a pain and a tedious task. And it's like death by a million paper cuts when you have to do all those things all the time and the amount of time that it frees up by you being able to just dump all of that on it is— I mean, how much— I guess I'd ask you, can you quantify the impact on business that, you know, Hermès Agent has had for, for you all over the last 4 months?

Marty Bent [37:17] Uh, yeah, I mean, I think from— it's increased our profit margins, increased our revenue. Uh, one thing I've hated historically, and I've told this to people many times. Like, like, we're a small shop. It's me. I ran TFTC by myself for 6, 7 years, and it's only within like last 3 or 4 years that we've brought on any employees. I mean, there's 5 of us and some contractors. Uh, I did all— for many years I did like the recording, the editing, the publishing. Uh, but the bane of my existence, and as funny as what I did at Barstool Sports when I worked there, was ad sales.

Marty Bent ⋮ And like putting together decks is something I'm— I appreciate good aesthetics, but I don't know how to manifest them in the digital world very well. So like all my decks were like Google Slide, like slapstick screenshots. Oh, yeah, yeah, yeah. Yeah, trust me, it's a good show. But went and found like a beautiful slide deck skill, connected it to the YouTube API, connected it to our Fountain API, connected it to a bunch of other things that are pertinent to putting together a media deck and basically say, hey, for example, like if I was gonna try to sell you on an ad deal, I'd be like, hey, I would like Noose Research to be an ad partner with us.

Marty Bent ⋮ Think about ways in which we would be a good brand fit for them based off of our—

Tommy Eastman [38:48] Yep.

Marty Bent [38:48] Our demo data, like our, our stats on YouTube and whatever, and like come up with a deck 5 minutes later. Uh, it's got an HTML page on Vercel, beautiful deck that can actually sell. Like on top of that, it's like, let's make sure we're pricing this right. Like run market research about podcasts of our size. Like what is the CPM?

Tommy Eastman [39:07] Mm-hmm.

Marty Bent [39:08] Is there any premium on our audience specifically? Like go do that research and come up with like accurate pricing. And that has led to more closed ad deals for us. So yes, it has. Long way of saying yes, it has.

Tommy Eastman [39:21] Yeah, but I like what you said too about, um, you know, you have a hard time personally manifesting aesthetically pleasing stuff in the digital age, but Hermes Agent enables you to do that.

Marty Bent [39:31] Yeah, right.

Tommy Eastman [39:32] And that's what's so cool about it is if you're, if you're a high agency, if you're a high agency person right now, there's no better time in the history of the world to exist, right? Um, Like, I can't write code anymore, but I can, I manage our compute clusters and I can get all of the visualizations, all the telemetry that I could possibly want from it just by interfacing in natural language, right? And build dashboards that help inform our business decisions and allow us to see how we're acquiring new users and how our compute cluster's health is. And that would take data scientists, front-end engineers, it would take a series of people to do that in the past. And now I'm, just prompting Hermes Agent and it's building out what a full team would have to build historically. So, it empowers you to do pretty much anything in any dimension that you want, in any domain that you want. I mean, it's unbelievable.

Marty Bent [40:25] Freaks, look at me. I'm glowing. I've got an angel's halo going around me. You know why that is? Is I feel good. I feel taken care of. I feel blessed, healthy, happy. And, that is because I'm a CrowdHealth member. My family and I have been CrowdHealth members for 5 years now, literally this month, 5 years ago we joined CrowdHealth. We've had 2 babies, we've had multiple health events, and we're never going back to health insurance. CrowdHealth is crowdfunded healthcare. So you sign up for CrowdHealth, you pay a monthly fee, you help out with other people's bills, and it's significantly cheaper than health insurance. We were on COBRA as a family of 3 when I left my last job before I went full-time to CFTC, went on CrowdHealth, Now, as a family of 5, we pay, I believe, $700 a month. It's significantly cheaper. They're going to negotiate prices lower for you. They've consistently negotiated healthcare prices as much as 50%, 60%, 80% in many cases.

