That she had.

Thanks for having me today.

Great. I'll do the little intro we like to do at the beginning of these just to ground everyone in in the series. And then we'll, get in get into, I think, get into hearing your story. Welcome everyone to Medigov seminar. Today's February 5 for the, recording. And I'm Nathan. I'm a fellow member of the Medigov community. I'm the finance operations lead. I'm stepping in for Val, who's our community lead, who's out today. But if this is your first time at the Medigov seminar, please feel free to unmute and introduce yourself or type a short intro in chat. And also you can do that if you're, you know, throw some stuff about yourself in the chat if you're not new as well. You're here every week just so we can welcome anyone who is. Seeing if any I flipped back to the screen to see if anyone was like, I wanna talk. But not seeing anyone, so I'll keep going. This is a weekly event at MediGov, a digital governance lab featuring discussions on online governance with researchers and practitioners. Today's seminar was proposed by our executive director, Liz, who just popped on and spoke a little about a bit about it. In our MediGov seminar Slack channel, we encourage community members to propose and lead future seminars. And I'll be, once I'm done talking, putting a little bit more information on how to do that in the chat. Today's presenter is Angela Kriesenweiss. Hopefully, I didn't butcher your pronunciation too much. The wait. Where am I? I have a script I'm reading from. But yeah. Oh, yeah. Focusing on all of our experiences with learning communities and token engineering and all these other interesting things. I don't know exactly what it's gonna be personally, but I'm excited to hear. The seminar will include around I mean, we're flexible on time, but twenty minute ish, thirty minute ish presentation followed by a moderated discussion, which I'll hold the space for. We do use a stack for discussions. So feel free to just kinda type stack in the chat if you're interested, or we can also use the raised hand feature on Zoom when that time comes. And please throughout the, throughout the presentation and throughout the discussion, feel free to put questions, comments in the chat, and I'll make sure to be keep an eye out and raise them to the speaker. And so, without further ado, I'd like to hand the space to you, Angela. Thank you so much for being here.

Thank you, Nathan, for this great introduction. Thanks for having me today. Thank you, Meta Gov community for your efforts. I really like the seminars and and the community, and I'm happy to share my experience and my journey. I'm the founder of Token Engineering Academy. We started a learning community back in 2020. I'm, in the crypto space in 2016, have a background in early stage startups, product investments, early product market fit, and then met first crypto people in 2016 and realized, oh, wait. This incentive thing, tokens, this is exciting. And it feels like we can create totally new systems and rewards to contribute in a system. And this what got me hooked to talking engineering, which was back then just a first mention of, well, this should be a new engineering field in its own right, actually. And this is where it started. Yeah. Let me share this journey and how we develop this learning community. Can I share my screen, Nathan?

Well, we would like you to be able to. Let's make sure you

have it. Okay. I can. Yeah. Just thought sorry. Oops. Let me get my slide. One minute. Okay. You should be able to see my screen. Wex?

Yes. Yes. I see it.

