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[00:00] Every week it seems like the new tools [00:02] that drop are just mind-blowing [00:05] that it's just a non-stop now. That that rate of acceleration, you can feel it. Welcome to the Talking AI podcast where we talk AI with both experts in the field and early adopters. I'm your host, Matt Paige, and we're here to demystify AI for you so you can get some value from it. Let's talk some AI. [00:24] Today we got a special guest, Robert [00:26] Ransen, director and founding member of [00:28] the Agentics Foundation, also founding [00:30] part partner of human race, an Agentic [00:33] engineering firm. And he's an author, too. The AI dividend preparing for a post labor economy. All kinds of you're a renaissance, Robert. But for those who aren't familiar with the Agentics Foundation, it's an open foundation dedicated to building scalable, intuitive, and human- centered agentic AI systems and infrastructure. [00:52] And it was originally founded by Ruven [00:54] Cohen, who hands down is my favorite [00:56] person to follow in the AI space right [00:59] now. Robert, first of all, welcome to the show. I think you'd agree there on the Reven side. The dude's just insane. Yes. Yes. Absolutely. Thank you. I'm [01:07] happy to be here, Matt. And it's always a lot of fun to have these conversations. And Ruen Cohen is is his own singularity. That's probably the best way to describe it right there. And so Robert and I, we were both kind of early members in this small random community that Ruven had started. And it began as like just this [01:28] Friday meetup online called the AI [01:31] hacker space. And essentially Ruv would jump on, blow our minds with something new he'd built that week and or maybe just had AI building while he sleeps, which see seems to be the standard now. And then he would open the floor and then others would share their projects. It was just this really cool community that started and what kind of started as like this casual gathering has grown like wildfire. So much so that it's like an official nonprofit organization and we're going to deep dive more into the community. A I think it's the best one [02:04] anybody out there that's interested in [02:06] AI can be a part of but I also want to [02:09] get into this central topic around open [02:11] source versus close source, right? because it's one of the core principles behind the agentics foundation at the core of the discussion is that and I want to start Robert just give me your what is your definition of open source versus closed source and your stance on it let's start super high level and then we'll rabbit hole dive down some interesting parts sure I mean at its core I think it's not trying to retain control over ideas and and that the tools that we build out around the concepts are meant to be tools freely available to society to run with and and I agree with you Matt that's from the very beginning and actually next week or on the 26th of April is our one year or 52nd live event is it really the actual calendar year full year I'm trying to remember back when I how I think it was maybe just some random like LinkedIn post I wasn't even connected with Rub and I just randomly saw button. I was like, "Oh, that seems interesting." And I I jumped in it. It just it's evolved so much. Actually, let's stay there. I'm [03:20] curious like what is your story of [03:22] getting involved in what was the AI [03:24] hacker space and now the Agentics [03:26] Foundation? Like how did you meet Ruven? Kind of give me your story, your perspective as this thing's grown into this like how many people are in it? Yeah, there's there's 1,200 members in the WhatsApp space and that's capped. So, we can't invite any more folks in. [03:42] Occasionally, somebody will leave and [03:44] somebody else will come in. So, folks, there is a little bit of rotation, but it's kept. That's why we've also now opened up the Discord side. There will be a place for the community to grow. There's over 85,000, I think, followers on LinkedIn. There is or maybe no, [04:00] that's 120,000 [04:01] and there's at least 65,000 in the [04:03] Reddit over several Reddits. So, it's an audience that's pretty much closing in on a couple hundred thousand. And then there's a huge longtail audience for those live events. So every week Ruben does a coding session on Thursdays and then we have the open forum demo and new tool drop integration conversations. That's every Friday. [04:24] Yeah. And then those get recorded. Our friends over at Caloura have that archive available. So you can go back over the last year and look all those different coding sessions. But for me, uh, that'd actually be a fun exercise, Robert, is go back to the first episode just as like the throwback. Yeah. [04:41] And see what we were talking about [04:42] because I'm sure it' blow our minds just [04:44] how far things have progressed. It It does undoubtedly because every week it seems like the new tools that drop are just mind-blowing. And it's just a non-stop now. That that rate of