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Marty Bent [42:17] 10 years. That's 10 times longer than most lenders out there, or go interest only for up to 5 years. Rates start at 8.99% APR. For a product that lets you keep your stack and still access liquidity, it's hard to beat. On top of this, guess what? You also get 2% unlimited cash back every time you use the card. Spend fiat, keep your Bitcoin. That's the whole game. If you've been stacking for years and you need liquidity without triggering a taxable event, this is worth a serious look. Go to aven.com/bitcoin. That's aven.com/bitcoin. Check it out. I mean, let's shift to this, the compute side. What are you, what are you seeing on the compute? You're talking about your cluster. What, on the physical side of things, like you actually need the GPUs, you need to download it, like what are you seeing there? Like what is it like managing a cluster? Maybe we'll start there.

Tommy Eastman [43:05] Oh, all sorts of headaches managing clusters and compute for sure. What I think is really interesting about the way compute has shifted, it's shifted with use, which is I guess obvious, right? But I think it's worth noting, again, we said this time last year Opus 4.6 wasn't out. developers weren't using it to write code. Good developers weren't using it to write code. I was using it to write code, but good developers were not using it to write code. At this time last year, you could, if you needed a cluster of whatever, 128 GPUs, I could send a text out and have 10 different providers bidding to win that. Now it's the inverse. I basically would have to go and and text 10, 20 different people and say, I need a cluster, I need a cluster, I need a cluster. Nope, we don't have any. We don't have any. We don't have any. It's unbelievable how squeezed the HPC industry is right now.

Marty Bent [44:05] Yeah.

Tommy Eastman [44:06] I think we're up against a lot of, you know, land and power limitations. I think you're seeing the regulatory environment has just really squashed the ability to continue to grow that. But also just the usage was such a parabolic increase in inference needs that we weren't prepared for it, right?

Marty Bent [44:30] Yeah. And so to that point, who was getting access, obviously outside the frontier model? Because you have training, obviously you have the inference, and obviously Anthropic, OpenAI, Meta, Google, SpaceX, they all have incredible access to this stuff. But I think we've discussed like OpenRouter. I think Stripe's acquisition of OpenRouter is a very strong signal. And I think this NeoCloud sector is going to, I think basically having open market for different models is a very smart idea, especially if we believe that being model agnostic is going to be a trend that strengthens. In the future, to that point, like how do you get priority? Like how do you both on, okay, backup infrastructure side, what makes you a good cluster?

Marty Bent ⋮ What do you need to do right for your end customer to make sure people come back to you and buy compute for you? 'Cause there's a bunch of stuff with like networking and latency and all of that. And then 2, how for the off-taker, like how do you— How are these people, the NeoClouds that own the GPUs and will inevitably host them, how do they decide whether or not you're a good off-taker that deserves access to that compute? Does it even matter? It's like you're paying in.

Tommy Eastman [45:49] Yeah. So on the first piece, yes, it's managing these nodes is difficult. There's a lot of entropy in the management of these nodes that I don't really fully understand, but there's a lot of downtime. If you're talking about managed inference specifically, there's throughput and latency, throughput, latency, uptime. And so you, I mean, these providers do wanna work to have a good experience for the end user because it can be a huge headache and people are paying a lot of money for these nodes. And if their throughput isn't met, if their latency requirements isn't met, it really ruins the end user experience really, really quickly and people are gonna stop. people are going to stop paying for, paying for machines from a specific provider. Right now, the market, I think, is so squeezed that there's way more wiggle room and tolerance for that stuff just because it's like, where else are you going to go?

Marty Bent [46:47] Mm-hmm.

Tommy Eastman ⋮ And to your second question, I know that that plays a role in like, who is the end user, who is the buyer, who is the off-taker plays a role in the decision-making process of these companies. I've heard people talk about how, Like, the sales cycle for these AEs is basically flipped. Before, it's like, I need to go find people to sell this compute to. Now it's like, I have all these people to go sell this compute to. I have to build a case of why my people, to internal teams, why my people are worthy of getting the right to this compute contract. So the thing is completely inverted.