Alright. Yeah. So my talk will be on massive decentralized learning communities, and I'll talk about token engineering academy, which existed with an education program and as a education platform from July 2020 to December 2024. When I got in touch with Liz, this was in November, I think, and this was right at the time when we decided to close the learning platform. And by then, we had more than 5,000 students enrolled in our courses. We had run a peer to peer learning program with more than 40 peer to peer study groups in token engineering, running sessions in 14 languages, onboarded around 20 k community members to token engineering, and we raised around 1,000,000, in grants to make education a public good from partners like Optimism, Ethereum Foundation, Gnosis, ENS, protocols like Ocean, DeFi, Carbon Balancer, and VCs like Outlier Ventures and one k x. So in fact, this was quite successful. Nevertheless, we decided to close TE Academy, and the main reason for us to close it was funding for public goods shifted, made it significantly harder to sustain educational initiatives, and we were always committed to provide our education as public goods. And demand for token engineers didn't evolve as expected. So while we were focused on mechanism design, complex systems engineering, web three business models, Most industry requests over the past years, people who are looking for token engineers were focused on token sales, token launches, rather than deeper systems engineering. So as a founder of the academy, I was, of course, you can imagine, very hesitant to take the step saying, okay. Let's close it. Let's close it down. However, surprisingly, closing was a positive experience, and I think that's the first learning I'd like to share. Closing a community can be good. Usually, communities fade away in silence. Like, they get less active. That can leave members defending something that no longer deserves them. So feeling like, oh, I still have to support it even though I don't even see the value for myself anymore. And when we chose to close the academy openly, of course, I was also afraid of what that would mean. And it turned out to be really valuable because making it official helped us to step back and be honest about where we are, celebrate what we built, and gain a fresh perspective on what could come next. And that's that's my recommendation. Communities have a starting point, and that's awesome. Consider the value in having an endpoint if a journey or a certain iteration or a certain experiment comes to an end. And I think, yeah, it can be valuable for everyone, for the community members, for the initiative, the vision. And let's now dive in. So where we started as a learning community. So you might have heard of token economies, token based crypto economic systems, new forms of economic systems. They enable programmable rules and institutional frameworks to facilitate collaboration, coordination without relying on intermediaries, traditional organizations. That's what we are exploring in DAO systems, in token based governance. And these systems can incentivize individual actions towards a collective goal. And while in parallel, we have unprecedented real time data that we can measure and monitor. And this makes token economies so unique and so exciting. Here's a diagram or a chart from the paper foundations of cryptoeconomic systems published by Sherman Pfaffengeier and Michael Sargen in 2020. It also had a huge impact on the vision of token engineering. They define cryptoeconomic system as combining knowledge and also methods from computer science, cryptography, economics, game theory. We can apply industrial and systems engineering, operations research, AI optimization control theory, and we have the human layer with psychology, decision science, with political science, governance, and philosophy, law, and ethics. So it's quite multidisciplinary. And we knew that you can't study this nowhere at any university. And we to make progress in the space, we have to establish a shared understanding and a shared language and help people to make progress in this space and to share what all the various distance that I mentioned here can add to token engineering. And this is some first definitions of token engineering. So this is this new discipline combining these traditional fields, and we consider it as token engineering the theory, practice, and tools to analyze, design, and verify tokenized ecosystem. And the second element, this is how we envision token engineering, building out systems that rather than try to optimize humans, try to provide the maximum degree of freedom while preventing dangerous conditions. And here, you you'll find elements of other engineering disciplines. Like, we combine