Epicenter - Learn about Crypto, Blockchain, Ethereum, Bitcoin and Distributed Technologies - Matan Field: DAOstack – An Operating System for Collective Intelligence

Episode Date: May 31, 2018

As a society, we have organized as tribes, hierarchies, and markets to accomplish the most impressive of achievements. Human cooperation and collective organization are present at nearly every significant milestone in the history of human civilization. As we move towards an increasingly connected and automated society and economy, there will become a need for decentralized infrastructure which enables companies and markets to make fast decisions at scale. We’re joined by Matan Field, CEO of DAOstack, a new platform that aims to become the operating system for collective intelligence. DAOstack is building a toolset to allow decentralized governance and building self-organizing collectives at scale. Topics covered in this episode: Matan’s background and journey since founding Backfeed What is a DAO and the necessary components to create a functional DAO The role of DAOs in today’s society and over the long-term DAOstack as “WordPress for DAOs” The different layers of DAOstack and their respective roles Holographic Consensus and the governance model of the DAOstack Genesis DAO The purpose of the GEN token and the idea of circular token economies DAOstacks recent crowdsale and upcoming project roadmap Episode links: DAOstack Website DAOstack Introduction Video DAOstack on Medium An Explanation of DAOstack in Fairly Simple Terms Decentralized Governance Matters DAOstack White Paper Epicenter Episode 115 with Matan Field on Backfeed This episode is hosted by Brian Fabian Crain and Sébastien Couture. Show notes and listening options: epicenter.tv/237

This is Epicenter, episode 237 with guest, Matan Field. This episode of Epicenter is brought you by Shapeshift.io, the easiest, fastest, and most secure way to swap your digital assets. Don't run the risk of leaving your funds on a centralized exchange. Visit Shapeshift.io to get started. Hi, welcome to Epicenter, the show which talks about the technologies project and startups driving decentralization and the global blockchain revolution. My name is Sebastian Kutjua. And my name is Brian Parban-Curban-Cur. We're here today with Matan Field.

He's been on the show before. We were just checking before, and it was in January 2016. And he was working on a project called Back Feed Back to End. So we're going to speak about that a little bit, but mainly we're going to speak today about his new project, which is a project called Dau Stack, which is trying to build kind of tools and frameworks for decentralized organizations.

So thanks so much for joining us today, Matan. Thanks, Brian. Really a pleasure to be here again. So maybe we can start there. I mean, so you tell us a little bit about how did you first become involved in the blockchain space and how did that lead to initially starting backfeed? Sure. So, yeah, I've been working as a theoretical physicist, as my profession,

done my bachelor's in physics and mathematics and then PhD in. string theory. So that was kind of like one side of my of my career. And then in parallel to that, I was very interested in social entrepreneurship and mostly around alternative organizations and cooperatives. So I found that a food cooperative, organic food cooperative and a community garden and such stuff. And when I was doing my postdoctoral research at the Technion, that was was kind of like, I guess, the end of 2013. And during that, I had an idea about social ride chairing.

And I started to work on that idea with some friends to build a social right sharing app. And via that project, we quickly discovered a blockchain. We had a need for generating cooperation at scale. And I kind of knew that we need to kind of like somehow track values or value of people. And to have some sort of token, I didn't know about blockchain back then. And then someone told me, look at Bitcoin, look at this thing, Bitcoin, and even look

at this thing Ethereum. That was the same months when Vitalik published his white paper, I think it was November 2013. And when we looked at that, it was kind of like instantly clicked as a technology that we were looking for. And quickly, the project became a decentralized right-sharing. application on the blockchain. Back then it was on Bitcoin blockchain. I think it was one of the first applications on the Bitcoin blockchain. And that kind of like accelerated very fast. I quickly quit the academy and focused full time on that. But as time went by, I was more and more

interested in the core problem of our how coordinating a large number of people. On January 2015, I quit project. I've quit Lazouz, the ride-sharing project, and founded my own company, Backfield, to solve that problem. So to build protocols and platforms for coordination of large number of people or for Dow's. So that was the goal of Backfield. Founded around January 2015. It was early days. We still thought that ICO is too far and risky and all that. We raised the regular legacy capital from Angels and have been working for 18 months. Basically, it just ended our last work around the explosion of doubt that we'll probably speak about later.

And at that point, we kind of like we felt that we need to stop to hold a moment for a moment and reassess where we are at, reiterate on the focus of the product. I, one of the most, like, the urge and burning thing was that I didn't have a technological partner and I didn't want to continue further without finding that partner. And then I took the time to do some research, both finding that technological partner and focusing the product that we wanted to build after like 18 months of building several iterations, several products. Yeah, it took six months to make this focus.

mostly to join forces with my main partner, Adam Levy, who was also a PhD in physics that I knew from the academy, but he's also very highly talented technologists. And around January 2017, we found in the beginning we thought a lot of whether to continue it as backfeed or found a new company. But after some iterations and checking up with external players, we realized that it will not be feasible to continue under the same. It was too long, like too long has been passed, it would not be feasible, for example, to raise money to the old company. So we started as a new entity. We also started with a new strategy, a new co-based and everything, but the idea was similar to build the platform for the centralist donors organizations. Cool, fantastic.