acceleration, you can feel it. Like today for instance, I I was eating lunch so I jumped on a little bit late, but Rufin was building something. What [05:05] was it? It was like being able to find rare earth medals or something. I don't know what it was, but something insane leveraging AI system. Today was one of those moments, Matt, where even his buddies are like, "Wait, I think you're crazy." You know what I mean? But where a [05:22] concept idea run through deep research [05:24] he came across an article which is a lot [05:27] of scientific work has been going into [05:30] quantum signals of magnetic [05:32] it's how do you even describe [05:33] magnometer or magnetic fields [05:37] with the science being that there are [05:40] fingerprints of each layer of material [05:43] and item and concentrations of metals [05:46] and all that kind all have fingerprints. It's just that we have not looked through the right set of tools at the to find those fingerprints. much. It took us a long time to figure out gravitational waves. And this is it speaks just so potently to the era that we're in because now an incredibly talented engineer like Ruben with these tools can utilize a recursive like a chain of deep research to really explore the entire footprint of that scientific body of work and then hypothesize about what a codebase that utilizes the science and tests for it would look like and then build it and then run demos within 24 hours. [06:31] So [06:32] that's that's crazy. It is crazy that it means that frontier scientific work around the earth, around the entire planet can be identified and have tools built around it very quickly. That's acceleration. That's what it feels like in civilization when those kinds of advances can be made, discovered, tested, validated, and pushed forward so quickly. Yeah. And it's, you mentioned something [07:00] and folks want to check out like you [07:02] mentioned the recordings are out there [07:03] and you can join the community as well. We'll get into some of that later, but you mentioned the Thursday sessions. Those kind of came later. This is like That's right. Ruven's call it vibe coding sessions where you literally you can just be a fly on the wall and see him vibe coding and you can see his how he thinks about it his stream of consciousness as he approaches it. And [07:22] he said something today that I think [07:24] really resonated with me. He talked about like the idea of vibe almost being like on a spectrum because there's one spectrum where it's like you're literally just starting from nothing and you're just like it truly is like vibes based. letting AI guide you and then to the other end of the spectrum truly are having a detailed plan of what you want to do and build and there's varying degrees of where that is and then he's also built this spark framework too which I don't know how much you've played with that but that's essentially his methodology for using AI to build yeah specification pseudo code architecture revisions and then convention so uh to work with AI coding assistants in order to give them an overview of what it is they're about to build. And it's yeah, it's really it's wonderful too because I think Ruben first really formulated that back about eight months ago and it's been adopted now. Now when you you know when you look up room boomerang or custom rooms, it's coming back for coming back with that with the Spark framework. So really hats off to the [08:34] work that Ruven's been doing in the [08:36] space. Agenic engineering, define that for us because I don't think a lot of people either know what that is or even the term agentic. I don't know about you, but spellch check still says it's not a word for my they'll catch up. Agenic engineering is not the process of building agents. Agenic engineering is the process of building systems that build things. [08:59] Right. Yeah. Yeah. So agentic means it can interact with information and then based on a goal set decisions about how it's going to respond to that information. So it takes action. It is agentic. It [09:11] has agency. The key point is that there's a touch point with information that's incoming in order for it to formulate it. It's not an AB. It's not a binary decision. It we can utilize large language models to give it a space of logic to be much much more powerful. [09:28] But genic engineering is literally [09:30] building systems that build things, [09:33] right? And and that's what we've been doing for the last year is really explore the space of what engineering looks like with artificial intelligence and what kinds of things that you can do with that. And you still hear an awful lot online and LinkedIn and everything. Oh, it's not. This is really important. And [09:50] Matt, you put your finger right on it. the vibe coding to a genenic engineering in that spectrum. What that looks like is really whether or not you understand what's being built and you've planned for what's being built and whether when it's going off the rails or not. Agenic engineer is is somebody who's learned the the space, the architecture, or