theory, practice, and tools, and we verify systems. This is the engineering, view on we are building public infrastructure. We have to ensure safety and fairness for everyone. And the second, engineering ethics. Try to provide the maximum degree of freedom while preventing dangerous conditions. And these were the starting points for token engineering in back in 2018. Some of what what happened in only in these two years, '28 and '19, The first mention of the engineering field, token engineering, first community meetup in Berlin in March, then some first papers published, the Cryptoeconomics Research Lab founded at the Vienna University of Economics, a first global gathering, and a second one in Berlin in October. And by the 2018, we had already 14 local token engineering meetup groups in 11 countries. People coming together, discussing white papers, discussing approaches, and, basically, a network of first initiatives, in token engineering. Then in 2019, common stack, community around how can we build new economies. In July, token economy, the book published in August another conference in token engineering. Catcat, the Python package was open source that supports complex system simulation, token system simulations, a first token engineering hack hackathon together with Outlier Ventures. The MIT launched a cryptoeconomic system summit in in November, and we started experimenting with game based cocreation of token based systems and incentive design. So this was only 2018 and '19. And we realized even though we have a lot of fun experiments and and a lot of things are going on in parallel, what we don't have is education. So we have to build this common ground, and this was, TE Academy. With this mission, we are developing a new engineering discipline, educating a new generation of engineers, and redefining structures and value flows for education and research. We our first educational initiatives were cohort based program. And, in fact, we continued running it until, July 2024, mostly in collaboration of, large protocols of projects willing to support us. For example, ecosystem value flows, the early stage of of a token engineering process, or we ran with Block Science, Gitcoin, and CADCAD a research group on Gitcoin grants and modeling where we explored quadratic funding and vulnerabilities and certain system properties and quadratic funding systems. The DAO rewards assemblage, this was a conference focusing with the, I think, eight hours online program with near endnosis and TEC supporting us, discussing how can we build reward systems, how can we align incentives in Daoist, computational social choice, modeling and simulation, ecosystem economic systems with machine learning and AI, hot topic at the moment, and DeFi's concentrated liquidity from scratch looking from, okay, algorithm design. How can we build autonomous AMMs, so automated market making in the crypto space. So a lot of different lenses and programs to learn token engineering and to learn from others, to learn from practitioners in the field. Because, at this point in time, 2018, there wasn't anybody there there weren't any trained token engineers. Right? Okay. And to get to the stage where we can say, okay. What what about this shared understanding? Let's make sure that we have at least a minimum understanding of the token engineering process. We then, in 2022, launched curriculum, a bachelor level curriculum. The main benefit, this is something that helps learners to understand where to start and what the learning journey should be. So it's not, you know, learning here and there and pick up knowledge here and there, but how to how to combine it to feel you are making progress towards a certain learning achievement. And also for the token engineering space to define this token engineering process to gain a shared understanding of the methods to be applied and also to find for anybody, be it course authors or be it practitioners or be it students to find certain focus areas because, as I said, token engineering is cross disciplinary. So how to connect your prior knowledge with the token engineering, the next level for your career? Okay. Key fundamentals, five modules. Module one, introduction to token engineering, really no prior knowledge required, five articles that shape the discipline, learning from the authors, the why and what, and a first overview, and what token engineering is. Module two, then we start the token engineering process with how to explore requirements in a token system, and forming this problem entity that will guide the design and modeling of the token system later. Module three, the design phase is then starting to design algorithms, the mathematical modeling. So students develop the mathematical models for