Now, so you worked on Backped, right, which is a similar problem, and then you switch or you started DAWS, are there some kind of big insights or learnings that you took away from Backfeed? So you said, like, okay, these things I'm going to have to pay special attention to these things I'm going to have to do differently this time? Absolutely. So, I mean, when I started Backfeed, I was kind of like more thinking along the interface, like how the interface for Dow's looks like. Only after a few months, I realized that the big, big problem is not even the interface. I mean, interface is a problem, but there is a lower problem of the protocol, like how DAO's are operating game theoretically. And already within BackFeed, I kind of like shifted from focus on the interface

to focus on the protocol. One of the lessons from BackPid was that this protocol space is enormous and it contains a lot of big challenges and more so that different use cases and different elements in the DAO landscape, if you wish, will require different protocols. So one of the main understanding from Backwood was that it's not maybe right to focus and build a protocol, but rather it's better build a framework from which you can build any Dow protocol and let those protocol evolve under economic evolution. So if you want, get ready for building an infrastructure for an ecosystem and then let that infrastructure evolve over time.

So that was one of the biggest shifts made from Backfield to DaoStack. In DaoStack, we, instead of tackling a protocol or a use case, we firstly build a whole framework for governance. It's kind of like we'll probably get back to that later, but we call that WordPress for Daozo. So a framework with which you can build any governance protocol. That was one big lesson for Backfitt. maybe another big lesson was that in Backfin,

we kind of like started very theoretical. And we firstly wanted to solve everything theoretically and then to start building things physically. And even we firstly build off chain because the technology was not mature. And we said, yeah, we'll get to be launch and only when the technology is maturing up. Further, in back in Dowstack, I realized that we have

to develop with the technology. We have to mature up with the technology. So we started our code based on the blockchain from day one. It was really important. With an aim, with a very specific aim to produce a very specific product and get it to market adoption. And later we also built on top of that infrastructure. We also built applications, or right now one application for now.

So it was kind of like in a way, I would say the different, the order of things was kind of like upside down. So I'm interested in this approach that you've the scripted. to build in this product. So you mentioned that when you were building backfeed, that you were building specific use cases and that you sort of shifted in Dowstack to building a more generic platform. Is that correct? Correct. That's exactly correct. I mean, eventually we go back to use cases, but we had to take one step backwards to build a more robust framework, both in order to be able to produce a vast number of products

and also to enable others to build a product, but also from the understanding that those products will have to evolve rapidly and you need to be ready with an infrastructure that can allow you to evolve them rapidly. So how much of the work that you had done on backfeed has now been ported over into Dowstack? In terms of products, not necessarily I mean applications, like any product, that code-based protocols or anything you can name as products almost zero. We completely kind of like started from scratch, code-based protocol, everything we started

from scratch. But of course, I would say that we started from scratch in the right place because of the lessons learned before. So how you measure that in percentage that's the same. for you to decide. So let's speak a little bit about Daos in general. Can you, first of all, define what is a DAO? Sure.

I mean, sure is an overstatement. That's a quite hard thing. So firstly, the centralized organization is something that, I mean, an organization, generally, an organization is something that gets input from agents, right, members of organization, and then spells out output, decisions, transactions, and so and so forth. Now, the one first difference of Dow from regular organizations is that the rules of processing inputs into outputs,

those rules are coded on the blockchain. They are coded on a trustless, decentralized technology. That's the first difference. A second difference is that those rules allow for organizations to grow and scale while become decentralized, which means that this decision-making process is not held by a small number of people

or agent members in their organizations. That's another way to, or another criteria, if you want, of decentralization. Now, you can also ask, like, how they look like, not like the definition, but rather, like, what is the flavor of those? So I would say that the characteristic or flavor of those is that since decision-making

is pretty distributed, one outcome is that these organizations are much, much more scalable, much more scalable and still much more agile, and at the same time remaining much more agile. So there is actually a very well-defined way to cracker as that. So every organization of the planet has a common factor, which is that they become less effective per person

as they grow up, as they scale up. So I imagine that DAOZ is something, on the contrary, more similar to the way that network affects and free markets and internet works is that these are structures that make decisions and make products and coordinate, but at the same time become more effective when they scale up. So it's kind of like the opposite

of the way that regular organization behaves when you grow them up. And with that, it's also the prediction that once you created that creature, it will basically grow up exponentially, explode in that domain, in its domain. So can you perhaps give some examples of what are some decentralized organizations

that exist today or that have existed in the past that, you know, don't, not necessarily in the blockchain space or that use blockchain technology, but just generally speaking, what are some good examples of decentralized autonomous organizations that don't function with the central governing structure? So, firstly, there is no, you know, full-blown down,

Dow does not exist. I mean, I'm claiming that there is a need for that, I think it will explode once it's exist, but it doesn't exist yet. However, we have many examples of things that are all. almost does, or seem to be close to, or reminding us, or hinting us how dows will look like. So for example, in the blockchain space, so blockchain itself, right?

Blockchain itself is in a way, an organization, it's a coordination of large number of people, producing something. The difference though is that it's producing very, very specific thing. It cannot do anything else. The Ethereum project, not the blockchain itself, but actually the network around the

project, including the developer community, and all that is getting closer to something that looks like that, but not yet. You can also look at examples which are decentralized structures, but they don't get, again, they don't have a decision-making capacity, such as the internet itself or BitTorrent or, you know, open source organizations, et cetera.