Tommy Eastman ⋮ It's fascinating, right? And I think it's always company, it's internal politics and kind of company dependent on that stuff, right? There's different partnerships between companies and favors had, of course. I think, you know, a lot of these companies do try to, you know, care about open source and try to support different parts of the ecosystem, right? I think people recognize that if all of this compute ends up very, very consolidated, that's a dangerous situation for a multitude of reasons. So I think, yeah, they— there's, you know, economics play a big part, but there's also a bunch of, um, kind of strategic initiatives that drive where, where this compute ends up.

Marty Bent [48:11] And I'm happy we're discussing this now because I meant to bring this up earlier. I think it's important to clarify for people, we were talking about open-source models, many of which are predominantly trained, uh, in China and then released. Uh, people hear that, they're like, oh, I'm sending all my data to China now. That's not always the case. Like, if you're connecting directly to DeepSeek servers, like, yes, you are. But I think the understanding around, like, no, like, it's open source, so you can have American companies go buy GPUs and download the model there, and you're, you're not serving it to Chinese servers. It's a Chinese model run on American servers.

Tommy Eastman [48:47] Correct. Massively different, right? And that's been a huge education piece that we're trying to drive home is You can have all of these cost savings. You can get really good performance at a fraction of the cost, 60%, 70%, 80%, 90% cheaper than US closed frontier labs. And you can do it with— yes, it's a Chinese model, but it's running on infrastructure owned by a US company in a US data center on US soil, right? And those are where your data flowing is 2 totally different things.

Marty Bent [49:16] Yeah, well, you can say that people are like, it's phoning home to China though, right? It's like, no, not exactly.

Tommy Eastman [49:21] Definitely not.

Marty Bent [49:21] And then, uh, like the pro— again, going back and like tying in privacy to this too. This is what, uh, I know we were talking about Maple AI, uh, Venice has obviously exploded in popularity, uh, PPQ is another one. Uh, I am very bullish on running these open source models in trusted execution environments, just like to increase the privacy layer, because that Shout out to Mark Goodwin, who's been on the tip on Twitter saying like, even if you're using open source, it doesn't mean decentralized. There's still somebody hosting those servers at the end of the day. But with like trusted execution environments, being able to run the inference in a secure enclave and have everything end-to-end encrypted from your device that's baking the prompts to the input in transit is encrypted, then— You do everything on the secure enclave, you re-crypt it, send it back. Like, I think that's a massive opportunity too. I'm just rambling now.

Tommy Eastman [50:19] Yeah, and I think that, and I think local models, local models as well. And local models are continuing to get better. Hardware, consumer hardware is continuing to get better and better, right? And so the ability for you to run a model on your local machine and do, again, it's not gonna be 100% of your work, but a good chunk of your work, especially if you have sensitive workloads, you can run those on local models and, and get, get real work done.

Marty Bent [50:45] Well, this is actually something, I'm happy you brought this up. This is something I've been like thinking of, like, I'm not smart enough. I'm, maybe I'm not, I won't—

Tommy Eastman [50:53] You're smart.

Marty Bent [50:54] I won't denigrate myself. I'm smart, but I, I do not have the skills to post-train an open source model on my own data. That is like something if like Hermes, if Noose could figure out a way to take what I built with my Hermes agent and be like, okay, I wanna use this model, um, this local, this SLM, like locally, uh, Hermes AGI, I have all the context of what we've been working on over the last 6 months. Like, can you help me post-train this model on our specific data? Like that, I think, at least for my purposes, that's the one thing I've been, uh, somewhat obsessed with for the last week or two is like, okay, I've gotten to this point. Like, what else can I do? Yeah.

Tommy Eastman [51:30] How can you squeeze more performance out of this?

Marty Bent [51:32] How do we post-train a model on all of our stuff? Like, How do I do that? Yeah. That's what I'm looking for. If anybody wants to help me, let me know.

