In the early 1920s, the A.C. Nielsen Company was founded to measure sales performance in the consumer market. In the 1930s, Nielsen began tracking radio audiences, and then TV audiences in the 1950s. Nielsen ratings became the de facto standard for live TV viewership metrics. These ratings didn’t just measure audiences, they shaped the burgeoning media landscape. Ad prices, programming decisions, even the fate of shows—whether they lived, died, or were relegated to unfavorable time slots—all hinged on Nielsen’s data. It was a system that, for decades, dictated the rhythms of an entire industry.

While this model has evolved with the rise of digital platforms, the underlying dynamic remains unchanged: the attention economy (a phrase coined in the 1960s) has been a central force in influencing mass culture since long before it was popularized by social media. Its evolution reveals not only the power of quantifying attention, but also the inherent tensions between capturing it and converting it into something meaningful.

People began questioning the accuracy of the Nielsen system as soon as the system was born. Nielsen’s data collection methods are often considered opaque and its relatively small sample sizes, especially for local markets, further undermine confidence. The meta-level criticism of the ratings system is that quantifying viewership does not account for quality of engagement. Imagine the thousands of establishments around the country that play TV simply for white noise; Nielsen ratings fail to distinguish between this kind of passive viewing and active viewing.

Today’s digital advertising marketplaces enable the buying and selling of attention at larger scales and faster speeds than ever before. The incremental units of attention on the internet are more discrete and granular. We are now technically able to track every click, view, and cursor movement with programmatic ease. While the practice of trading attention has experienced a leap in sophistication, the fundamental question still persists: how accurate are the metrics?

Almost 50% of web traffic is believed to be bots, and more than 50% of those bots are considered to be malicious. Meta is currently battling a $7B class action lawsuit alleging that it falsified ad metrics to advertisers. Further developments in AI and personalized recommendation algorithms only signal that these issues will become more prevalent.

A spiritual successor to previous iterations of attention markets is emerging: tokens. Tokens are quickly beginning to reshape how we measure and value attention, offering a distinct alternative to legacy systems like Nielsen ratings and Google Analytics. At their best, tokens go directly to users and actually reward them for their data contributions, provide real-time data access and liquidity, and create more transparent systems for data collection and processing.

While legacy tools seek to methodically convert proxy metrics for attention into economic value, tokens make this relationship 1:1 by giving each engagement a programmatic price. Mechanisms like prediction markets take this a step further by introducing a speculative layer to attention economics. These markets don’t just measure what’s happening, they forecast what will happen. By allowing participants to bet on the success of content, campaigns, or trends, they aggregate dispersed knowledge into real-time, dynamic signals. This isn’t just a theoretical improvement; it’s a practical one.

Decentralized attention markets also offer certain protections and rewards to users that legacy systems don’t. Compared to Nielsen’s reliance on a handful of households to extrapolate national TV ratings, or Google Analytics’ vulnerability to bot traffic and click fraud, decentralized systems provide a transparent ledger for these metrics. Tokens transform users from passive data points into active stakeholders, giving them a direct financial interest in the platforms they engage with.

However, decentralized attention markets come with their own unique challenges. Many are technical and/or mechanism-related, but I want to focus on a very specific subset of issues related to the commodification of attention itself.

The commodification of attention has transformed it into a frictionless, programmable asset that can be bought, sold, and traded in real-time, often with little more than a line of code. This stands in stark contrast to the slow, deliberate rituals of building social capital, where attention is not just captured but nurtured, and converted into something more durable: trust, loyalty, or influence. In the past, earning social capital required a kind of alchemy—attention-seeking that, if successful, might eventually translate into financial or cultural capital. While speed is usually considered positive, a dangerous side effect creeps in.

In his book about the digital advertising industry Subprime Attention Crisis, Tim Hwang argues that the extreme commodification of attention has made these subsequent markets irrevocably detached from the human attention they seek to represent. This detachment is not just a technical glitch but a broader societal shift, one that Jean Baudrillard would recognize as a hallmark of our hyperreal age.

Jean Baudrillard is a French philosopher best known for his concept of simulacra and hyperreality—the idea that in our modern world, representations of reality (signs, symbols, images) have come to replace reality itself, creating a self-referential system where the distinction between the real and the simulated collapses into a loop. For Baudrillard, the metrics of attention—likes, clicks, views—are not just measures of engagement and social capital, but total abstractions, floating signifiers. Baudrillard would argue that the more we commodify attention, the more we detach it from any real social or cultural foundation; it has become a simulacrum, a copy without an original. It becomes a kind of spectacle, a performance that mimics the forms of social capital but lacks its substance. We mistake the map for the territory, the metric for the meaning. In this sense, the gap between attention and social capital is not just a practical challenge—it’s a philosophical one, a reflection of a world where the real has been replaced by the hyperreal, and value has been reduced to visibility.

Yet, for all the innovations that promise to analyze and optimize attention—analytics, tokens, prediction markets—the fundamental challenge remains: attention alone is fleeting. The real work lies in holding onto it, shaping it into something meaningful, and forging the relationships that turn visibility into value. In his book, Hwang draws a parallel between the subprime attention crisis and the housing crisis of 2008. Both, he argues, are rooted in the creation of speculative bubbles built on unstable foundations. In the housing crisis, financial instruments like mortgage-backed securities were abstracted and traded far beyond their actual value, until the underlying reality—the ability of borrowers to repay their loans—collapsed. Similarly, in the attention economy, the metrics we use to quantify attention are abstractions, hyperreal constructs that often bear little connection to genuine engagement or lasting value. In the case of tokens, we see prices soar only for early adopters to pick a time to pull the rug, leaving latecomers as exit liquidity. Just as the housing bubble burst, Hwang warns that the attention economy risks collapse when the gap between simulated value and real value becomes too wide to ignore. The danger, as both Hwang and Baudrillard might argue, is that we mistake the spectacle for the substance, the metric for the meaning—and when the bubble pops, we’re left with nothing but the hollow shell of what we thought was real.