is a previous computer science engineer, a developer, and they're not just having the coding assistant go from scratch on its own figured as you go. That's the vibe coding space, which is is beautiful because literally millions and millions of people around the world and growing every single day are diving back into software and what they can create and discovering this new tool and the the the ease of developing software is coming closer and closer to everybody to make it universally accessible. You can build great stuff. [10:48] We're not there yet, but it's coming [10:49] closer every day. And people are learning more quickly. So, they're approaching the technology every day. And the impact of that is more creativity, more discovery, faster iteration. and and that impact is a huge boom to society within the right uh guard rails. [11:09] And to your point, there is this like [11:11] knowledge gap right now. It's almost like this arbitrage overnowledge of where the technology actually is. And I think two key points. One is even if AI LLM did not progress one iota from today, there's still so much untapped potential. And I think that's a big thing. And then B, I y'all go check out [11:29] for the listeners the episode I did with [11:31] Michael Lou from Stripe. The key phrase he said that sticks with me almost every day. It's like this is as bad as AI and LLMs are ever going to be, right? It's only going to keep getting better. You put those two things together, it's insane. And I love how [11:46] you define the agentic side. It's about it's very much a systems thinking. You're building the systems to build the systems and whatnot. And we're a similar type of firm, Patrick's AI. So it's the way I like to describe it in simple terms is we build AI native solutions and we use AI to build them. [12:01] Yeah. On that side it's like you do those two things but the key thing is you're using AI to build in essence. The other cool thing too we mentioned the Spark framework earlier. Ruven open sources everything he does and we'll put that in the show notes if anybody wants to go deep into that. Like it's almost absurd how much stuff he open sources and just puts out there. But that's like [12:22] his foundational view and mindset is [12:25] things should be open. This shouldn't be gatekeep. But like back to the original kind of closed versus open discussion. This this is like a very interesting debate to me because there's I see points on both sides that make sense, right? There's the point on one side around just the transparency and trust and you know the safety side of it right because some will say oh it needs to be closed because this is so powerful and it can't get into the hands of nefarious actors and people with ill intent and on the other side it should be completely democratized and open and that will most benefit society versus a small number of folks at the corporate level dictating how this grows and like both points I'm Yes, makes sense. What's your take [13:14] there? Especially like in the wrong hands. I think that's the scariest point for people is like when it gets in the wrong hands and can you stop that anyways? I think is the point. But I'm just curious like going into some of those points around the debate. [13:26] Yeah. And it's entirely all those concerns are completely legitimate. So they are things that we need to constructively and creatively solve for. I think most people would agree it would be uncomfortable to have a singular entity or organization that had the sole access to near infinite cheap and abundant intelligence and that was not to some degree ubiquitously understood and except accessible and that's the heart of it for the Genesis Foundation at android is that these tools are so important that the awareness of how to use them, what they can do, how to build them, how to develop them responsibly, deploy them responsible responsibly, all of that needs to be open. Now, transparency, accountability, traceability and and how we identify and respond to the potential of bad actors. That's a tool set and [14:28] that's in a number of tool sets that a [14:30] number of organizations are working on. And but also let's be practical. Let's be realistic. Governments and and leading institutions are going to retain the most powerful models that they've been able to build for a period of time before they're public. So there will always be a leading edge of governance. [14:49] And obviously as a civilization you want [14:52] to be able to have trust and faith and [14:55] the transparency and accountability of [14:56] your governance but also ensure that the [14:59] ability to protect all of us [15:01] collectively. Yeah. There's a whole bunch of things there. The base level like you said before of what we've already got is so incredibly powerful and we've only scratched the surface in terms of utilization and where that can be applied that we've got lots to work with already. Yeah. My view is I like to believe that [15:20] there's more good actors out in the [15:22] world than bad actors when something's [15:24] truly open source that there's almost [15:26] this these two forces combating each [15:29] other and ultimately I think the good [15:31] will win at least I like to believe that [15:33] but there is power in the [15:35] decentralization [15:36] of this like insanely powerful tool and [15:40] innovation right [15:40] yes yeah absolutely there and the [15:43] collective input of human creativity [15:46] because we have such great context of [15:49] the entirety of our lives and our world [15:50] views uniquely still leading in terms of [15:54] side by side of being able to direct our [15:57] creativity. Anyways, that's why I love the Fridays the Friday live events because you get to hear from so many. And what Ruven's been doing is he's been showing what's possible in the hands of an amazing engineer, right? Taking everything to its logical conclusion and and it's so the eugenics.org We want to make sure that those tools, the understanding, the repos members are working on all of that is available and it's really exciting. We've got I think [16:25] there's about 80 chapter requests around [16:28] the world and one of the first in Asia [16:30] will what's will be in Singapore. So there's lots of really work there because at the ground level people want to get want to know in their communities who else is involved, who else is engaged, what are the leading tool sets and so those local chapters will be a great asset to the community. So I think the other point with open source versus closed source is how do you define it? Because you hear like companies and model makers coming out saying they're open source but they've just essentially given the weights to their model. What's your view on that? [16:59] Is that do you view that as fully open [17:01] source or is there a spectrum of open [17:03] versus closed source as well? For sure. Yeah. The weights of the models are that that is that's open that's an open source model otherwise. Yeah, it is it's just a variation on the theme if you're not exposing those weights. The ability now for lighter [17:19] open source models to train up on [17:24] leading closed source models. Yes. means that the economics of that of that intelligence gap really significantly changed right since the quen the quen which lead to the which led to the deepseek which got which Quinn was Ali Alibaba's model and then was it deepseek that leveraged that so you're almost saying they're building on the backs of these other models in a sense during for the as a an approach for their training of the new model in a sense yeah that's right that's right because they can just d tap right in directly interact with the leading thinking models and then benefit from that logic exchange. I think the repo that Ru was talking about was DRP DPRO which allows you to and it's not expensive either. It's not it's not what it was six months ago. We talked a [18:14] little bit about Ruben Spark framework [18:17] that he leverages, but like on the AI [18:20] IDE coding front. Curious your take on the different tools, which ones you like, which ones use for different purposes. And then this may be old news by the time this launches, but I know you saw a couple days ago OpenAI's talking about acquiring Windsurf and what does that start to do, but maybe start on just the different AI IDs that are out there? What's your go-to? Are there ones you use in different scenarios? [18:46] I've been using Klein since it first [18:48] came out and that has been my preference [18:51] from the very beginning and now Rue R [18:54] code which is built on that's yeah which [18:56] is a fork off of client that's right [18:58] they they community they're doing just [19:00] great work [19:02] and so yeah so Windsor cursor [19:06] the really for public facing small [19:09] projects both lovable you can get pretty [19:12] far now especially that you can [19:14] integrate superb work with that. But as far as in the IDE for me, it is completely rude code with custom modes. Boomerang. Yeah. Being able to create subtasks and custom modes and the creativity that of what we can do with those custom modes is just a it's a wonderful combination. And that [19:35] is you do that well with the Spark [19:38] framework which means all the lifting [19:40] comes in the planning and the [19:41] articulation of what it is that you want [19:43] the software to do. and user stories and functional specs and everything else builds out from there. That's where the work is that with root codes, custom modes and the Spark framework that gets us there. So, I want you to go deeper on those two things, custom modes and the boomerang. But just for people as well because I feel like a lot of people either aren't using these tools or they're new to them. But like Root Code for instance, [20:08] you can be in just a regular old VS Code [20:11] instance and just it's almost it's like [20:13] a plugin, right? So you kind of have the chat window there. So that's the way you can access that. Technically, you can do that in cursor as well, but may do you need to I guess is the question. But