Tommy Eastman [51:38] Yeah, we can do that. We can get you that. So that actually was part of the reason that Hermes Agent was created. It wasn't created to be this outward-facing product. It was created really out of like a completely utilitarian birth. Our co-founder Technium created this Hermes Agent to help as a small AI research lab, right? You're always trying to find Like these moonshot ideas to push you to the frontier. And Technium created this self-evolving Hermes agent to help us become frontier model trainers. So the original birth of Hermes agent was really to do— it was in part to do that. And that's something we should do a job of highlighting, how you can use Hermes agent in that stuff as well.

Marty Bent [52:26] Yeah. So what, uh, what's the plan with Noose? Like, you have the agent, you have Noose Portal, you got this enterprise. What, uh, what are you guys striving for, um, in terms of what this company looks like? Um, and I know you said this on the phone, like, who knows what any company looks like. Like, what are your, what are your north stars and who are you building for at the end of the day?

Tommy Eastman [52:49] Yeah, yeah. I think, um, who are we building for is, is everybody. And I think I answer that really intentionally that way because I think we've built this product in a way that it meets you wherever you are. The open-source repo, if you want to run a local model on your local network and never touch any Noose Research managed product, that's great. Like, the Hermes aging repo will always be able to empower you to do that, and we'll continue to improve it and maintain it. If you want certain things managed, like, great, we'll do all that as well. We will be the best— we are the best place to have your Hermes agent hosted and managed.

Tommy Eastman ⋮ If you want different pieces managed, but you want to own certain pieces or do some work locally, great, we'll meet you wherever we are. So we really are building this for everybody. I think the 2 sort of key outcomes over the next um, handful of months for us, which lead to where we, we want to be in the end, is one, making— decreasing the amount of time that you go from Googling Hermes Agent or having your friends send you a Hermes Agent to, to realizing, wow, this is a magical, magical experience, right? Um, how can we get that time? So how can we make it a frictionless onboarding?

Tommy Eastman ⋮ How can we meet people on whatever device they are How can we enable people to send others there, send others a Hermes agent? Oh, Marty hasn't used Hermes agent. Let me send it to you. You can click a link, open it up, and ask it one question and be like, wow, and not have to do setup, not have to configure anything. So that's really, really important, right? Is how can we make it as frictionless as possible and make it so that you, as quickly as possible, realize that you have a tool that you've never experienced before in your hands? And then the second piece is delivering Hermes Agent to enterprise in a way that they're able to control their AI stack, right?

Tommy Eastman ⋮ It is their sovereign AI stack with all the bells and whistles that enable employees to be much higher agency, much more output, and do it in a way that isn't prohibitively expensive, that leverages the plethora of models and tools out there that can power Hermes Agent in a meaningful way, delivering that product to enterprise at scale. So yeah, those 2 things. Can we trim down that timing? Can we deliver to enterprise at scale?

Marty Bent [55:30] Yeah. Meet people on their device, that's been one of the interesting observations I've had over the course of the years. who attracts to what specific form factor. Like I was telling you, like I haven't used Claude Code or Codex Desktop in 7 months. People are like, how are you doing that? Like, are you trying to get left behind? I'm like, no, I literally, it's connected to all these different models. And my go-to form factor is just like voice-to-text in Telegram. I have a group chat with the agent, just the agent and me, but the group chats allow you to create topics. Yep. So we have topics that represent different sessions that are AdOps, Bitcoin Brief, or the commoner newsletter builder.

Marty Bent ⋮ If we have a business meeting, okay, like BizOps, what do we need to get done? Blah, blah, blah. And then there's something about that form factor, it just vibes with me. Like just being able to like on the go, on a walk around the neighborhood. And you saw me literally when you walked in, I had had my newsletter session open, like talking about how I wanna frame today's newsletter. And just that form factor of being able to walk on the go and do it on my phone clicks with me.

Tommy Eastman [56:40] Yeah.

Marty Bent ⋮ For others, it's like, and I think a lot of people are talking about vendor lock-in, people are locked into Claude Code and Codex specifically, those desktop apps. And they think like, this is the only way that you can leverage this. I'm like, no, you gotta get yourself self off that tit as quickly as possible because you're going to get vendor locked in and that's not what you want. Um, but it is like, but some people like Ed on our team, he loves the, uh, he loves the Hermes desktop app. That's how he interacts with it. And I'm, I'd never, frankly, I'd never use it. I just use it through Telegram.