But they don't have a decision-making capacity that we're speaking about. Maybe the closest thing that I'm aware of right now is something like, actually, I've met the CEO of R-loop. I think it's one most exciting project that I've met. It's the team that was winning the Elon Musk competition about generating Hyperloop technology. And while the other competing team that did not win the contest

raised $200 and $300 million, the winning team was building a working technology with, you know, half the speed and fifth the scale with a budget of $200,000 and $1,300 distributed engineers over 60 countries, all of which hold day jobs. So that's like the closest thing that I've heard of to the central organizations. But the decision of capacity is there in terms of budgeting and all that was still fairly centralized, I guess, and also was very much based. on good faith, like on volunteering. But if you would like to reproduce this kind of behavior

on different causes, not based on volunteering, and on a more general domains, and at the larger scale, you definitely need to have a systematic decision-making engine that can scale up indefinitely. When we think about Daos, or when you think about Daos, is this something that you see as just the next form of organization, you know, maybe had like different forms of organizations in the past, and now there's going to be DAO, which is basically, you know, structured organizations where you have explicit processes for making this decisions, you know, that kind of scale, you have these network effects. So do you think that down the line, you know, most companies will be sort of

does, maybe countries or like large social organizations or local organizations and maybe nonprofit communities, will they all start to resemble Daos or is Dao is more a solution to a specific problem which applies to maybe a small number of use cases? That's a really good question. So I think the answer is yes. Or let me make more specific. The advantage of the DAO is at large scale. You know, if you operate an organization of 30, not necessarily the central organization.

is superior to centralized organization. But if you're operating an organization of 100,000 people, then yes, I think that the decentralized organization is vastly more effective than centralized organizations. And thus, just like the way that Internet, so Internet replaced kind of like global-wide distribution networks completely. But then you still have distribution networks locally and inside the Internet.

So in the same way, I think that large organization would be completely decentralized in the future, but you'll still have companies operating in that global decentralized network. But still, at scale, I think that DAWS will be orders of magnitude more effective than regular organization. And thus, just evolutionarily, I think every organization will either need to decentralize itself or basically be out-competed vastly. So does that mean, I guess, the implications of this,

would also be you see in the future kind of the demise of, you know, the organizations that we know today, whether that would be something like, you know, the U.S. government or Apple or maybe even United Nations, like all of those very large, complex centralized organization. You think those will essentially be out-competed and just not be able to adapt and respond as fast as, as or run organizations? I mean, I think it's a process, it's going to be a long process. And there are domains where Dao's are kind of like,

it's harder to decentralize them. So, for example, anything that its core activity is essentially physical and geographically local is a bit less fit the model that I'm describing. So just because of that, naturally, I think states will be much harder to centralize. Also, you know, anything that the main assets that the organization is managing are physical assets.

For example, and not only, I mean, also the ownership structure is kind of like, so for example, factories. Factories are maybe last to be decentralized. You need to decentralize the technology of manufacturing in order to decentralize them. I mean, you can decentralize the ownership of the factories already today, but decentralized the actualized

the actual production will require, you know, for example, to be based on 3D printing, etc. So, or micro factories. So, yeah, I think it's not like black and white, and it's not that Google will disappear tomorrow, but definitely what will happen is that those organizations will also gradually move towards greater degree of systemizations. So what do you think is the positive outcome, if this really happens like that, and we're going to have these super well-working, large number of decentralized organizations at scale? What will the world look like? That's a really good question because also it communicates with the question of good and that, right? So, you know, one way to look at things is simply about efficiency. I mean,

a lot of things will become much more efficient, the market will become more efficient, opportunities, et cetera. But that's just one aspect, and I think not the most interesting one. The more interesting aspect, you know, I think, and I think so more and more so every day, I mean, if you look almost every place that you look at the world, you know, the systems, when you look at the system, how things work, you know, what motivates agents in the system and how they behave, you feel that everything is broken, like literally everything is broken. And when you look inside, you understand why it's broken.

It's boring for a reason. It is broken for the good reason, or not good reason, but for the real reason that there is no good alignment of incentives. Like, you know, I just spoke about it today with a friend. Just take any topic on your mind. Like take the topic of a garage. Like my garage owner doesn't have the incentive to actually repair my car. he actually has the incentive for my car to be as broken as it can.

Or the health system doesn't have an incentive for us to be healthy. It actually has the incentive to keep us sick. And that's built in in the economics, and then it derives the rest. And part of that problem of incentives is the ability to capture the power. So the power is constantly concentrates in a hands of few, and then the interests are aligned around the interest of those. of those individuals, or centers, not necessarily individuals. So one, I think, big, big shift would be that power will be much more distributed,

on one hand. Number two is that crypteconomics models will design a much, much greater line of interests. And on general, I think the global network economy will be much more, not only much more efficient, but also much more, you know, I'm trying to be careful here, not to say fair, because I have in my mind the word fair, but I think it's not just about fairness, it's about more resiliency and sustainability and, you know, harvesting more of the power of more people because they are more involved in greater alignment. And eventually, I should also, I don't want to advocate for that, but I also think that's the only way to actually resolve,

the weak wicked problem such as climate and other problems we're facing. That's the only way to resolve that. I think without that trying to resolve climate while there are major

gigantic corporations that have the incentive to actually make our situation worse is just like fighting Don Quixote in the windmills. So in the white paper it says that the Dow stack is sort of WordPress for Daos and that one would be able to create a Dow just as easily as one can create a blog on WordPress. Can you explain what this means and what this will look like for the end users, so whether these are developers or entrepreneurs or actual users of the DAOs that would be built on this platform? Absolutely. So when you say a DAO, you can look at it from.

several different levels. So let's see at the first level. The first level is the level of the game, right? When you say a doubt, you say there is a game. There are certain rules. People can play. People can input whatever they want into those rules, and things happen, right?

That's the game. Now, of course, the rules is that is one layer. By the way, there is a layer below the rules, which is the blockchain, of course. This is the layer that facilitates those rules. So there is the blockchain, and then there is the layer of rules. and then you also have higher layers such as interfaces, right, the way that people actually interact.