Capturing attention is no small feat in a landscape where attention is increasingly fragmented, transactional, and ephemeral. But the very mechanisms that make attention easy to capture also make it difficult to sustain, leaving a widening gap between the spectacle of visibility and the depth of genuine connection. As we move into an era of decentralized attention markets, the challenge will be to design systems that not only capture attention, but also cultivate the trust and loyalty needed to transform fleeting engagement into lasting value. In a world where attention is commodified, the gap between grabbing it and converting it into something meaningful has never been more pronounced—or more consequential.

As a more nuanced point, however, I think many left FarCon with more questions than answers. Many familiar ideas and concepts were discussed throughout the weekend almost distressingly repetitively. A contentious question also lingered in the air: can a truly decentralized, positive-sum social network exist while still largely at the helm of a single team (with the best intentions)?

I wanted to share some of my own initial reflections here—from what questions I heard discussed the most often to what I’m interested to see emerge from the Farcaster community to my own general framework for thinking about consumer crypto.

Personally, I don’t think the infrastructure is quite ready for mainstream consumer adoption.

Despite all the conversations we’ve had about L2s and L3s, using these chains is still challenging. Whenever I use an L2 or L3, checking the status of a transaction on that respective chain is quite difficult—for example, LP’ing $ENJOY on Zora is still extremely confusing. Logging into Farcaster clients via “Sign-in with Farcaster” is still clunky and, frankly, a bit annoying. Many people at Farcon who were excited to buy goods onchain had to wait 10+ minutes to complete their purchase because they had to bridge funds to Base.

However, there is a danger and complacency to hiding behind the excuse of “we have to wait for the infrastructure before we can build applications.” A framework I developed while talking to folks at FarCon was thinking about the evolution of infrastructure and applications in two phases.

Phase 1: Get the infrastructure to a place where it’s easier for less technical, less crypto-native, and perhaps more product/vision-oriented folks (aka “Idea Guys”) to engage with tooling and iterate on application concepts that may onboard mainstream consumers. We’ve already made strides towards this, thanks to the work of the Farcaster team, Farcaster-native infrastructure teams like Neynar, general infrastructure teams like Stack* and Privy,* and other developers in the community. Leverage crypto-native users as testing grounds for those MVPs and continuously iterate over time without critical infrastructure obstacles hindering the process.

Phase 2: Build kickass applications and product experiences for consumers of all interests, crypto-nativity levels, and backgrounds.

I think we’re approaching the close of Phase 1. We have made impressive strides over the past several years on infrastructure, from embedded wallets with companies like Privy, to reducing costs with L2s/L3s, to improved bridging and chain abstraction with companies like Decent,* to seamless offramps like Ansible,* to the buildout of the Farcaster protocol itself, which is a huge feat of complex network engineering. There’s a lot left to build to further improve the user experience, but we’re finally at a place where that can be done in parallel with rapid application development and experimentation.

There was much discussion and debate during FarCon (both IRL and URL, but mostly URL) about the fate of clients when the Farcaster team may be incentivized to maintain Warpcast as the dominant client—that most clients will simply serve as feature fodder for Warpcast and promptly be swallowed up.

It makes sense to me that this was a central debate given the form factor of clients to-date—most are some sort of re-skinning or slicing/dicing of the global Warpcast feed. Most potential client concepts I heard, to me, stayed within this narrow scope. My sense is that this homogeneity lies in the core desire to appeal to and siphon away Farcaster’s valuable social graph from Warpcast, while I think there has been less attention on Farcaster’s other primitives: the Farcaster protocol and its data architecture.

Past conversations with Archetype research advisor Andrew Hong and teams attempting to build social networks have enlightened me to how the ability to leverage an out-of-the box p2p network and data structures actually designed for social graph modularity are gamechangers for application developers. I would love to see visions for clients that break out of supporting existing Warpcast users—offering entirely new experiences or functionality that may not make sense in the scope of a Twitter-like interface like Warpcast or appealing to users that may not be interested in crypto industry discourse that is Warpcast’s primary user base. Also as a high-level aside, my general belief is that consumer-facing interfaces that try to do everything actually do nothing—”There is no super app, I love you.”Channels are a clever effort towards this direction, as topic-specific Warpcast channels can better inform what a more niche, differentiated client may look like for a specific community and allow those clients to emerge more organically.

The above then alludes to the former point that infrastructure/onboarding mechanisms are not yet at a state where completely abstracting Farcaster/Warpcast away from the client experience makes sense, perhaps gridlocking us in a state of “meta-feature” clients.

Another question that naturally emerges then concerning the difficulty of all of this is—why leverage crypto infrastructure at all if you’re appealing to non-Warpcast users? In an age where information and media (both real and simulated) are abundant, social curation and coordination are essential. I believe that social products entirely coordinated by users, rather than monolithic algorithms, can be extremely powerful, and tokens are an powerful mechanism for facilitating that coordination.

A shorter-term question I left FarCon particularly curious about was the future of commerce and commerce-focused infrastructure/clients on Farcaster. While on-site, I was aware of multiple teams powering different commerce experiences throughout the conference. The category has generated builder excitement extremely quickly, and I’m hoping to follow developments there particularly closely over the next several months.

As a more general note, common questions I received at FarCon were what’s top-of-mind for me in consumer crypto nowadays and how I approach the space more broadly. Nowadays, I broadly break down consumer crypto with two different frameworks:

Ecosystem-first

Crypto ecosystems are famously tribal (i.e. Ethereum vs. Solana), and the same is true for more narrow consumer ecosystems. It’s been fascinating to watch the interactions between Zora, Base, and Farcaster as intertwined ecosystems. Zora and Base-based transactions often lean on Warpcast for distribution and discovery, while Farcaster then is bolstered by Zora and Base for products, content, and tokens for the community to engage with. I believe that the culture and practices that emerge from these ecosystems, both independently and in relation to each other, will be core to shaping the short-term future of consumer crypto as builders

Use case-first

In terms of use cases/types of products I’m thinking about, a few categories:

1. Bridging offchain/onchain user data

2. Brand loyalty

3. Onchain social

4. Onchain media/music

These categories are rather intersectional, so I’ll provide more sweeping thoughts below:

In my former post “Fast Forward: Building Consumer at Internet Speed,” I wrote about the broken user identity and experience across IRL and URL. For sake of brevity,I’ll simply rehash here:

“The user journey across online and offline is incredibly fragmented. As the boundary between the physical and digital planes continues to blur, the ability to form a truly legible, representative identity disintegrates. There is a massive opportunity to build experiences that seamlessly blend the physical and digital, particularly where social graphs can move freely between online and offline.