Marty Bent ⋮ Um, and I think there is, it's becoming clear to me that there's going to be different preferences for different form factors for how you interact with this and thinking about a company like Noose Research trying to design for all those different ways which people are going to prefer to interact with it is, it's a crazy problem to think about.

Tommy Eastman [57:32] Yeah, it's a massive problem, right? And you're exactly right. There isn't some golden solution where, oh, everybody is going to use this as the way to interface, right? At least certainly not yet. And I think the stance that we generally take is don't be, Like, we, we're definitely opinionated on some of the best ways to use these things, but we don't wanna ever lock in unless it's blatantly obvious that that is the place that we need to lock in, right? So can we— or so we allow WhatsApp, we allow Telegram, we allow email. Like, wherever you want this thing to live and meet you is, is important 'cause people use it, people use it in different ways.

Tommy Eastman ⋮ There's a lot of people that would never wanna talk, wanna talk as much as you, right? Like, they would never wanna do that. Everybody is so different and everybody finds different ways to get the performance out of these agents that they want that you need to build for a huge range of different platforms.

Marty Bent [58:25] Yeah. No, it's funny, when we, like, as you're mentioning that, like email, the Hermes agent has an agent.toomail email address. And so like for my wife, whenever she's like, ah, like we're in the market for a new car, and she's like, ah, she's like doing it the old way, I'm like, hey, just email Martin. I gave him permission to email you back. Like tell him what you want and he'll go do like a search search for you. So like, my wife is emailing Martin, the more sophisticated Marty, is, uh, is doing all this work. But it's like, it's been fun watching my wife just, just, she'll be like, oh, I emailed Martin today and he like did some good work for me. I'm like, that's pretty incredible.

Tommy Eastman [59:04] Does she like Martin more than you?

Marty Bent [59:05] No, no, unfortunately. I hope not. Not yet, at least. Maybe at some point. Maybe when robotics get here. Shoot, maybe we need to put out— I'm kidding, I'm kidding. But no, it's just like the, yeah, like that's one form factor where it's like, hey honey, instead of like you taking my phone and getting Telegram, just email Martin. Yeah, yeah. And he'll get you a list of cars in the area that are within the range of what you're looking for.

Tommy Eastman [59:34] Yeah.

Marty Bent [59:35] She's just been going back and forth with him in an email thread.

Tommy Eastman [59:37] Yeah, and it's probably a magical experience for her, right?

Marty Bent [59:40] Yeah. Yeah. Yeah.

Tommy Eastman [59:41] And awful, and awful, it's all of those monotonous tasks like going and searching and getting quotes from 6 different vendors and finding the car you want and the reviews, all of that is— it goes from these incredibly laborious processes to, you know, a few minutes texting your Hermes agent.

Marty Bent [59:57] No, and then we have, uh, Ed on our team. He has his agent, uh, and our agents are emailing each other. Yeah, like, so if we have stuff in the business, like, Ed in his Telegram or his Hermes desktop app with his agent, like, all right, email Martin, um, and tell him that we did this thing in this part of the business and make sure he updates his second brain to recognize that. Yep. And I feel like, I still feel like I'm not utilizing it. Like, I'm like, we do that and something like a workflow like that will emerge. I'm like, is this the right way to do something like this?

Marty Bent ⋮ Like, is there more efficient ways? Point being is there's so much to explore in terms of all these different workflows and use cases. Particularly teams, like thinking about how teams interact with agents. And I think Dorsey's interview with Sequoia earlier this year really, uh, really cemented my thinking about like how to view a company in the world of agentic AI.

Tommy Eastman [1:00:57] Mm-hmm.

Marty Bent [1:00:57] Or like the company is like essentially like a knowledge layer and your job is to give it the best, most robust knowledge that every employee can access. And so, I haven't let everybody into the group chat on Telegram. However, we do have like Discord and the agents run wild in Discord and they can talk there and interact with them. So that use case of creating a second brain for a company specifically and then getting access, the right access to individuals on the team is a massive problem. Not a problem, massive opportunity. Because when you think about like permissions, especially if you're like selling enterprises, like, okay, I want Becky from finance to have access to this data, but not this data. And like just building the guardrails for that.