go deeper on those two things. Custom [20:26] modes, boomerang. What are those? How should you think about them? Yes. For folks listening. [20:30] Okay, great. Yeah. So root code VSC extension open source you can set and select the models that you're going to work with that you want it to work with and it lives on the left side of your IDE and you interact with it and it can read write edit do all kinds of create the code for it or edit or review or you can keep it in ask mode and you just have conversations about your code. That's an underutilized thing, by the way, is like collaborating, aligning with your whatever tool you're using just to plan together, right? Yep. That's it. That's it. Because and [21:10] in that dialogue, all kinds of really [21:13] neat insights and creative inspirations [21:15] come. So key is that have that fun and do that exploration before you really get into say, okay, now this is what we're going to build. And so you've got that mapped out. So with R codes, now you can think about it for a second. I want to turn off the ability to edit, leave the ability to read, and we'll call that ask mode. So then I said, [21:34] great, go through my project [21:36] documentation. Let's talk about how we're going to what kind of ideas we have for the UI, right? And have a conversation back and forth. Maybe what are some interesting visual visualizations we could pull from the data? That kind of that's ask mode. [21:50] architect mode. Let's say you're gonna you can give it a specific set of custom instructions whenever it's in architect mode. You describe how it is that you want that documentation and those plans and the specs to be created. How do you want them written? What's the form? What's the flavor of it? What your [22:10] general approach to writing those kinds [22:12] of documents. So different modes can have different custom instructions so that when you enter that mode it's got a it's wearing a specific hat and rue code enables us to create custom modes. So we can create any mode that we want in a template in the R modes and and now we can move between them. Okay, there's one really important mode just like in any multi- aent system, interestingly enough because this sort of transitions root code from a coding assistant into more like a multi- aent framework specifically for coding and that most important mode is the orchestrator mode. So that's the mode that it's going to be in when it's thinking about the project or the part of the project that it is working on and it's the one that has to is going to determine what the next task is and which mode it's going to assign it to. Fascinating. That's the boomerang. [23:13] It's almost like having another human in [23:15] the loop in like a weird way. I I get more into this like mode of as I'm working with AI, I I intentionally pretend like I'm working with another human in a sense. Yep. It's it is fascinating where you can go when you get down the rabbit hole of coding when you can we have a whole team of specialists in the development environment. Right. One of [23:44] the first things I did when I saw the [23:46] the remotes is said I said great let me [23:48] create a custom researcher mode and I [23:51] just laid out use the open AAI API [23:53] connection and GPT40 search preview [23:56] model and anytime you need to look up [23:58] API documents just use that and I've got [24:01] my key and my amp and and it works. So now when the coding team is building a project and it runs into a problem with with an API setup it can just look it up and continue on. Yeah. And then Chris Royce morphed that on Rub suggest, morphed it into a Perplexity MCP server. So now you can do deep research while coding. Phenomenal. Earlier you [24:24] mentioned lovable, which we glazed over [24:26] that, but I got to say that's almost my [24:29] favorite go-to tool for just call it [24:32] vibe coding or whatever. And the beauty of it is you mentioned the connection with Superbase. So, I've got into this nice little method that I work especially for like niche like use cases and things where I'll almost have it define you align with it on what you want to build, but I'll have it like build out the landing page of the thing first. It's something about that does this nice like alignment on the positioning and what we're trying to build the value prop and then connect into superbase, have it do authentication, set up the backend, and then you just start building feature by feature. But it's pretty insane of how capable it is when you have it integrated with Superbase. And then the [25:11] design is just very impressive in terms [25:13] of what it can do from a design [25:14] perspective. Haven't they done a wonderful job on that? It's really nice that it puts out in the sandbox environment so that as you're asking, for example, the other day I'm a sculptor. I wholesale. Did you sculpt that behind you? The [25:28] thing behind you? Yes. Yeah. Who is that? Uh that is no one in particular. That's [25:33] just a clay study. I didn't know if it was like error. Those listening, there's