For individuals/communities: How can my favorite channels online better inform and tie to the people, groups, and places I spend time with offline and vice versa?

For brands: How can a brand better understand how a consumer who bought a product in-store spends their time online and engage them on those platforms?”

Now is a pivotal moment to be thinking about the intersection of crypto and media, though I also believe these products will stabilize over a longer-term time horizon than most shorter-term opportunities. Traditional media and music are having existential crises and crumbling around business structures, monetization, and the role of the consumer and the artist/critic. Alluding to a point I made earlier, I think tokens and crypto more broadly are powerful tools that can be leveraged to coordinate media networks that are becoming increasingly reliant upon user participation, user generated content, and perhaps even user ownership.

I purposefully meant to keep this reflection relatively raw before the temptation of over-intellectualization creeps in. Overall, I left FarCon both more excited and more concerned about its future. The foundation has undoubtedly been set by the stellar team and early ecosystem that have organically emerged. I think it will take a diverse community of developers, ideators, and power users to take the ecosystem to the next level and I am incredibly excited to be a part of its journey.

*I work at Archetype, and Archetype is an investor in these companies.

Disclaimer: This post reflects the current opinions of myself and is not made on behalf of Archetype or its affiliates and does not necessarily reflect the opinions of Archetype, its affiliates or individuals associated with Archetype. The opinions reflected herein are subject to change without being updated.

Written by Katie Chiou

IN CONVERSATION WITH is a series from Archetype where we interview artists in/at the edges of crypto across music, visual art, design, curation, and more.

André Allen Anjos, professionally known as RAC, is a Grammy award-winning musician, record producer, and DJ. RAC is most notably known for pushing the boundaries of remixing, expanding the historically dance-forward genre to include indie and rock. RAC has released 200+ remixes over the course of his career, which you can listen to on SoundCloud. Artists RAC has collaborated with include The Shins, the Yeah Yeah Yeahs, Tegan and Sara, Phoenix, Kings of Leon, Lana Del Rey, and many more. RAC has also released three of his own solo albums, STRANGERS(2014), EGO (2017), and BOY (2020). Anjos has also been incredibly active in the crypto ecosystem, releasing an onchain, tokenized cassette tape known as the $TAPE token in 2020, as well as the $RAC community token launched the same year. He is currently building a new company at the intersection of music and crypto called Oscillator.

Over a video call, I asked Anjos a series of questions ranging from his experience as a major label musician, remixing and technology, personal brand, the opportunity to improve the music industry by leveraging crypto, and more.

The following interview has been edited and condensed for length and clarity.

Katie Chiou: When you think about the music business, the first thing that comes to mind is streaming because that’s where people interface the most with artists. Can you tell us a bit about the dynamics of music streaming?

André Anjos: Let’s break it down from recorded music, which includes streaming. You can cut it a few different ways depending on what type of recorded music it is. There’s physical sales and the costs of creating those artifacts—vinyls, CDs, cassette tapes, whatever. There’s a real cost to producing and distributing those artifacts, and we’ve taken that model and applied it to something digital which virtually has no distribution cost.

Cover art for RAC's most recent solo album, BOY

Spotify dominates digital distribution. For every play of a song, you receive a fraction of a cent, which is tiny. To give some concrete numbers, about a million plays is worth probably about $4,000. That’s assuming you don’t have a label, a manager, or a distributor that’s taking a cut. Now, let’s say you’re signed to a major label. They’ll typically take about 80% and give 20% to artists. Without getting super in the weeds, the artist is usually the last one to get paid after everyone else gets paid. If you’re on an indie label, there’s typically a 50/50 split. You get less visibility, usually in exchange for a higher percentage of ownership.Then, there’s the full independent route where perhaps you own everything or you use a digital distributor like DistroKid, but you get no support so you have to promote it yourself.

KC: Streaming isn’t usually an artist’s biggest revenue stream, there’s other things like touring and partnerships. Can you break some of these down?

AA: In general, I would say the three broad main categories are recorded music, publishing, and touring, and every artist has a slightly different version of that. I separate publishing from recorded music because that’s essentially like writing. You can be a writer on something, but not own the recording, so I treat them differently.

I talked about streaming, but on the publishing side, it's kind of its own industry. It involves a lot of government-mandated royalties and is a complex, convoluted industry. They are very litigious, they love to sue people. So, writing and publishing can actually be one of the more profitable sides of music, but you have to play their game and you can’t really be independent. You have no sway.

To talk about touring for a bit, I’ve done almost every type of touring. It generally depends, but I will say that touring can be profitable once you get to a certain level, but for most people it’s actually a loss or breakeven at best. There are a ton of hidden costs that people don't realize until they're too deep in it. You can get caught in this cycle where you're constantly touring just to make ends meet, and it can really spiral. I would say, right now, the only real way to be profitable is to be a solo artist who DJs and is a somewhat well-known person and tours non-stop.

I also don’t see enough people talk about how touring is just fundamentally different after COVID. There used to be a balance to it before where there was enough ebb and flow—people take a break and write an album, come back. The issue that happened was that everybody tried to come back all at once after not touring for 2 or 3 years. With limited supply of venues, that inevitably pushed everybody's fees down and the cost of touring is suddenly 3x more expensive. You basically have a supply shock.

KC: Artists today are increasingly personal brand-driven and are expected to form more social relationships/communities with their fans. Frankly, it feels unfair to me. Maybe some people just aren’t built to do that. Curious if you feel the same/if you have thoughts around that?