Tommy Eastman [1:01:43] Yep, totally.

Marty Bent [1:01:44] Massive opportunity.

Tommy Eastman [1:01:45] Yeah, it's a massive opportunity. And I think there's a bunch there too, as far as how can you use Hermes Agent to get more out of every employee, right? And I think what you see is certain employees, it's a skill to be able to prompt these agents, right? Like different people get different performance out of agents. It's like very much a feel thing. And I think you have, you have people that are incredibly, incredibly proficient, like your top performers. Um, Hermes Agent lets you bring other people up to their level, right? And that's what we're rolling out for enterprise is, is, is, you know, this concept of, of a collective wisdom, a collective brain where you can take performing employees, top skills and deliver those to relevant employees, and they immediately get boosts in their performance.

Tommy Eastman ⋮ Their agents are immediately better. They're shaped in the way that you want them shaped. If you, you know, you— however you want your top employees perform, if you want other people like that, like, it will shape other people's agents in that way too. And when you have new hires, instead of having like this cold start on-ramp experience, you can equip them with a skill set of tools that are formulated, you know, in the way that TFTC wants things written. Right. And, you know, all of that stuff. And, and you can have, um, you, you can have your agents molded kind of to your voice and, and the way that you want things done, your guidelines.

Tommy Eastman ⋮ , to kind of help shape people in your direction and also give them that productivity boost.

Marty Bent [1:03:14] Yeah. What do you think this does for the job market? Are you, uh, the permanent underclasses as quickly quickly approaching or a world of a billion flowers are going to bloom?

Tommy Eastman [1:03:27] I think we could have a whole other podcast on that. I think I land somewhere in between, right? I think that what this does is, you know, it enables you to not do all of these monotonous tasks, right? If you've— I think my big—

Marty Bent [1:03:47] Oh my God, I'm going to lose my laptop job. Yeah.

Tommy Eastman [1:03:49] My bigger concern is, oh, you Like, you're worried about not just like, you know, making Excel sheets for the rest of your life or whatever. Like, that's your—

Marty Bent [1:03:56] I'm really worried about the paycheck. That's your concern.

Tommy Eastman [1:03:59] Yeah, like, I think what this, what this should do is free people up to do, you know, more thoughtful and higher agency tasks than sitting there and like button pushing. Um, so yeah, I mean, is it going to be this straight shot to a million flowers? No. Like, there's of course going to be bumps in the job market as these disruptive technologies move through their natural growth and integration and flow. But I think if you— the optimistic view is that this will enable humans to do things that are way more fulfilling than what a lot of people have convinced themselves is foundational to their lives.

Marty Bent [1:04:38] Yeah, that's sort of philosophical musing I've had over the last year. Because you mentioned earlier, like, if you're high agency, you can get a lot out of this. And that's the question I have. Is there just like a natural distribution of individuals who are inherently high agency and a very large percentage of which are not? Or is there an ability to engender high agency in people? And do AI tools inspire them to become high agency? I don't know. I think that's what we're going to find out in the next decade.

Tommy Eastman [1:05:13] We'll find that out. I'm sure it's some mixture of both.

Marty Bent [1:05:16] Yeah. What's your most contrarian take on what's going on right now?

Tommy Eastman [1:05:22] My most contrarian take of what's going on right now. I don't know if it's contrarian. I'm sure it's— there's a lot of people I think that probably share this viewpoint. I never know how pigeonholed I am, or sorry, how echo chambered I am. But I think that if you want to talk about existential risk and the way that existential risk of AI, like AI, misaligned AI killing all humans or whatever, I actually sometimes believe in— I believe there's some degree of credibility to that argument as a possibility. But what I think is, I think where we get to crazy town really fast, and it's really, really disingenuous, is you see large companies and lobbyists pushing for a stop of open source, right?