So if you if you zoom in for a moment at the layer of rules, when I say that you can you know establish a DAW and you know and operate a DAO easily like you would build a blog from in WordPress the meaning is that you you have you already have we already have that you have a framework of rules it's a framework of rules for coordination of people that you don't need, if now I want to establish a new DAW with its own rules, with its own governance protocol, I don't need to

code that from scratch. And rather I have many modular, many modules of rules for coordinating people, and I can build a few models one into the other like plug and play, combine them and, you know, boom,

I have a decentralized organization. And I want to have slightly different rules great, I can pick up a different module, plug it in, maybe configure some parameters, and I have another organization, and so and so forth. So I don't need to code the rules each time in beginning, but that's also why it's very easy to upgrade the rules, you know, and evolve them over time. So that's at the rules level. Now, at the same thing you can imagine at the interface level, but I mean, our focus right now is in that level to enable others and also ourselves, but mostly to enable others build their own interfaces,

but then you can think about the same ideology at the interface level. You have certain components you can put inside and build an interface for a DAO. So as a user, if I'm building a DAO on DAVStack, I would have access to interfaces through which I could very easily, as you mentioned, sort of plug-in-play, you know, build this, this Dow sort of like with Lego blocks, right, and like bringing all the different rules and components and governance structures and schemas

that I need for my organization. I think maybe where the challenges and where I'd like you to address how Dow Stack would address this is as a user building a Dow, perhaps I need some guidance as to what types of blocks. You're like, which plugins do I need basically to, that, to, that are better suited or better adapted to the type of organization that I'm building? Let me maybe give you an analogy. If, if I'm building a company that's meant to scale to many employees, you know, hundreds of

employees sort of spread across the world, you know, with some venture capital from different places around the world and certain types of corporate structures, like, you know, there are sort of established ways that you can start a company for that. Or if I'm starting a small business that's only going to operate in one country, well, perhaps there's a certain type of legal structure that I need. Or if I'm building a Dow, well, maybe I want to have a Swiss foundation and a company in Delaware. Similarly, for any type of decentralized organization, one can presume that there will be certain structures that would be adapted to certain organizations.

how will a Dow stack or how would a user be sort of educated and gain the knowledge necessary to build the right type of DAO for his organization? Great question. I mean, totally. So the whole idea of the stack is to provide different solutions at different levels to different, you know, level of users. So, for example, if you start from top down, if you start, you know, with the average user, then instead of working with modules and plugging them in,

you'll have completed templates. So we have one, two, three, four templates, you know, with names for different use cases under different conditions, and then you can just click a button that's it. You have a template, you just need to feed in the parameters. For example, the founders of the Dow, you know, the voting power, each of them hold, or something like that, on the token distribution, et cetera.

So you'll have kind of like completed templates. Then for a slightly more advanced user, that you want to kind of like play themselves and kind of like experiment with different governance protocol you'd have modules a completed module that you can combine and get it out for slightly more advanced users

and developers you have the library of modules but then it's an open source library and then any development can come up and add yet another module and new rule that you can play with and so and so forth so yeah so you have we have

a solution at different levels for different audits sense for an advanced user or for the earnest users. This episode is brought to you by ShapeShift, the world's leading trustless digital asset exchange, quickly swap between dozens of leading cryptocurrencies including Bitcoin, ether, Zcash, Gnosis, Monero, Golem, Auger, and so many more. When you go to Shapeshift.io, you simply select your currency pair, give them your receiving address, sent the coins, and boom. Shapeshift is not your traditional cryptocurrency exchange. You don't need to create an account.

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And we'd like to thank Shapeshift for their support of Epicenter. Can you walk us through the different layers of the platform, the different sort of layers of the stack and the role of each layer? As I mentioned, there is, of course, the blockchain. And then above the blockchain, there is the rules for governance of organizations. Maybe just a question on that. So blockchain, does this mean like Ethereum or like a new blockchain or, like, a new blockchain, or will DAO stack

kind of be able to operate on many different blockchains or how is that going to work? Yeah, good point. So right now we are all coded on the Ethereum blockchain. Thank you for that. Over salinity. In the future, there is no reason why not to be interoperable

over several blockchains. But right now, the only blockchain that makes sense for that is Ethereum. So, yeah, that's the current situation. Probably for the, you know, for seeing future. So you have the blockchain there. You can also have a decentralized database layer such as IPFS. We actually are, our earliest version was coded on IPFS as well,

but right now we are still database-wise. We're using centralized servers. And then you have the rules there. So we call it ARC. Arc is a framework for governance, which you could basically architect different governance protocol, basically any governance protocol. So kind of like somewhat analogous the way you would say, okay, with Ethereum, I can program any smart contract.

Then with ARC, it's a higher level framework of facility with which you can program any governance protocol. So this is the next layer. Basically, yeah. And so question on that. So if you say any governance protocol, do you mean like, let's say different types of voting? systems or maybe something else where you have some kind of. Right, right, right. So what do you mean by any governance protocol?

So I would say that any governance protocol, as I mentioned, governance protocol is simply that logic that collects input of agents and translate that into decisions, outputs, whether the decisions are transaction of funds, budget, or whether decisions are registering results on databases or maybe operating yet another function. So generally this engine of collecting inputs and making decisions, you can, and that's what we call governance, you can break it into two categories of rules, two kind of rules. The do's and the don'ts. So doze means that, you know, if certain things happens, then we do such such. For example, one example for that is voting systems.

You know, if someone makes opposals and then certain number of people say yes, then under some condition, let's execute that proposal. This is a voting system, voting logic. That's a yes, that's a do's kind of rules. Another kind of doze can be a token saying. If someone is sending such and such ether to that contract under some conditions, the contract will automatically print new tokens

and sending that. That's also a kind of dues. Then the other family is the don'ts, which means that let's, for example, crystallize the organization with a statement no matter what will ever happen, the organization will not print more than 1 million tokens. So that's a don't.