a beautiful clay sculpture. What do you call it? A bust behind Robert. That's right. [25:43] Yeah. Thank you, Matt. Yeah. I was actually I thought I was retired from the business world until J. You're back in AI brought you back in completely immersed in the studio in the studio work and and over the la and the last and when gen AI first was publicly available 3.5 came out it was because [26:05] the lifetime before the clay studio I [26:07] was an operations exec the impact on [26:10] workflows operations organizations was [26:12] just so obvious it hit me like a 2x4 and [26:16] I've been immersed ever since but I do [26:18] still keep the clay work for my Zen [26:20] counterbalance [26:21] Nice. There you go. There you go. That's you do the the vibe sculpting. It's the next thing. That's the thing that's [26:27] caught on is like there's vibe [26:29] everything which is funny how that's [26:30] become like a moniker. Yeah. Lovable is Anton and the crew. They I think they've done it just obviously they've done a phenomenal job and they've Yeah. And the work that they do under the hood is it's a just a wonderful user experience. So you can chat in natural [26:46] language. You've got dev mode. I don't know that's actually trademarkable or copyrightable, but yeah, they got into issues with Figma. The response back to Figma was funny. It's some back and forth. [26:57] All right. I didn't see the response yet. I'm sure I'm sure it would. Yeah, that'll be good. The but lovable itself is a wonderful program. And what this [27:04] means is yeah, demos, value props, you [27:08] can create a you can create a little app [27:10] just for a meeting. It makes sense now. And for non-developers, like there is the side of it that's like you and Ruben and folks like that that are like deep into it, but anybody can now build have that experience and I feel like it's such a good inroad to then say, "Oh, how does this work? How does that work?" Then you leverage AI to teach you and there's nothing stopping you from progressing to where a Reven using AI as your teacher. [27:35] That is the uncomfortable truth [27:39] that literally the ability to access the [27:42] information and create a self-learning [27:43] program and and expose yourself to a an [27:46] entirely new [27:48] corpus of thought and knowledge is is [27:51] widely and freely available. And this is a nice segue, last thing I want to hit on. You mentioned the folks at Lovable. They're a tiny team in comparison to what they've done. And that's a new pattern that's emerging. [28:04] when you have AI, you just don't need as [28:05] many humans. You've written this book called The AI Dividend: Preparing for a Post Labor Economy. I'm just curious, and I think folks can let us know where they can find it, but what's your thesis around this? I think this is like the one of the next interesting debates that like us as society will begin to have. And I think it can go a multitude of different ways entirely. Obviously, we're not there [28:30] yet, but the writing is on the wall. We can feel the impact already. If you are a young computer science graduate, you know that we already are seeing the change in society and the impact as as these tools become increasingly more more capable. But it's and but it's the systems that are built with the tools, right? I suspect AGI won't be achieved by the base language model necessarily, but by some really clever engineering that is built on top of one of these. [29:05] That's such a good point, right? Large language models. Yeah. The impact on the work the workplace. Let's just let's take in a long term five years, right? [29:13] Which is almost impossible to conceive [29:15] of what that escalation and speed. I love how five years is now long-term, which is just hilarious. But it is like investors used to want fiveyear financial forecasts. It's like even three year threeear forecast. What does that mean right now? Contracts that [29:30] companies are entering into big [29:32] long-term the implications are [29:34] incredible. Anyways, so we know that we know what's coming and that is that the ability for these systems to be able to outperform the vast majority of humans in the vast majority of economically viable roles. That's how artificial general intelligence is currently defined by open AI, which most people don't realize. AGI is defined as being able to do your job, right? If it can do most jobs, then that's what they're that's the definition of AGI as it stands with open air right now. That's the course that [30:05] we're on. Whether or not if 3 to 5% of the working population gets displaced, that is a massive societal impact. and and we haven't been having the conversations necessary to digest and really prepare for what that might look like, let alone the 30% mark, the 60% mark, etc., etc. There'll always be there's lots of opportunities for things for us to do as humans with each other, but that the economic economically performing tasks for the majority of the economy will be capable of being executed by artificial intelligence in soon. So now