systems introduced in the previous module. We use the example of Uniswap. We won AMM, so a very simple algorithm, but with many, details to be explored. And we walk students through the token engineering process and provide context for how a system might evolve in response to real world events that might, edge cases, that might, be unexpected, and that we can explore via simulations. And module four is in programming a digital twin running simulations, how to code a model that replicates the intended system, how to validate this model, and then how to test the system design. And finally, module five, token based governance. So the landscape of token based governance, key governance concepts, analyze, explore, and initiate web three governance systems and processes. And by the way, the course author of module five is Jessica Sartler. You might know her. And Michael Sargam and Block Science provided a lot of the most valuable foundational work we are building on on TEA fundamentals. Okay. Now the next important component for this learning community was building a record of achievements. So here you see students, who acquired their first NFTs as a proof of learning achievements, of exams passed. And in our NFT system, we have many more NFTs that represent knowledge, expertise, contributions to the community. This is our NFTs, our ERC $11.55 tokens on OP Mainnet. This is a screenshot from the OpenSea collection. And we have in total 40 types of NFTs that represent certain types of achievements and contributions with 1,788 NFTs minted in total and fifth 553 individual NFT holders or better n f wallets holding TE Academy NFTs. Now we designed the system to be, sybil resistant and, with web free user agency in mind. So the NFTs are nonfungible and nontransferable, meaning an NFT or an achievement in the community should not be tradable, should not be borrowed away, and the wallets are also tied to an ID. And this makes the system highly SIBL resistant since once we start building applications on top, we can make sure that, a wallet is unique and that, NFTs belong to a certain wallet. And the second one, users in full control, refers to web free user agency. So all, users and students and community members claim ownership of NFTs so we don't air drop, and they can also burn NFTs. Thus, they can fully manage and are in control of their reputation. It's also not a black box for we assign to these NFTs, and this is maintaining our vision of you are in control of your reputation, you are in control of the proofs you're holding, and of how you would like to make use of it in our ecosystem. Okay. Now the system of NFTs allows us to track progress and observe the evolution of our discipline. This is the first benefit of this system. We can observe how the for example, how on an individual level, who are the most and most important and most active contributors, who are the most active learners. And on a community level, we can track how the community is making progress, what are the levels of expertise we can find in our system, and how to, further develop them. And this makes the system very important for designing the whole community and also designing incentives around contributions. So I mentioned the TE fundamentals modules. And here, let's take a look at, first analysis of the total number of exams passed across all these all five modules, from q four twenty twenty two until q three twenty twenty four. And so around two years. So we have a continuous growth across all modules over the two years. And, again, in total, we have 1,788 NFTs minted. Now if we break it down and look at the distribution of NFTs minted by module, we see that module one is the most popular. So, obviously, no prior knowledge required, the least learning time required. Interestingly, however, the number of t e four remember, this is the building simulations in Python module. And module five, token based governance is almost equal. So this is the first indicator that we have, let's say, different personas in our ecosystem focusing on on different topics and areas of talking engineering. Now let's take a closer look at the exams passed by module and by quarter. So we expected a stable cohort of students steadily advancing from module one to module five, which would result in a decrease in a in module one exams over time. And instead, the data shows that the share of module one past exams remains high over time, and a relatively consistent share of students completed module two to five in parallel. So we can draw the conclusion that, TD Fundamentals, a, has managed to attract a continuous inflow of new students starting with module one, and, also, that we have a diverse range of learners, and students are engaging with the content in a way that aligns with their interests, goals, and prior knowledge. And to me, this is or proves our hypothesis that this modular learning content is quite valuable even though we didn't know how students would approach it. Here's another interesting analysis, examining the linear progression from module one to module five. So if we look at the lines, I look at the first three lines that show t fundamentals module one to three, so I don't know if you can see my mouse, we can see that only a fraction of students here successfully acquires NFTs for subsequent modules. So, for example, sixty six percent of all TE fundamental two holders, NFT holders, has all have also passed module three and so on. While if we look at the other direction, ninety percent and the vast majority asked the prior module. So, like, if you, again, look at module two, ninety three percent passed module one. And if you look at module three, 95% passed, module two. Now this is different for the last two modules. For module five graduates here, we see that only eighty two percent point five percent of module five holders also earned a module four NFT. And vice versa for module four, it seems that they were quite motivated to complete the full course maybe, or for some reason, this combination of four and five makes sense. Now let's review again, revisit the content of the final three modules. Module three translates system requirements into mathematical modules models. Module four, verify mechanism designed through a Python digital twin. And module five, token based governance principles. It seems that some students bypass or fail to pass module three and four in favor of governance topics, module five. And module four graduates do proceed to module five, probably motivated by the proximity to earning full t fundamentals graduate status. And we saw this in the community, also in the behavior during cohort based programs. This might be driven by personal preferences, and it appears that we have two distinct groups, either skilled programmers, math heavy people, and token engineers primarily interested in token based governance. And I'd say, I would we always try to encourage people to do both because without understanding the dynamics and and the implications of an algorithm, you can't really optimize them and and really think about how to, for example, design a good governance model. So we encourage people strongly to study both. Nevertheless, in in reality, we saw it many times. It's then most promising to foster cross disciplinary collaboration. It makes it even more important to develop a shared understanding of the challenges we need to solve together and how