AA: I think that’s definitely become more true over time. I had this realization years ago that I'm effectively competing with Netflix for attention. Everybody's competing for the same thing. And with attention comes money, so it's like we're all chasing the same thing. So naturally, it doesn't surprise me that artists suddenly have to play this other game that maybe they didn't sign up for or that maybe they were promised some version of being an artist that now looks very different.

rac.fm

I think change is inevitable. You kind of have to adapt. There are aspects of that I’m not personally comfortable with, but you have to make those choices for yourself and do it in your own way. If your choice is to not play that game, then maybe that's cool too. But I definitely still empathize with newer artists today. If you asked me what an artist just starting out right now should do to succeed, I have zero clue. I think everybody's kind of in the same boat. You try different things, see what works and what doesn’t work, and trends emerge from there.

I remember when I first started doing remixes, I wasn't really touring for the first year or two. I was perfectly happy doing studio work. I love being in the studio; that's what I like doing. Then suddenly, I started getting offers to play shows. It wasn't really my thing, but I thought, "I guess I can learn." It's funny because I learned how to DJ while in the club, even though I never used to go to clubs.

KC: Yeah, I read in an early interview of yours that clubs aren’t your scene.

AA: Yeah, not at all. But I get booked for shows all the time, and maybe that's a good thing because I bring my own energy to it. I remember in 2009, there were all these bedroom producers suddenly being thrown into clubs and DJing. Performing is such a different environment, it’s like learning a whole other art form. Even to this day, it's not the most comfortable thing to do for me, but everybody has different comfort levels, and you have to find your own path. I empathize with people that have to do a lot more social media now than before, but it feels like it’s just the world that we live in now. I kind of just accept it.

KC: You livestreamed on Twitch a lot during COVID after you had to cancel your tour. What was that like?

AA: I was pretty aware of the culture on Twitch, so I think that gave me a little bit of a leg up when I started streaming. I knew that I had to solve a few things like filling a lot of space and being loose and improvisational. There were experimental musical things I did that sometimes worked and sometimes didn’t, but I got to have fun with it. But the music was just there to fill the dead space. The real powerful thing about Twitch is talking to people. During COVID, everybody rushed to do Twitch streams and “live” performances that were actually pre-recorded, but they just glossed over the point entirely or it’d just kind of miss the mark.

RAC livestreaming in August, 2020

I'm really glad I did it, but I'm really glad I don't have to do it anymore because it was 4-hour sessions 3 times a week. It wasn't even that much money. Honestly, people were very generous with tipping but Twitch takes 50% unless you’re a huge streamer, and I just feel like that’s a lot.

But I enjoyed it. I think it was a way for me to interface with my fans and my audience in a more meaningful way and I still really appreciate it for that. Sometimes people will talk about that time very fondly, but I think everybody understands why I don't do it anymore.

KC: You’re an artist that’s always been at the forefront of technology. Part of your early legacy is transforming remixing. In the past few years, remixing has exploded even more because of things like TikTok and AI. As an artist, what’s your relationship to technology and these types of tools that make music creation easier?

AA: Obviously, I love technology. It'd be pretty hypocritical of me to criticize it because I feel like I owe a lot of my career to it. Recording technology, the rise of the internet—these things have enabled me to reach a wider audience than I ever could have as a local artist playing local gigs.

Back when I started, the remixing technology that existed was somewhat limited. Now, you can make a fully finished song in a day—it's crazy how things have changed. Especially with AI these days, I'm almost glad it wasn't around when I started. Picking a path like remixing and going deeper and doing different things with it than most people at the time, it gave me an edge in my niche.

Now, my moat around that was simply the fact that most people didn't have access to these files. Because, and I don't know if everybody knows this, every remix I've done has always been officially through the artist. I've never put out anything bootleg, even though that's a big part of remix culture. And I'm not saying that's a bad thing. I just mean that it was a source of income for me. I was paid by the artist to do it, which was, again, kind of a weird path to take. But now with some of these AI tools where you can extract a vocal from any track on YouTube, it’s hard to make a living from that type of work.

Technology, especially crypto, has served me well. It's become an interest of mine, a tool for expression. It doesn't feel forced—it's just something I'm genuinely into.

KC: Many of the original attempts to build at the intersection of music x crypto started with music NFTs. What are your thoughts on how music NFTs evolved and what are your thoughts on them today?

AA: Music NFTs were, I think, piggybacking off the narrative of scarcity that was happening in the fine art world at the time, and it didn't quite connect in the same way because people think of music differently.

People don't think of music as being a scarce asset. So why do I have to buy a music NFT? I don’t think anybody would deny that music is art, but people just think about it differently. They think about music as being everywhere, pervasive in the background. It's just not something that people think of as a scarce thing. So I think that narrative just didn't quite click for people, and there wasn't an analog to compare it to. With art NFTs, it's like a digital painting, there's only 10 prints and editions. But with music, there was never that same analog that resonated for people.

Aside from that, I really like the emergent behavior of uploading a song on the internet that is free of a platform and is universally compatible with everything else. That is exciting. That, I think, is a novel behavior that is so much more interesting than what we have currently. There are so many problems there to solve with that structure, but I think that is really cool. It’s just not yet compatible with the ways music works today with copyright, government-mandated royalties, performance royalties and all these other structures already in place. I still think there's merit to these ideas. We haven't quite figured them out yet, but I'm not ready to throw them away.

KC: What are your learnings and reflections from your own crypto projects like $TAPE and $RAC?

AA: They've all been unique in their own way.

$TAPE started as a concept I worked on with Jacob from Zora and Jack, my Co-founder. We basically came up with this question: If you let a market decide the price of music instead of a platform like Spotify, what does it become worth?

$TAPE is a physical cassette tape and the supply was completely arbitrary, but there's a hundred cassettes. Let's put them on a bonding curve and see how much they’re worth. People can trade $TAPE back and forth, and the trading created crazy price action. It made us realize that music is worth way more than a fraction of a cent. I don’t know the exact number, but it’s definitely higher. We learned that if you introduce some kind of artificial scarcity, you can use markets to kind of find a price. We also created a function where in order to get the actual physical cassette, you had to burn the token. Out of 100, only 31 were redeemed which is also interesting. Maybe the token is even more valuable than the actual thing.