No matter what, this organization that managed $1 million will not spend more than $50,000 a month. That's a burn rate. That's another don't. And the architecture is as flexible as it can get, so you can actually combine the dos and the dudes. For example, no matter what, you will not burn out,

burn more than $50,000 a month. But scheme number six, that can approves in the voting with majority of 70% of reputation, can change myself, can change the don't. So you can combine those things and basically create any sort of logic for those rules or if you wish any governance system. So that's the there's a truth. It's called ARC.

Then we realize that if you want to build an ecosystem, if we want now to allow for thousands of foreign developers to work with this engine, and to build collaborative decentralized applications, we need to make it much more accessible. So then we've built an ARCjs, which is a JavaScript library over Web 3 that allows you to basically operate ARC,

build organizations, configure them, operate them, vote anything, directly with commands over JavaScript. There is some other layers that maybe are secondary in importance, and then of course at the end you have the layer of the applications. So many different applications, that's due to the fact that they're all writing over the same open protocol, they're all interperable.

So different DAOs can use different interfaces into many ways. Do you mind speaking a little bit about the Genesis DAO? And what is the role of the Genesis DAO in this ecosystem of different tools? The idea was that we have to, we will have to experiment. I mean, we have to do some dog food. We have to eat our own dog food. So while we have a company that works on further building effectively right now, the Dow stack platform, we want to have also a parallel experiment,

a parallel decentralized experiment that kind of like aims at the same goal, same mission. So the Genesis DAO will actually, so maybe maybe, maybe, Maybe it's here a moment to mention we've done like a token sale initially privately, and eventually some of it was publicly. And we raised back then at the day it was $30 million. And the idea is that majority of that fund, in addition to majority of token distribution, will be managed by that decentralized fund.

So Genesis is that decentralized fund that operates on top of Dowstack, with majority of that capital, and in that empowers and engines, if you want, the establishment of the growth of the growth of the DAUSTEC ecosystem. So, you know, rewarding and investing and supporting projects that support the DAUST ecosystem in one of three ways, either projects that build infrastructure components of the stack, more tools, more plugins, more modules, more governance modules,

or projects that are building more interfaces to the stack, more applications. So we've built the first application, the native application alchemy, and now there is a bunch of other applications integrating the stack. So companies that are building interfaces and applications integrated in the stack. And finally, projects that are themselves DAWs that are using the stack in order to yet do something else, maybe build something else, organize or manage, collectively manage assets, or collectively curate databases or whatever. So that's the idea of the Genesis Dow.

So this first application that you've built, this Alchemy application, what does it do precisely? Right. So Alchemy was, I mean, initially we wanted to build the first interfaces for Daos. So how do you make a large number of people organize and build something together? But then we decided to focus, to make it slightly more focused and answer a real need that people have right now. And so it's a decentralized budgeting and rewarding system, which answers the following pain.

So today, you have in the blockchain space, you have many examples of projects that have very large capital. So for example, the flagship example would be the Ethereum Foundation, the Ethereum project itself. So the Ethereum project, let's say, managed just throwing a number, manage $1 billion in capital. So $1 billion is roughly infinity, right? It's much more than you can spend in a short time frame.

So it has infinite capital. So OK, so there is no limiting factor in terms of capital. Now, we also have thousands of developers, if not tens, or hundreds of thousands of developers that could work on the economic ecosystem. So there's also no shortage of human capital. So what is the limited factor? What is the actual limiting factor?

factor right now for solutions, for producing solutions. Like why haven't we solved yet the scalability problem? Do the Ethereum Foundation lack capital? The answer is no. Do the Ethereum Foundation lacks developers? I mean, in the broader ecosystem, the answer is no. The actual answer is the decision-making capacity

to wisely deploy capital into human capital and produce solutions. And that's exactly the role for Alchem. So decentralizing that function, the decision-making function. It's a, you know, people can get into the system. They can make any proposal to use of that fund. And then people can vote on that proposal and produce decisions in large numbers and effective incapacity and effectiveness.

Yeah, I'm super excited about that because this is one of the things that, you know, concerns me a little bit is that all of these projects have started, right? And they raised money and maybe into foundations. And now they meant to. launch these decentralized networks, but they were actually operated or controlled in a fairly centralized way. And now, I think that's, it's not the fault of these people or, you know, it's not the fault of these projects. It's just that the tools aren't there yet to kind of build a decentralized way from the ground up. But I'm, you know, I'm unsure how well it will actually work to over time transition to a more decentralized organization or whether this will not be

sort of fatal for many projects that they will never be able to decentralize anymore. So I think when projects can from the very start, like, you know, deploy funds and manage and grow in this collaborative decentralized way, I think that would be extremely powerful. Yeah, I agree with you, but I have to admit that I'm quite surprising also by the big projects how seriously they're desiring to decentralize themselves. more so willing to do real live experiments with real funds to check that up. I think a lot of the biggest projects in the space right now sincerely look for Dow solutions to manage their hundreds of millions of dollars.

They just are waiting to see that technology comes up. And once the technology is ready and it's almost ready, we are launching the pilot these days and then actually experiment with real projects, such as Gnosis, for example. And I think then we can explore, you know, maybe not with $100 million, but maybe with, you know, $100,000 first and a million dollar then. But once we can show, we can show that we have a technology for producing large number of decisions effectively by the professional crowd, and then we produce much, much faster growth and innovation. And I think once a project would see that, you will see massive adoption.

So let's talk about consensus. The white paper states that Dowstack uses a consensus model called holographic consensus. Can you describe this consensus model and how it's different from the ones that we know, like proof of stake and proof of work? Right. So firstly, just award on proof of step before it, it's a different kind of consensus. So basically there are two families of consensus. Actually, we can discuss more than two. focus on two.