to approach these challenges in multidisciplinarity. Okay. Building a crypto meritocracy. Let's take the next step. So once we have this NFT system in place, we can start assigning rights or rewards to these achievements, to these proofs of achievements, the NFTs. And we did this in the voting for the winner of the first TE Academy fellowship grant, the fellowship prize. So we decided we won to decide who's winning this first fellowship prize. This should be decided by the community. And here are four examples of the NFTs, just four of four t. We have t fundamentals module one, a student, half exams, NFT. Here's an NFT for the course authors of t fundamentals, for speakers at our token engineering bar camp in Paris at ECC twenty twenty three, or for the fellowship prize winner 2024. And these are just four examples. What I'd like to show is that we can identify different types of NFTs for students, for course authors, for speakers. And we can identify types of achievements, like learning achievements, successful completion of a learning program, establishing foundational knowledge, like research and curriculum development, or sharing knowledge, like content creation, providing lectures, providing talks, or community building, organizing peer to peer study groups, events, and supporting these events and supporting the, community and sharing of knowledge. And these types of achievements represent also different levels of expertise. We can identify the pioneers, so mapping the discipline with fundamental research. We can identify experts, the practitioners in the fields, court author authors, who established curriculums and building on their practical experience in token engineers. The graduates who managed to successfully complete all five modules or students who just embarked on their token engineering journey. And today, the distribution of the levels of expertise looks like this. And I guess this is no surprise. The largest group are students. Then we have graduates, and only a very tiny portion of the NFTs can be associated with expert knowledge. And so this is to be expected. However, in a voting for the winner of the first TE Academy fellowship prize, we probably should not apply one token, one vote. Because then, in the current state of the ecosystem, it would give students most voting power and experts least voting power. And looking at we we ask what is the most valuable breakthrough in token engineering, who should receive the fellowship grant in order to be able to continue token engineering research. This is a decision that requires expertise. Right? Okay. So we developed a waiting algorithm that we can use on top of this NFT system to solve this problem. And it's a mechanism for our community and, basically, every community where knowledge, expertise, and achievements count. And you can use this algorithm to distribute rewards, to assign rights, or to assign voting power, decision making power. And the key property of the waiting mechanism is that the total weight of all NFTs in a certain category, so the three categories, experts, graduates, and students, in our case, in other communities, the categories might be different. This total weight of all NFTs in a certain category should be equal. This is the key system property. So that in in a voting, for example, in our case, no group should be able to outvote the others based on the number of NFTs minted in this category. And from there, we can start aligning incentives. And we can ask what the core goals of members and different stakeholders are, and if these goals might be at odds which with each other and how to best align incentives to solve it. And the goals for community members, or the incentive might be, okay, you reward individual achievements. For the ecosystem, it's striving for innovation, insights, and progress. And for TE Academy to establish reputation and gain legitimacy. Okay. How can we align these goals with a certain mechanism design? And we define four design goals. So number one, there must be an incentive to learn and make progress individually. Individuals should benefit from their achievements. The scaled NFT weights or the the outcome of, the waiting mechanism must always be greater than zero, never negative. So it should never hurt you if you learn or if you contribute or if you build token engineering innovations and, work on research. That's pretty obvious, but it can have downsides. Let's take a look at the second design goal. There must be an incentive to support others in making progress. And this makes perfect sense because education is not a zero sum game. Right? So we all benefit from acquiring knowledge in the system. And supporting others in acquiring NFTs should create a network wide value and, should be rewarded so that members who contribute to collective learning are rewarded, The second design goal. The third one, there must be an incentive to maintain high quality standards. So for token engineering to thrive, the ecosystem must uphold rigorous quality standard. We want to establish the reputation of the contributors and, the of TE Academy as an organization. So members, we want to reward members from setting up hard requirements for acquiring NFTs so that the achievements remain meaningful, and the mechanism must balance quality enforcement with with collaborative support. And the final one, there must be an incentive to take on hard challenges. Scars NFTs should hold the highest value in a knowledge driven ecosystem representing novel achievements, difficult milestones to encourage ambition. And we can imagine NFTs in limited supply should yield a higher weight gain, motivating members to take on the most challenging accomplishment. And if you look at these four goals, then we see that design goals two and three are balancing each other. The most the more NFTs that get minted, the better it is for the ecosystem. So learning should be encouraged, not limited. Education is not a zero sum game. However, we can't let the standard slip. So if it's too easy to mint NFTs, their value and reputation will suffer. So we need to balance broad participation with maintaining high quality achievement. And if you look at design goal one and four, everyone benefits from minting NFTs, number one, design goal. This keeps people engaged in making progress. But at the same time, unique breakthroughs should be rewarded more than basic learning progress. So if everything is rewarded equally, there's no extra incentive to push the boundaries. And these are the four design goals. Now we found a very promising elegant approach to solve this, and we are currently working on publishing this dynamic network weight scaling algorithm expected to be available February, March. I'll be happy to come back and present again. And meanwhile, you can start or read more about this building a crypto meritocracy on Mirror. Happy to drop the link in the chat where we share the details of how we establish this NFT system. And last but not least, I should mention that you can meet us at FCC in July, where we are organizing a dedicated token engineering track. Speakers applications are open as well. Here's what we are looking for, and feel free to contact me and, of course, submit a speaker application for your latest and greatest work in governance and token engineering. And, yeah, definitely make sure to meet us at ETC in June, July, in summer, and come. Okay.