Tommy Eastman ⋮ Like open source has become this sort of, has become this evil and this scapegoat. Whereas if you ever actually believed in existential risk as a real threat, open source would be the last thing you would be concerned about. You'd be concerned about this massive consolidation of compute. You'd be concerned about, you know, um, the frontier constantly being pushed by the closed labs, right? Like, just distillation to create open-source models, like, definitionally can't exceed AGI unless the top labs already have done it themselves. Um, so I think the— yeah, the way that that argument has been, has been pushed and is certainly kind of the, the controlling argument in the vast majority of the population, likely not those that are very in tune with AI.

Tommy Eastman ⋮ But the way that that argument has been framed to the vast majority of the population, I think, is just incredibly, incredibly disingenuous.

Marty Bent [1:07:16] Incredibly. It's almost disgusting to the point, because it's like, if— I don't think most of the public is aware because they don't pay close enough attention, but it's like very clear to me. It's like, okay, you're looking for the— you've raised a ton of capital You're deploying a ton of capital into this infrastructure build-out, particularly for the frontier labs. And you have a need to get a return on invested capital.

Tommy Eastman [1:07:44] Mm-hmm.

Marty Bent [1:07:44] And you're seeing these open-source models begin to nibble at your feet. Not only that, like many people are turning to them for 90% of the work for their individual use cases. And you're trying to shut, pull up the ladder and shut the door behind you. Just so you can save those profits. And I think when you consider how profound of a shift this technology is for humanity, the fact that there's literally 2 or 3 companies trying to pull up the ladder and control it all, it's just incredibly, I would say, like evil at the end of the day.

Tommy Eastman [1:08:16] Well, where did all the data come in the first place?

Marty Bent [1:08:18] Right?

Tommy Eastman [1:08:18] Like it's all of our data that trained it.

Marty Bent [1:08:20] I mean, the fact that they were buying like centuries-old books and like cutting off the bindings And then burning them. It's like, what the hell?

Tommy Eastman [1:08:27] Yeah, it was all our data that it came from in the first place, right? And then they, yeah, it's just disingenuous.

Marty Bent [1:08:33] Dealing with it with the New York Times right now, I believe.

Tommy Eastman [1:08:34] Yeah.

Marty Bent [1:08:34] I think that, I guess, copyright case is moving forward. Tommy, it's been a pleasure. We should do this more. I am gonna pick your brain off air about what I should be doing with my agent.

Tommy Eastman [1:08:49] I love it.

Marty Bent [1:08:50] Any final thoughts, final words of wisdom before we wrap up here?

Tommy Eastman [1:08:54] I don't know about words of wisdom. I think at some point it will be very obvious that you should care about privacy in the age of AI and agentic AI. I think that the more proactive you can be about it and the steps that you can take to empower a world where you have more ownership as a business and as an individual of your AI and where the data that you give to your AI flows, the better served you'll be and you can avoid a lot of headache down the road. And so I think looking for obviously Hermes Agent, but looking for tools that enable you in the AI realm to have good controls over your data, but do it in a simple way that isn't super burdensome and a huge headache for you, I think will be a really, really valuable investment going forward.

Marty Bent [1:09:52] I completely agree with that. Thank you for joining me. Thank you and the team at Noose for building Hermes. It's been incredibly powerful for us here at TFTC, and excited to see what you guys build next.

Tommy Eastman [1:10:05] Love it. Thanks, Marty.

Marty Bent [1:10:07] Thank you. Peace and love, freaks. Thank you for listening to this episode of TFTC. If you've made it this far, I imagine you got some value out of the episode. If so, please share it far and wide with your friends and family. We're looking to get the word out there. Also, wherever you're listening, whether that's YouTube, Apple, Spotify, make sure you like and subscribe to the show. And if you can leave a rating on the podcasting platforms, that goes a long way. Last but not least, if you want to get these episodes A day early and ad-free. Make sure you download the Fountain podcasting app. You can go to fountain.fm to find that. $5 a month gets you every episode a day early, ad-free. Helps the show, gives you incredible value. So please consider subscribing via Fountain as well. Thank you for your time, and until next time.