With the $RAC token, it was basically like an airdrop to fans. It was a retroactive thing. Everybody that bought merch at a show or heard about tickets, bought an MP3 on Bandcamp in 2008, etc., got an email with some tokens. We didn't want to sell the token, it was meant to just be a community token. I thought it was a really interesting experiment. We ran into other issues such as people constantly in my DMs or in my replies asking why the price was moving.

ERC20s, for better or for worse, come with some baggage. No matter how often I try to tell people that the $RAC token is not meant to be financial, people still want to attribute a financial value to it. It was around this time that social and creator tokens were a big conversation, and the focus soon shifted to NFTs. Unlike ERC20s, NFTs don't carry the same liquidity provision baggage. I realize now that I may have been a little early with ERC20s. An NFT membership model may have been more sustainable for a smaller community. It's interesting now to observe the resurgence of memecoins and watch how narratives cycle.

KC: How are you taking those learnings to build Oscillator?

To back up a bit, when I first discovered Ethereum, I was excited about the programmatic nature, the ability to replace institutions with code, or middlemen with code. I think this idea is often overlooked in crypto discussions. While some focus on tokens and financialization, I think there's actually so much more interesting stuff you can do with blockchains and just programming business logic, if you want to think about it that way. That's the part that's more exciting to me than anything else. That’s where I'm coming from initially, and that's the future I want to see. I think this will be a better ecosystem to play in because open data keeps people honest. That's the vision I want to work towards, and it's what we're trying to do with Oscillator. In general, I think we just want to attract people that believe in that vision and that want to help. We want to recreate what a modern music industry could be onchain and that is built with the right foundation and built for artists. We want to cut out and trim a lot of fat and baggage that comes with the traditional music industry.

So if any of that resonates, reach out. We even launched our company with just a manifesto that said if you believe in these principles, come talk to us, like we want to work with you. We want to find the right people because there's no way we're doing this on our own. We want to put this vision out in the world and meme it into reality.

osc.wtf

Disclaimer:

This post is for general information purposes only. It does not constitute investment advice or a recommendation or solicitation to buy or sell any investment and should not be used in the evaluation of the merits of making any investment decision. It should not be relied upon for accounting, legal or tax advice or investment recommendations. You should consult your own advisers as to legal, business, tax, and other related matters concerning any investment or legal matters. Certain information contained in here has been obtained from third-party sources, including from portfolio companies of funds managed by Archetype. This post reflects the current opinions of the authors and is not made on behalf of Archetype or its affiliates and does not necessarily reflect the opinions of Archetype, its affiliates or individuals associated with Archetype. The opinions reflected herein are subject to change without being updated.

Written by Katie Chiou

I recently wrote a post on my personal blog about the state of the music industry, spanning the economics of streaming to social discovery to the role of media publications in elevating artists. The general thesis was that the music ecosystem is extremely complex and esoteric, and we’re overdue for new models and new platforms.

The original post was not framed through the lens of solution-finding or crypto, but my research made me more excited and confident about the opportunity for crypto to enable next-generation social platforms and creator tooling.

So far, explorations in onchain social and creator platforms emerge from the following guiding question: “Should I build for web2 users or should I build for crypto-native users?” Consequently, a tension between two approaches arises–familiar and arguably skeuomorphic platforms like Lens or Farcaster vs. more experimental, “crypto-native” platforms like Friend.tech or Song.tech that are often explicitly financially speculative.

Rather than argue that one approach is better than the other, I’d like to explore the potential of onchain social through a different first principles question: “What types of platforms uniquely leverage the power of being onchain?”

To properly understand the “power of being onchain,” we must return to what I’ll call “The Principles of Onchainness,” drawing heavily from Jacob Horne’s seminal piece “Onchain,” and examine how onchain mechanisms can unlock net-new platforms and features for users, builders, and creators.

The permissionless nature of blockchains means anyone can participate onchain without requiring approval or permission from any central authority or platform. The public and open anatomy of the network also means that everyone has access to all existing onchain data and, consequently, onchain users.

Composability closely follows being permissionless. Permissionless composability is a strong value proposition for builders who can now build apps and interfaces on top of existing data and protocols–tapping natively into social graphs, media, assets, etc. without necessarily having to bootstrap data or users from scratch or acquire permissions from any closed ecosystem or API economy. An important aside is the ability to do this while maintaining user privacy and integrity through cryptographic mechanisms such as ZK.

From Chris Dixon:

“When Twitter changed their API in 2011 or so, there was a big wave of startups — including a lot of my friends — who built Twitter startups. That was a thing in 2009 and 2010, with Tweety, TweetDeck, and all sorts of API services. [...] at some point [Twitter] decided, ‘Hey, we need to control. We are going to have client software, have an ad-based model, and change the API,’ and that whole industry died. Same thing happened with the Facebook platform.”

Composability breeds developer innovation, but what does “permissionless” or “composable” actually mean to the average user?

Users don’t join platforms out of principle, they join for some sort of utility (whether social, economic, emotional, etc.). Web2 consumer social platforms, for obvious reasons, make it nearly frictionless for users to join, making the immediate utility of a “permissionless” platform perhaps non-obvious. Composability is only valuable for users insofar as if there’s another platform or app users want to use, they don’t necessarily have to start building their social graphs or assets or even log history from zero.

From Eugene Wei when initially reviewing this post:

“The example I like to use is that every app that wants social features forces people to go through a friend discovery process and to build their network from scratch (Netflix and other social viewing experiences, for example). But scaled services like that probably already have enough nodes for a scaled graph, it's just the friction to create the graphs again that prevents us from experiencing what a social version of that service would be.”

At its weakest, onchain composability can eliminate the possibility for user data to be locked into a single platform. Threads is an example of unsuccessful composability, where the platform was able to attract signups at mind-blowing speed due to its native integration with Instagram, but quickly lost the majority of its daily active users because the Threads experience was not considered fun or differentiated.

At its strongest, symbiotic platform relationships can actually incentivize users to traverse platforms. When I think about a rich digital social ecosystem, the first example that always comes to mind is Neopets. Imagine a world in which every spot on the map–whether a game, store, quest, battle, etc.–was built permissionlessly by a different team, each not knowing the other, leveraging the same universal player data and identity. These types of open, interoperable world-building experiences are not possible in web2 where data access is constrained to a single team or permissioned access.