Amazing.

It for now, for the moment. I'm

Thank you so much.

To take questions.

Yeah. We have a number of questions here. I'm gonna I thought I'd start us people who have thoughts or questions, please feel free to either, you know, type let's let's let's use, the the Zoom feature. Go ahead and raise your hand in Zoom. But as you, do that, I am gonna highlight a couple questions from the chat that seemed kind of like more clarification questions before we go into that. Hopefully, we'll have a quicker answer. One one is actually from me, and then there's another from someone else. One is when you said in with the NFTs that the wallets when you're talking about civil attacks, while it's tied to an ID, I was just wondering what Mhmm. ID. Do you mean a government issued ID or something else?

No. It's tied to an email, basically.

An email?

So Okay. It's quite straightforward web two, ideas that help us. Mean main reason is we'd like to be able to contact community members, and it we have to have a unique identifier so that you can't, so that we can make sure, for example, that you can't reregister with the same wallet. Mhmm.

Gotcha. Thank you. And kind of like a sim maybe similar, sort of, like, a clarification for someone who's maybe not as familiar with, crypto terms. What is can you just briefly explain what an airdrop is on the same page here?

Airdrop is, you receive a token without knowing and without, yeah, accepting it. And this is this is, feels like yeah. Sure. Airdrops most people associate airdrops with airdrop farming, so you try to be an early recipient of tokens in a token launch event. However, when it comes to reputation, receiving a a reputation token airdrop to your wallet can be negative because you might be associated with things you wouldn't want to be associated with. And that's why we define that since it should be a reputation token, it's, the users who would take this active claiming step for receiving NFT.

Great. Another early question is that you shared this actually isn't a quote from you, a quote from someone else was in Saragum that you shared, in Saragum with someone else. There was a quote about optimizing something versus optimizing humans. And Yeah. Yeah. Yeah. Steve was wondering if you had like, what does optimizing humans mean?

Yeah.

And, Steve, feel free to jump on if you need to. But, yeah, do you have any commentary on that, Angela?

Steve, feel free to switch on your mic if you'd like to add a comment.

No. I mean, I don't have a comment. I just just wondered what that meant. What's optimal human means context?

Yeah. So, generally, there is this notion that within with building up incentives, you can manipulate people's behavior. Right? So that, set up an incentive and people will do stuff. And to a certain extent, this is true. Right? We can put up rewards and, let's say, steer an ecosystem in a certain direction. However, we know and and should value the freedom to decide and should also expect irrational behavior. So in economics, you have this notion of the rational actor maximizing utility, and utility equals most cases equals some, let's say, numerical value or monetary value. Still, in these systems, we also have socio economic systems. We have irrationality. And we should set up, a system always in a way that it provides maximum freedom. We can't expect that humans are predictable, and we have to expect adversarial behavior at any point

Oh, okay.