You have consensus about, I call them objective realities. So blockchain is a consensus engine about objective reality. So objective realities are realities that a computer can decide if it's yes or no. So for example, whether to add a block, whether the block is legitimate is an objective reality. The program can read that and say yes or no. So objective consensus are falling

under the title blockchain. That's what a blockchain is. It's a decentralized consensus engine for objective realities. And then you have proof, there you have proof of work, proof of stake, and so on and so forth. Now the interesting stuff, or the next interesting stuff, is about reaching consensus about subjective realities.

So, for example, whether this claim insurance should be handled or not, whether that article is good or bad, whether we want to approve budgeting with $10,000 this or that task. So this is subjective because a program cannot read that and say yes or no, because by definition the decision is subjective. It's not objective. The first step was to build consensus engines for subjective realities, and that's what falls under the title decentralized governance.

Now, what is the problem of decentralized governance? And it's actually the exact analogy problem to decentralized, I mean the consensus of objective reality. It's the same problem, which is the scalability problem. So just as we have scalability problem of blockchain, you have scalability problem of decentralized governance systems. Now, what is the scalability problem? It's very easy to understand.

You have 1,000, let's say let's make it easy. You have 1 million voters, 1 million agents in an organization, and let's say that there are equal voters. So each of them has equal weight, no, voting 1. Now, naively, if you want to be resilient, like if you want to make sure that the system is not manipulated by a small group of people, that the system is well represented by the majority, the decision that are made

are in line with majority, you would need to require that each and every decision is looked by, you know, the entire, by a majority, approved by a majority of the organization. But, of course, that completely doesn't make sense. I mean, you wouldn't be able to produce a single decision. decision and definitely not a million decisions a day or a million decisions a month. So you see, there is a strong tension

between scalability, the ability to produce more and more decision effectively and resilience, the incorruptibility or non-manipulability of those decisions by small minorities, and even more so having those decisions be representing really the mind of this hive mind of the doubt. to solve that problem, and I think that was the biggest actually problem of Dow's upper-a-beat-day.

So to solve that problem, we've designed holographic consensus. Now, there are some alternative solutions. One of the hottest, I think, of them is, for example, TCRs, token curate registries, but then we can also dig into why I think those pure economic governance models will not work well. and the root of holographic consensus is basically combining two different systems inside the government system.

One system is the reputation system. Votes are weighted, agents' votes are weighted by the reputation. These systems are highly resilient, are not very well manipulated, but they have part of scalability. And on the other hand, markets, like prediction markets, for example, They are highly scalable, but their problem is they are highly manipulable. So we combine those two systems together. You have both a prediction engine and prediction market and a reputation system,

and together you can show that you can generate both scalable and resilient interaction at the same time. You're basically translating the tension between scalability and resilience into an economic problem that you can always grow if you're willing to pay more costs. and basically the prediction engines, so the people who are placing the prediction, they are not answering, like, future people, for example, they are not answering what is the right answer,

like what they want to be the result, but they're actually placing predictions about what they think that the reputation system will decide. So that's the core essence of program. And in essence, maybe just say what it allows you, it allows you to make decisions, fast decisions by small minorities, but at the same time, ensure that those decisions

will be in line with the greater majority, with the Dow majority. And the way that it ensures that is that you're basically creating a crypto-economic incentive to identify possible mismatches. So anyone that can identify a mismatch between a process that seems to go to that way and what people think that the DAO would vote

would be that way, anyone that can identify that mismatch can make profits by, predicting that misnage. This is actually quite interesting. Could you elaborate a bit more, maybe walk us through how decisions are made with holographic consensus, like if it's a concrete example of how, so if you marry this reputation system and this prediction market, and who are the actors basically taking part in this

consensus? Right. Yeah, let me give you a concrete example. By the way, I also need to kind of say that this holographic consensus is really a concept, just as much as blockchain is a concept, and off-chain computation is a concept. Actually, there is a close analogy between off-chain computation and geographic consensors.

And I'm saying that to kind of like explain that once you understand the concept, you can have many different protocols that falls under that title. So it's not a protocol, it's a concept. Now, but nevertheless, let's go through a quick example. So let's say that, let's focus on the simplistic version which you have a DAO that makes yes-no decision. So anyone can throw on this DAO proposals.

I propose to such and such, you propose to such and such, and the DAO, the collective mind just saying yes, yes, no, no, yes, no, yes. So anyone can open a proposal. Now then there is a reputation system that weigh the voting power of agents. Now when a proposal is being open, is it open into a queue, so just a list of proposals. Now, by default, if a proposal is on the list, on the queue,

needs, if you want to execute that proposal, you need to have absolute majority of reputation holders supporting it. So actually 50% of the entire reputation of the DAO needs to say yes in order to execute the proposal. This is completely resilient, very coherent, and unmanipulable. The problem is, of course, is that it's not

scalable. So now the next step is that you would like to allow, you would like to allow to boost, to accelerate the process of decision making under some conditions. So what I mean by that is that you would allow, you would like to allow decisions to be open for finite time voting. So let's say that I take, I want to boost the decision, which means that I open that decision for one week. And then whoever vote on that decision in that one, within that one week, makes a decision. So if the majority of those voters says yes, it's being executed, majority says, no, it's not.

It's rejected. Now that's, of course, very scalable. You can process any number of decisions you want. But of course, then again, it's not resilient, because now I can attack the system by opening millions of boosted proposals, and then most of them will remain unnoticed because the collective tension will be completely diluted.

So how do you fix that? So now there is the second system comes in place. While those decisions are in queue, there is a second thing that you can do with that is to make predictions about the fate of those decisions. So you can come. I'm proposing a decision to budget my task of producing the next feature.