Ownership is probably the most straightforward value proposition of onchainness. In web3, whatever you own onchain, you own everywhere, forever.

However, knowing when ownership is a must-have versus a nice-to-have is crucial when designing a consumer experience–and the answer is more complicated than one might think. While the value of onchain ownership is usually discussed in the context of owning assets themselves, this neglects a far bigger picture.

For the sake of this post, we can think about ownership in two different, often interlocking, forms: owning assets and owning distribution.

Owning an asset is important when it has persistent, long-term value–money, art, “real-world” assets or representations of such. These assets have clear utility, aesthetic value, and/or durable markets. Owning assets onchain is usually most important in the context of security, ensuring that these high-value assets are secure, self-custodied, and can’t be siphoned away from the user.

Owning distribution is important when the assets themselves either aren’t objectively valuable or are only valuable within a specific context. To extend the earlier Instagram/Threads example, if Instagram suddenly shut down tomorrow, all my posts would disappear. How much does this matter? I may care about my posts emotionally, but I could very easily save the pictures in other places (like a hard drive). However, losing Instagram as a distribution channel for my pictures means Iosing 1) the social context in which my pictures became valuable, 2) the social graph/audience I crafted from the platform, and 3) history/proof that I was ever on the platform at all. This is a similar case for Twitter. If I were really that attached to my tweets, I could just screenshot them or write them down. I can even still download all my Twitter data (though this feature is permissioned/could be killed at any time). However, losing access to Twitter as a platform would mean losing access to my audience, my distribution, and the years of history and social capital I’ve accumulated from using the platform.

Owning distribution can be just as, if not more, valuable than owning an inherently valuable asset. Distribution → social capital → economic capital is often a powerful revenue flywheel for creators, with the monetization features either baked into the platform directly (YouTube) or indirectly (Instagram + brand partnerships).

As a holistic, real-life example, take this Reddit post from a DistroKid user. For level-setting, DistroKid is a creator platform that allows artists to upload their music to streaming platforms like Spotify and Apple Music and manage their streams earnings across those platforms.

In this example, it’s important to recognize that the music files themselves aren’t the issue, it’s the distribution and revenue tied to the uploads, facilitated by DistroKid. Without DistroKid, the artist has little clarity or control over their uploads, their metrics on streaming platforms, and the revenue they’ve accrued and are due. There are other platforms similar to DistroKid like TuneCore and CD Baby that artists can switch to, but interoperating between these platforms is a whole new challenge in itself. This isn’t to say that platforms like DistroKid are inherently bad, power structures simply exist in a web2 ecosystem that give platforms indiscriminate control.

In an onchain ecosystem, while the artist may still interact with a DistroKid-like interface, they’d have much more autonomy. They would be able to directly check and manage their assets onchain, the value accrued to those assets could flow programmatically through the protocol, and the artist can directly view and interact with their onchain audience. DistroKid wouldn’t be able to arbitrarily change the mechanics of the underlying protocol without being held publicly accountable–platforms are more incentivized to maintain credible neutrality.

The amount of autonomy an “onchain DistroKid” exactly enables still depends on many core design decisions, but at the very least the mechanics of the platform would be much more transparent to its users. If the interface becomes untrustworthy or a “bad actor,” the public is able to keep entities accountable and/or another interface could directly compete while leveraging the same data.

A few onchain-specific features to highlight that also strengthen ownership:

Protocols: Protocols enable distribution channels, social graphs, and transaction history to be permanent and programmable. Even if a platform shuts down, the underlying protocol keeps all the data, assets, and rules intact allowing other interfaces to easily emerge.

Markets: Onchainness makes it simple to permissionlessly create markets around assets, thereby making those assets more attractive to own. We’ve seen examples of consumer social platforms creating markets for their native assets in attempts to make them more durable and objectively valuable. For example, Friend.tech keys only have utility in the context of Friend.tech as a platform, but the markets around keys make them more valuable as singular assets.

To date, provenance has been one of the more legible and compelling value propositions of being onchain to artists and creators.

In a world of 1) digital nativity and transmission, 2) permissionless remixing, and 3) synthetically-generated content, tracking authorship and attribution becomes a significant challenge.

Josh Benaron, the founder of Bundlr, describes this problem space well:

“In the Web2 era, internet users gained the ability to easily ‘write’ to the internet. While this empowered users in new ways, the explosion of content came with downsides: murky attribution, lack of metadata to describe the content, unverifiable authorship, and weak assurances around who created content and when. AI has only magnified these downsides with its ability to facilitate counterfeit and derived content at a scale never before imagined. This trajectory sets us on a collision course where inaction will have grave consequences.”

A few real-world examples:

1. In an interview with the CEO of YouTube, creators Colin and Samir (1.4M subscribers) share that the most popular Colin and Samir videos on YouTube are short clips of their original videos posted by third parties. Colin and Samir aren’t able to capture any direct view count metrics or AdSense revenue from these videos, even though they created the original content. YouTube has a system called Content ID and a newer tool called Remix that were created to better attribute value to original creators, but the systems are not highly sensitive or yet used, respectively. Colin and Samir have resigned to the fact that the shorts (hopefully) give them free distribution.

2. TikTok has created an entirely new way to discover, distribute, and trial songs. Artists often have to scramble to funnel the free distribution into ways that actually capture monetary value. For example, in 2020 Aly and AJ released a new, explicit version of their 2007 song “​​Potential Breakup Song” after the original song went viral on TikTok. According to an article from Variety, “the TikTok trend associated with ‘Potential Breakup Song’ led to the creation of about two million videos, with the two most popular posts collecting over 10 million likes each.” The re-released version has amassed over 50M streams on Spotify, as compared to the original which has about 150M Spotify streams.

3. Ghostwriter is a music artist known for creating songs with AI-generated vocals from artists like Drake and the Weeknd, gaining 15M+ views on TikTok for their song “Heart on My Sleeve.” Neither Drake nor the Weeknd were directly compensated for the usage of their vocals, and neither have publicly commented on Ghostwriter’s music.