By humans or agents artificial agents, and that's why it's more about preventing dangerous conditions, setting up boundaries.

I'm just wondering why you phrase it like this. It seems to me what you're describing is you're optimizing humans, but then you're not expecting that to necessarily work. You're expecting that there's still gonna be errors, but you're still optimizing the humans. So you're really doing both, in my opinion.

Yeah. You could frame it one or the other way. I think I would say we are always optimizing systems, and you don't humans should have a maximum degree of freedom or actors. I mean, today, we are talking about artificial and human actors.

Centers plus constraints. I agree.

Yeah.

Thank you. We have Yanis who hopefully, I'm pronouncing your name correctly. You put a couple questions in here, and I was wondering if you wanna top on mic and and, ask them yourself, or I'm happy to do so if if not.

Exactly. So the dynamic network weight scaling is based on the idea that, number one, we have this equal weight of categories, and two, then it adapts dynamically to the ever changing system state and the supply of NFTs. In the total ecosystem and in the NFT categories and also in a personal wallet. And the the weight depends on the supply. We can add additional parameters where the community adds a score as well, but the core idea is scarcity makes weight grow. And the the more supply we have in the system, we assign the the weight volume or the or the weight decreases. So these these are the core parameters, the categories, the NFT supply, and, if needed, a community weight assigned or a certain score assigned to an NFT.

By the algorithm, ideally. And and this is why and this is core to the idea of token engineering. You try to find an algorithm that is robust under any circumstances that cannot break and at the same time provides us maximum degree of freedom. So the let's say, the core goal of token engineering work is to find an algorithm that meets these design goals, explore the edge cases, make sure that the system can't break, and then be able to let it run because we know it's robust enough to handle all scenarios that we can expect.

We have a comment that I think is in the flow of this from Anke. I don't know if, Anke, you wanted to hop on mic or if I should read your comment aloud.

Anchor, yeah. Spot on. So due to the supply, and I guess you remember this chart I've shown on the supply of the modules here, the later NFTs weighed more than oh, module five weighs more than module one. And and looking at this yeah. We have this funnel, and we have less students who manage to get to module four and five, and they build on prior knowledge most built on prior knowledge. It makes sense to assign more weight to the later NFTs.

Right. Yeah. Of course, any community could also assign values and weights in a deterministic way. What we wanted to achieve is that this waiting mechanism adapts to any state of the system no matter what NFTs are minted and how many we have in the system at any point in time.

Okay. So I have Michael's question that's in the chat. And then, Mel, I see your hand. So I'd like to at least meet those two before the top of the hour, but there may be space for up to one more. Michael, do you want to hop on mic or should I read your question for you? Please read away. By all means. The question from Michael is understood. Oops. I did something so I couldn't see it anymore. One second. Sorry. Understood, public funding dried up and the org must close, but what guidance would you offer a future organization or successor, question mark, aiming to provide learning services?

Ah, very good question. Okay. Advice number one, try to connect the learning outcome with next steps. So what is like, what could be next for someone who has learned this? This could be progressing your professional career. It could be participating in certain follow-up programs or be able to manage personal individual challenges in a better way. It's for us, it was very helpful to point people to projects who are looking for token engineers. And, on the other hand, vice versa. This was this is so critical that we had to realize without the perspective, for many to embark on a professional token engineering career. It's just doesn't really make sense to provide this education. Motivation decreases. It's not fun, and and it's also we are missing the push for innovation. So this is definitely super important. And then radically built on intrinsic motivation, curiosity. Let people meet. Let people discuss. Let them shine. This is, I think, the beauty of learning communities, this intrinsic motivation of people on board.

Great. Thank you. And then, Mel, I see your hand up. Thanks for being patiently thanks for patiently waiting. What's your question?