what? Here's the principle [30:49] of the book and what I believe is best [30:51] for society and it's just my idea and [30:53] there's lots of others and and it's not [30:56] novel. There's three things that went into the discovery of the validation of the theory of the current era of Gen AI and that is the science, the capital, right? The folks that that backed it and paid for it and the data. Yeah. And the science and the capital are recognized with equity and the data is a complete mess. Right. [31:21] Yeah. Pilford's don't now we're just talking about going back and say oh let's just get rid of IP and forget copyright and so everybody so the scientists get paid and the capitalists get paid but the people that contributed the data to the achievement of the breakthrough don't and I think that's a fatal flaw and it's really it's a it's now made its way through the entirety of the large language model ecosystem because you can't track where where that stolen data went but you know it's being utilized That's the thing. It's very hard to trace from like an IP perspective. So it's like even if you wanted to good luck, you know what I mean? Because it's just so difficult to truly tell it's leveraging in its response. [32:05] That's that's right. Especially constitutional AI will have layer protection systems to make sure that it's not responding in a way that does clearly display what it's aware of, what it's been trained on. So that leads me to the idea that data should be recognized. It should be recognized as as effectively as equity and it should be paid a dividend and that dividend should be available to everybody in on earth and it should come directly from the economic activity of artificial intelligence and there is no reason that it ought to be something restricted to basic because the economic implications current for us will be profound. and the ability for all of us to benefit from as a as from a from that structure specifically a dividend paid out by participation in equity. It takes it out [33:05] of the hands of governance because [33:08] governments are led by parties and [33:09] parties are fickle, right? And and this is much more foundational. I think that an option for how to address the increasing displacement of human labor would be for a universal participation in dividends of the economic activity of artificial intelligence. And that's the I like how you framed it as Yeah. I like how you framed it as dividends. It's almost like democratized [33:34] capitalism. Yes. In a sense because all of our data has contributed. We can't say where, how much, when, but we know it's there. Yeah. No, it's definitely interesting. [33:45] And where can folks find the book? Is it It's up on Amazon. And then the the the Kindle version is titled tokenized and there's more words coming. Human race, that's your company on the Gentic Engineering side. That's right. I [34:03] think folks can find that. What's human race.ai? Yeah. And we're largely experimental, but also we love joint ventures. So if there's projects or [34:12] joint ventures that people have an idea, [34:15] they want to get it built. That's the kind of stuff that we love to engage in. Yeah. We need to do something together there. What's the coolest thing you've built or been a part of or that you've seen out of curiosity? Anything come to [34:26] mind? Yeah. The one we saw today by Ruben. Yeah, I know. Because you can just pull things out of the ether that's really good for us to stretch exercise our elasticity of creativity. Yeah, [34:37] for me what I'm working on right now, [34:38] which I really am enjoy, excuse me, and [34:41] the first newsletter is about to come [34:42] out in the next week or so, but that's [34:44] the awareness layer. The awareness layer as a critical structural component of any organization or business conceptually. And what I'm working on within that is is that chain of deep research and how to map out that creative space when you point a team of agents in a specific direction. But the awareness layer I think is one of these the applications of agents and the applications of artificial intelligence that really hasn't crystallized clearly yet and I think that's a space that we can contribute to because for example a product owner you take a startup and in the old days a startup would come they do a competitive analysis right and so here's all the competitors and this is what the space looks like they do it once maybe revisit it eight months later something big is that's it. That's gone. [35:38] That we now with agents we can be aware [35:41] of fairly be aware of absolutely every [35:44] competitor in our space have all of [35:47] their concepts mapped out. We know exactly what their feature set is. We know what their pricing is. We know what their sentiment analysis in the marketplace is. And that's all dashboard. And that's going to that is a [35:57] tool that I can use as a product leader [35:59] in order to ideulate and AB test into. So that's an awareness layer in one specific really obvious case, but it doesn't exist for the vast