I need $20,000, and I'm proposing to allocate to me $20,000. Now you're coming and you're looking at that decision, and you have familiarity with that doubt, and you're basically making the prediction. You're saying, OK, I know. that this guy has a reputation, I know that this proposal makes sense, so I know, you know, I know the way that the people hear things, I know some of the reputation holders, I predict that this decision is going to pass, and I'm also willing to stake some tokens over that

at the station. So I'm willing to stake, you know, $1,000 that this decision will pass in the Dow if enough people look at it. Okay? So now, basically, when you do that, you are putting your capital at stake. So if eventually you'll be right, you will gain more capital, more tokens, and then if you will be wrong, you will lose your state. Now, the way that this prediction engine connects with the voting system is that the only condition,

the only way that a proposal can be boosted, is if enough predictors are predicting that it's going to pass. So that's the first instance. And then once, and without too much challenge, so without too much of others predicting that it's not going to pass. So the relative people that think that are going to pass

with respect to those who are not going to pass, is crossing some threshold. And then once it did cross some threshold, then the proposal is being boosted, and then people are voting on it. And still, people can always, can always predict against the status. So if the status of the decision that it seems to be passing,

you can bet against it by predicting it's not going to pass. And if it seems that it's not going to pass, you can bet against it by predicting that it is going to pass. And then those who predicted plays the prediction, they also have incentives to kind of hold the process and make sure that those who needs to vote in order to reflect the truth that they think they exist, to make sure to call them out and make

and remind them that they need to vote, because it seems that the reality right now is incorrect. And then, of course, the voters place the vote in the subjective, requiring the subjective majority. And if it's being approved, the thing is executed and otherwise, and not executed, and rejected otherwise. And now you can get into details in the game theory and show that actually this system can, and also,

I skipped a few parameters and so on. But you can see that this system is fully resilient. into manipulation and you can also see that you can process more and more decision in fact indefinitely providing some cost and the cost comes in in the fact that the DAO itself needs to be put a bounty that is basically distributed to successful predictors for successful proposals so you're basically essentially you're translating the tension between scalability and resists into the cost of the Dow management cost if you wish yeah this is great I you know we

did podcast before on Futurkey, I think we did multiple before with Ralph Merkel and Robin Hansen as well. And it's a really cool concept, but it seems sort of, you know, hard to make work and maybe not so realistic in the short to medium term. But this, to use prediction markets to kind of manage the, you know, priorities and, you know, managed the scale at which a dollar can process proposals and decisions, I think is really great and very elegant and seems quite quite simple. And so yeah, so that's that's great. It will be very interesting to see this in life with with an actual DAO. Cool. So let's let's move to to another topic, which is a little bit about the sort of economies and economics of this. One thing that is written about in the

white paper is that the DAO stack is based on this concept of circular token economies. Can you describe what that is? Sure. It's actually not a fancy concept. It's quite trivial and you all know it. We just added there for readers that are not familiar with option space very well.

But basically, it's just the regular adapt economy where you have a token economy where on one hand, you're printing and distributing tokens, to contribute as a value. For example, in the blockchain, it would be minors. But now since you have a general purpose decision-making engine, you can distribute those tokens to any contributor value. I mean, someone is writing, so right now in the Bitcoin,

or if someone is writing a code and place a pool request, successful pull request, he will not be compensated by coin-based Bitcoin, right? Additional Bitcoin. But you can actually make a doubt that, print new tokens for any sort of contribution of value, just need to agree about what is value and what is not. So on one hand,

tokens are being produced to contributors of value, and then on the other side of that loop, tokens need to be consumed, to consume the value that is being created. So, for example, if it's a blockchain and the value is created is the blockchain itself, and then if you want to use the blockchain, you need to spend the same tokens that were distributed to miners,

then you need to spend them in order to use the network effect that is created by the miners, which is the blockchain. And that same circular economy, I mean, it's critical. To have that circular economy is critical in order to build the network effect correctly. And I think that every DAP economy should have that circular economy in place. And if it doesn't, it has a broken model. So, yeah, now you may ask what is the circular economy, I guess, of DauStack.

Is it correct? Yeah, yeah. Let's briefly speak about that. So the gen token and kind of how that works in this circular economy. So I think that's really interesting. And to be honest, it took us a lot of time to crystallize that model. And I think it's quite hard to build a really robust model. So the idea is that identifying what is valuable right now.

So in our ecosystem, in the DAO ecosystem, the claim is that the hardest thing is coordination at scale. That is the thing. That is the thing, right? I mean, of course, you need contracts and all that, but it's not enough. And then I told you that there is a core problem to generate coordination scale.

The core problem is that there is a tension between scale and resilience, right? I'm arguing that it's an universal problem. It's not my problems. It's any project we'll try to try to try tackle that front will enter the same problem. And then I also told you that I think there is kind of universal solution to universal problem.

This universal solution is not a protocol. It's a concept. As much as I would say there is a scale problem for blockchain. And there is a universal solution that we call today off-chain computation. That's a universal solution. Well, it's not totally universal. There is also on-chain solution.