Derivatives have been valuable art forms since the beginning of art itself (remixing, sampling, interpolation, etc.), and attempting to terminate those artforms is a losing battle. However, as content becomes digitally-native and the technical barrier to creating and distributing digital-native content plummets to zero, the context collapse around remixed content becomes an existential issue. Authorship and authenticity are crucial to creators and artists who want to capture the full value of their work, whether as social capital or economic capital.

Verifiable provenance makes the transfer of content between people and platforms seamless.

“By being onchain, information gets a provable provenance that establishes its origins, its collaborators and supporters, and its context in a way that’s permanently and publicly accessible without requiring any institutional stamp of approval or maintenance. This system of independent verification and dissemination of knowledge—whether it be ideas, artwork, or personal information—is truly revolutionary.”

- Yancey Strickler, Co-Founder of Kickstarter, Co-Founder of Metalabel

As technical barriers fall and tools/platforms launch unique ways for users to leverage AI, the social inclination to interact with these applications increases. However, today’s younger users are also both more socially conscious and emotionally attached to artists, meaning they are simultaneously less willing to engage with platforms and tools perceived as extractive.

For derivative, remixed, or synthetically-generated content to truly reach its mass potential, value from these platforms must tangibly flow back to artists. Value doesn’t have to be explicitly financial, but cultural capital often indirectly leads to financial capital, though the relationship is quite blurred. Being able to at least map these flows more distinctly becomes even more of a priority.

Being able to track information between people is just as much a coordination issue as it is a source issue. Programmatic provenance increases the speed and granularity at which information and data can move.

In abstract terms, this means that 1) the upper limit of people that can be coordinated simultaneously disappears, 2) the number of layers added onto a piece of media or information (remixing) without losing context approaches infinity, and 3) the atomic unit of information or value that can be transferred between people or platforms approaches zero.

What does this actually unlock? I’ve shared this before when writing about the type of future I’m excited to watch crypto enable:

• Communities to self-organize and govern

• Communities to self-custody, coordinate, and deploy capital

• Users to own and selectively share/their identity/data

Strong coordination mechanisms create environments in which people are actually rewarded for collaboration, rather than zero-sum mechanisms. We see this clearly with the rise of freelance workers and experimentation around DAOs. From a 2021 post I originally wrote in collaboration with Station called “A New Genre of Work”:

“In his seminal 1937 essay, The Nature of the Firm, economist Ronald Coase explained why companies exist—to reduce the friction and transaction costs of contracting individual work on the free market. While perhaps a truth of the past, traditional corporations with bloated management and poor incentives for employees and users no longer effectively create value. Rather than focusing on practicing the craft at hand, tremendous energy is wasted optimizing for zero-sum games of equity vesting, salary negotiation, and organizational politics. [...] It’s clear that the most thorny problems facing humanity today—climate crisis, cybersecurity, income inequality to name a few—will not be solved by one corporation or one individual. These problems need to be addressed with the scale and efficiency of a corporation, without compromising on individual autonomy, creativity, and ownership. They require fluid and multidisciplinary collaboration that transcends the borders of institutions, from corporations to nation-states.”

With onchain mechanisms, networks can be orchestrated programmably, and value can stream atomically to contributors. Inherently decentralized fields like AI and media, that are rapidly approaching and inevitable, can be better approached from positions of encouragement, rather than fear.

Permissionless, Composable, Ownership, Autonomy, Provenance, Coordination

It’s worth examining how these lofty principles can actually be stitched together to unlock new, rich experiences.

The permissionless and composable principles of blockchains realistically benefit builders and developers more than they do end users. Think of this similarly to a perhaps more self-evident statement that users don’t care if the AI they’re interacting with was built with an open source or private model. However, the permissionless and composable nature of blockchain data encourages more rapid and open developer experimentation, which one must believe will ultimately result in richer end experiences for users.

As developer bases become more distributed and users traverse platforms more freely, value flows become much more complex and difficult to orchestrate. For developers, contributions become more granular and shared between more parties. For users, identity and inventory become increasingly fragmented. Distributed parties and information are one of the key trade offs of decentralization. In order to resolve these issues, data must adopt stronger provenance and coordination features–to both ensure verifiability and accountability of information and seamlessly orchestrate information and value flows between parties across these decentralized bases.

While the means by which permissionless, composability, provenance, and coordination affect users are more nuanced, the value of ownership and autonomy appear more clear.

In web3, whatever you own onchain, you own everywhere, forever.

However, as I outlined earlier, ownership and autonomy are contextually valuable.

Ownership of private and identifying information like PII and highly-secure assets are always important to users, but consumer social platforms are most powerful when they create new value substrates for users to own. I cannot stress enough that value does not have to be explicitly financial.

To steal a few excerpts from Eugene’s canon piece “Status as a Service (StaaS)”:

“Let's begin with two principles: People are status-seeking monkeys. People seek out the most efficient path to maximizing social capital”

“We have no such methods for measuring the values and movement of social capital, at least not with anywhere near the accuracy or precision. [...] Despite this, most of the social media networks we study generate much more social capital than actual financial capital [...] And, while we may not be able to quantify social capital, as highly attuned social creatures, we can feel it. Social capital is, in many ways, a leading indicator of financial capital, and so its nature bears greater scrutiny. Not only is it good investment or business practice, but analyzing social capital dynamics can help to explain all sorts of online behavior that would otherwise seem irrational. [...] What ties many of these explanations together is social capital theory, and how we analyze social networks should include a study of a social network's accumulation of social capital assets and the nature and structure of its status games. In other words, how do such companies capitalize, either consciously or not, on the fact that people are status-seeking monkeys, always trying to seek more of it in the most efficient way possible?”

My interpretation of these specific quotes is that humans are generally very good at finding ways to increase and leverage their own social capital. The opportunity for new consumer social platforms therein lies in either 1) creating assets that are newly valuable, 2) creating connections that are newly valuable, or 3) enabling new value chains for existing assets or connections.

Tying this more meta-point to crypto, crypto is uniquely good at 1) accelerating creation through permissionlessness and composability, 2) tracing connections and flows between people and platforms with strong provenance, and 3) enabling the creation of new markets.