majority of companies yet. There's an enormous amount of development work and opportunity that will come just from organizations opening up their eyes and expanding their field of view in the marketplace. It's funny on the competitive research. I was listening to a podcast. I think [36:27] it's like the Greg Eisenberg, but he had [36:29] the CEO from Lindy, which is one of [36:31] these AI, think of it like ni in that [36:35] space, right? And he was getting overwhelmed on the competitive side because he had an agent that was doing this research for him and it's another company. What he did is he set it up to say, "Okay, all those companies you researched, look, let me know in six months or whatever time frame where they are now." Right? And you see that 90% of them just fizzled out and it allowed him to calm his nerves. How many people are actually [37:00] progressing past just like a splashy [37:03] launch? It's kind of an interesting angle. Matt, it's beautiful because you know where this leads is two years ago or a year and a half ago I said roof said this is I was actually at the beginning about a year ago artificial intelligence in the longer run is going to be deflationary obviously because it enables things to make it's it's pennies per millions of tokens uh for this intelligence this is a really good case point because when you have the ability to have near complete market visualization in a sector then ultimately that's going to drive creativity and it's going to drive competition. And one of those one of those buckets is price and you have market triage and it's more difficult for people to say I'm going to sell this for $800 when I can buy it for 50 and I just I make my living on ignorance, right? My my competitive advantage is you don't know what I paid for it. [37:56] That's coming to an end. Yeah. Another fascinating area where there's going to be big implications. Yeah. so many areas. Let's give the [38:05] Agentics Foundation plug for Ruven's [38:08] community. Free for anybody to join, but give the breakdown. This turning into an actual not for-p profofit foundation is relatively recent in the past month or so, but how do people get involved? Where do they go? By the time this comes out, the Discord, it's out there now, but I think it'll be humming along, but give us the lowown in terms of how people get engaged. [38:28] Sure. The website is atix.org org and on that you can find the discord, you can find the WhatsApp. The WhatsApp you may have to try to jump in a couple times because again it's capped out but on there you can find everything about the organization. The website is in evolution. So there's some tools on [38:48] there. ultimately the Aenics Foundation there's so much talent and experience in that that in the 1,200 let alone the 150,000 but of active engaged conversations that are taking place every single day in that WhatsApp group really it's about giving a forum for the membership base to be able to put forward tools and ideas and best practices for each other and that is the foundation and then the working local chapters are about making sure that people have networks in their local community to be able to explore the tools and help communities around the world put them into play. Yeah. The Agenics Foundation I'm temporarily leading up the AI safety and responsible deployment committee. There is in order to ensure that with these tools comes a framework and an understanding and another set of tools that help us do that responsibly and and proactively socially positive social impact. And then there's a committee on [39:46] research and of course member services, [39:49] the operations side, the chapter [39:51] management. So there's a little over 10 different working groups or teams or committees within the organization and it's open. We welcome everybody to participate and and hop in. They can sign up for that on the website. And then also chapters if there's if you're in Milan or there's a city community that you would like to host live events and have the support of the Aenics Foundation there on content promotion and actual materials to work with then then you can sign up as a as an ambassador on the agendics as well. [40:23] So really excited. I'd say for everybody check out check come to a Friday hacker space session. Yes. and you'll understand why we're high on this this community. It's it's the best community out there. There's a [40:37] lot of AI communities. It's overwhelming. This is the one that I proactively recommend to people. But Robert, thanks for being on talking some AI. Appreciate you being on. [40:46] Yeah, Matt. Wonderful. It's always great fun. Good to see you again. And I look forward to hearing. You've got a bunch [40:51] of great projects on yourself, so look [40:53] forward to hearing about them. Awesome. Thanks for listening to the Talking AI podcast. If you enjoyed the show, give us a follow or subscribe on your favorite podcast platform. And don't forget to leave us a review. We [41:04] love those. For more info on Talking AI, visit talkingodcast.com. [Music] [Applause]