Thanks for having me. Really great presentation. I'm a I'm a product to the academy, but I I only did two and five. So it was really like, the fact that that was the focus of, you know, to jump around and and where we land. Right? So just on yeah. On behalf of a very grateful cohort generation, thank you. I really do think you inspired a lot of people. That being said, dynamic network wakes network weight scaling seems to get to the the target. Right? Like, we can take anything we have and then say, okay. Here's where we wanna get to, and that's really cool. What I missed in there was, like, you had the three segments of what we need to reward, but but God mode ain't free. Right? Like, I I think of that. Like, there has to be something at the center that says we need a way to reward the the meta allocation. Right? Like, we've decided where these three cohorts are equal, but who decided that and how. Right? I think it's kind of where my brain goes. And I guess with that and this kinda Steve's question made me think of this. A lot of what we do now is, like, we sprinkle token on top to get people to try and do that thing. Right? Like so, okay, we've carved out. Here's what we think the successful allocation looks like when we get to the end of a voting process or the end of a you know, this is the the target. Right? How do we sprinkle to to get there is kind of a lot of what I mean, that that seems like the grail right now of these automated incentive programs. And so I guess I can only say that as, again, a product of this this program. So Mhmm. Maybe this is like that a good final question. Like, where do you see it all going with this? And because I know you and I have had some conversations. This this is like, maybe is the conversation, and it's the, you know, the tokenomic conversation of our time. How do where do we go maybe in the next, like, three months and year for you?

I well, first of all, I think we have to make sure that we don't confuse systems where intrinsic motivation is key and others where you have to have extrinsic motivation to get things going. And then for the first, you can build on it. You can build on both, but maybe you have to take different approaches. For example, in TE Academy's case, getting the learning going didn't require any tokens or incentives. So the pure offering courses make people subscribe was not based on tokens. And for in over the first, let's say, one and a half years, we didn't even discuss incentives. We just focus on how can we track this? How can we make contributions, achievements trackable? And how can we have or create this pool of data and and this opportunity to gain insights? And then once we have the system in place, we we looked at application that we can build on top. And voting weight is one application, and there could be others. So I think in many cases today, it's the other way around. So we we think that we have to provide some incentives to steer a system in the right direction and then realize, we how can we even track this? How can we even track the value in it? How can we track the value contribution of individuals and and the like, this this category of value adds overall? And then you start struggling because, you basically can't build on data. You you don't have signals, and then you are very focused, of course, on one application case and it and your whole idea might break and you might need a different kind of proofs, in other cases. So I think this is the key challenge in in many reputation systems today. There is no system in place. You real you just realize, oh, we have to reward people to do stuff. Now how? And, yeah, that's, how I see it, and we we have to solve this.

Well, thank you everyone for your questions, for your follow ups, and, of course, thank you, Angela, for this generous presentation and discussion. I have a couple one tiny housekeeping thing, and then we'll, we'll give you some applause. First I wanted to say, let's continue the discussion in Slack. I'm gonna press enter now and include, some information on how to join if you're not there. If you have unanswered questions or Anke, I see your your, like, potential async question. I think the best thing to do is take that, put it in Slack, and we can continue discussing there. And also we do have a couple of slots open for the seminar on the nineteenth and on March 5. Next week, right now, we have scheduled Austin Roby. I'll give you behind the scenes that that may be postponed. We'll see. But, so there may be no seminar next week. It'll be either Austin Roby of subvert or no seminar, and, please just, we'll keep you posted in Slack. But, yeah, lots of opportunities to engage, and thank you so much, Angela, again. And as is the Medigap tradition, please, it's gonna who knows what it'll sound like, but please unmute and give Angela a round of applause. Return to take this Yeah. Yeah. While she has a press availability here in the next

couple of weeks. It was a pleasure.

Everyone's news in the background. Thank you so much, everyone, and I hope you have a great rest of your day.

Thank you. Bye.