There is non-chain solution. But it's kind of like almost universal. And the same way I'm arguing that there is kind of like universal concept. of holographic consensus, which allows you to make decisions in small numbers, but then maintain resilience or make sure that those decisions are in line with majority

by crypt economically incentivizing, identifying the mismatch. So that's holographic consensus. And I also told you that this holographic consensus requires to have certain prediction game, right? The prediction game of the entire ecosystem is done with the gen token. So while you can have many different applications, on top of the stack, on top of ARC,

and you can have many, many different DAOs using those many different applications, all of the prediction games that is critical to facilitate, to enable large-scale decision-making processes, is being done with the Gen token. Kind of like somewhat analogous, but in a very different way, to the Ethereum being the gas for consensus over the chain. Here, Gen is the gas for large-scale decision-making,

or it's basically the token, the staking token, for the prediction game over the Dowstaffix system. So if you're going to have these different DAOs on, you know, let's say maybe Ethereum, or let's say you have different plasma chains or different, maybe on Cosmos, different Ether main chains that run some of these different DAO's, right? Because of scalability, you know,

they probably won't all run on the Ethereum main chain. How could you then still use the Gen token across all of these different, how would that work? that's not critical. Firstly, you can still have the prediction game on the main chain, but I don't think you need to because you can have many different sub-tokens on the sub-chains.

I mean, when you work on a sub-chain doesn't mean that you cannot use ether, right? You can still, you know, you can use tokens of the sub-chain that reflect the ether or reflect some other tokens. So it's not that the off-chain layers will not be interoperable in terms of token economics. So I don't think, I don't see any...

Or could you have, like, one chain where it's like a prediction market chain and all of the predictions and economics for all of the different donors that may live on different chains take place there? Yeah, sure. To be, you know, for it transparent, we, this current version is already on the main net. I mean, this current version of the stack is fully on-chain. So it's not scalable in terms of blockchain scalability. While I think you can already use it for some level of organization, maybe not millions of things. people but maybe thousands of people and maybe not you know daily decisions

but maybe weekly decisions and then already like next to next version we are planning to completely auctionize that platform so let's talk about roadmap and where the project currently sand so you mentioned earlier that you've done a crowd sale and that you'd raised at the time around 30 million dollars so Where are you currently at in terms of project development and when should we expect to see the DAO, the Dow Stack platform launch? Right. So we are launching the stack and Alchemy as the first application. I mean, literally these days, it's ready for launch.

We actually, we are just postponing a bit just to reorganize after the sale. We have a lot of things to wrap up. And then right away after that, we are launching the pilot, the first pilot. So, no, June it will be already running the pilot of the Genesis Dow. So the first use case will actually hold a real fund in Ether and let a large crowd to co-manage that fund around the Dowstack project. So that's like the pilot of pilot. Then we want to have like a few iterations on that pilot and also including pilots with some other teams, such as I will tell you about a few use cases,

in particular Gnosis, which are close partners as far as... Actually, Gnosis, we are running two experiments. One experiment is that Gnosis themselves they are launching their decentralized exchange dutch X and want to have that Dutch X completely managed by a DAO so that that will run on the DOSDAQ platform. And the second experiment is that Gnosis themselves,

they want to reward, incentivize developers to build on top of the Gnosis platform, application on top of the Ignosis platform using their prediction market and then reward them with Ignosis tokens. So that reward process will also use alchemy, or at least partially use Alchemy, and experiment with that. To deal the two experiments with Nosis and one experiment in-house with the Genesis Fund, firstly in Alpha and later in the, you know, kind of like public beta. And then we have a few other applications already in process of integration. So So the idea is that the first, if you want, Q3,

will be dedicated to piloting. Firstly, our own Genesis Dow, but then also a few other, maybe two, three other projects. And mostly piloting, stabilizing the system in terms of operation, gas costs, scale, protocol parameters, vector attacks, sorry, attack vectors, and so on, so, course. So stabilizing system.

And then Q4 actually launching real full products, again, including the Genesis fund, but with much more significant amount of funds, as well as Gnosis experiments, and then at least one other application that is already in process. So that's in terms of, I would say, six months timeline. In 20, I would say that we would like to have a few of experiments by the end of this year.

In 2019, our focus will be on one hand to a widespread the usage of the system. And by that, we're not going to develop many, many applications ourselves. We are putting a lot of efforts and focus on building the technology in a way which is very easily usable, integrable by others. So whether you need a holdout for yourself,

or maybe you have your system, but you just need you know, component, a decentralized component, then you can easily integrate with the stack. So, yeah, the idea is kind of to build horizontal platform and ecosystem for many different integrations. So while one front to proceed with in 2019 next year will be to widespread that adoption,

the second will be to iterate heavily on the technology right now the gas costs are still high everything is on-chain I mean we want to optimize that everything is own-chain we want to auctionize everything or not most things integrations with

you know with with other other other tools such as identity U-port kind of thing integration with the decentralized databases such as IPFS integration with external services such as Slack and Trello and so on so forth so

So maybe you can actually separate into three categories. One will be like market adoption, like massive adoption. We actually believe that this would be the killer. I mean, DOWs basically are potentially would be the killer apps on Ethereum. So one would be massive community adoption. Another would be a heavy iteration of technology. And third would be, I would say, UX. So kind of like integration with existing tools and so on, so forth.

Cool. Well, thanks so much, Martin. It was super interesting. I'm really excited about Dowstack, where it is and where it's going to go. I totally agree with you, that I think finding new ways of collaborating, of organizing, of building structures and organizational systems is one of the most exciting applications of blockchain. And I can't wait to see how this is going to turn out in real life. Thanks, Brian. I'm also really looking forward to see this, you know, taking shape in reality. Thanks guys for having me here. Yeah, absolutely. And of course, we're going to have links to a bunch of resources about Dada stacks. If people want to check that out, then they can check out the show notes.

And otherwise, thanks so much for a listener for once again tuning in. So we're putting out new episodes of Epicenter every week. You can scrap the show on iTunes, on SoundCloud, your favorite podcast applications, or you can also watch the videos on YouTube.com slash episode of Bitcoin. And if you want to support the show, you can leave us an iTunes review, and that helps new people find the show, and it helps us keep this going. So thanks so much, and we look forward to being back next week.