What has hopefully become clear through this exploration, is that creating new, sustainable value mechanisms is much more complex and nuanced than assigning a speculative dollar value to an asset. This is not all to say that financial capital is not an important lever for social experiences. Financial speculation and gambling can be very fun and very lucrative. Wealth will likely continue to be *the* status marker for a very long time. Creators should be able to directly channel social capital into financial capital. Creating new, sustainable value mechanisms also requires reaching beyond theoretical principles like “permissionless” and “composable” as means to reach users.

History tells us that the most paradigm-shifting markers for value originate not from dollar value or grandstanding, but from new experiences demanded by concentrated movements of people (often underserved) with new interests and new tastes.

I’m most excited about a future that uniquely enables new means of creative expression and value distribution. This future is already rapidly approaching. Creation is easier, faster, and more distributed than ever before, thanks to the globalizing force of the internet and more emergent technologies like AI, and people’s identities, connections, tastes, and interests are also increasingly more complex and distributed.

Onchain mechanisms are uniquely positioned to unlock collaboration, power experimentation, and ultimately track and create value for builders, creators, and users–all while maintaining user sovereignty.

At the beginning of this post, I mentioned a post on my personal blog about the state of the music industry. At the end of that original post, I proposed a few new models for tools for artists and social platforms more broadly that I would love to see come to life:

“Platforms that spotlight a track’s social provenance, highlighting its often unsung songwriters and producers, and create rich attribution graphs and experiences around those social connections.

Platforms that spotlight a track’s data provenance, gamifying remixing and experimental AI creation while preserving attribution and data provenance.

Decentralized media and curatorial platforms, where media is sustainably co-created and co-distributed by the local scenes and communities that create niche scenes and sounds.

Digiphysical platforms and experiences that sit at the interplay of live and digital.”

I’m more confident than I ever have been that the rails of these next-generation platforms and many more will live onchain.

Thank you to Eugene Wei, Reggie James, Andy Weissman, Seyi Taylor, and Ruby Justice Thelot for thoughtful and critical review and feedback on drafts of this post.

Thank you to Jacob Horne, Yancey Strickler, and Josh Benaron whose pieces I referenced in this post.

Disclaimer:

This post is for general information purposes only. It does not constitute investment advice or a recommendation or solicitation to buy or sell any investment and should not be used in the evaluation of the merits of making any investment decision. It should not be relied upon for accounting, legal or tax advice or investment recommendations. You should consult your own advisers as to legal, business, tax, and other related matters concerning any investment or legal matters. Certain information contained in here has been obtained from third-party sources, including from portfolio companies of funds managed by Archetype. This post reflects the current opinions of the authors and is not made on behalf of Archetype or its affiliates and does not necessarily reflect the opinions of Archetype, its affiliates or individuals associated with Archetype. The opinions reflected herein are subject to change without being updated.

Written by Katie Chiou

Gaming has always operated at the absolute cutting edge of technology. The earliest video games (think Pong, Space Invaders, Doom, Quake) were deceptively simple, but pushed the limits of early computer graphics and network capabilities—eventually birthing companies like NVIDIA, which would go on to revolutionize not only the gaming industry, but technology entirely. Gaming continues to be a meaningful playground for frontier technologies today, from AI/ML to blockchains to VR/AR. However, to understand exactly where and how these technologies can fundamentally improve games requires a first principles understanding of games themselves. In this post, I’d like to deconstruct the elements of a game and explore opportunities to actually make them more immersive and ultimately, fun.

“‘What is a game?’ Marx said. ‘It's tomorrow, and tomorrow, and tomorrow. It's the possibility of infinite rebirth, infinite redemption. The idea that if you keep playing, you could win. No loss is permanent, because nothing is permanent, ever.’” - Tomorrow, and Tomorrow, and Tomorrow, Gabrielle Levin

Games are a unique art form because they engage one of the most dynamic aspects of humanity—agency. Consider other modes of media such as image or film. While the resulting form of those mediums is the final object, the object of a game is the action itself.

In his classic study of the art of play, Homo Ludens, Johan Huizinga coined the term “the magic circle” which refers to the theory that a game should draw clear distinction from reality. Games create spaces where players willingly subject themselves to new rules and constraints. In this way, games are fundamentally irrational, a suspension of reality. However, these “arbitrary” limitations enable players to experience new forms of agency, allowing them to pursue world conditions that suit their own goals and desires.

While the magic of a game is its abstraction, to understand what truly makes a game tick, you must inspect its wires. Successfully plucking a player out of reality and wholly submerging them in a new world is not a simple or easy feat. Let’s turn our attention to video games which we’ll focus on in this post. A video game is a complex, cybernetic software system in which the player interacts with a machine (console, PC, mobile device), which typically consists of some input device (keyboard, controller, screen) and some sort of UI (screen) which is loaded with the game’s software. Designing a video game then requires careful equilibrium between three principal actors:

1. Player(s)

2. Environment (the game itself)

3. Machine

The Player - Environment - Machine triad is a powerful schema we can use to investigate how to craft lively, conscious games (Part I), before exploring how onchain elements can help further imbue games with new life (Part II).

The relationship between game developer and game player is a delicate one. The game, a canvas of rules and boundaries, unfolds as a collaborative act, scripted by one and performed by the other.

We can categorize the player experience in two categories: player-to-game and player-to-player.

The player-to-game relationship chiefly concerns itself with how much autonomy is given to a player. After all, we stated earlier that the best part about games is their ability to explore agency. In exchange for willingly submitting themselves to a game’s landscape, the player must be given assurances that in this fictional world, their journey is unique and that their choices matter.

However, there is an interesting tension here. Granting unlimited agency to players actually diminishes the quality of gameplay. Fun emerges from the challenge to creatively problem-solve and push against a game’s boundaries, rules, and limitations. Therein lies the difficulty of giving players autonomy. The relationship between developer and player is a pact forged in code and design. The player seeks the sensation of agency, the belief that their actions have consequences. The developer, meanwhile, must shape these actions, guiding the player along the chosen path, yet artfully concealing the strings that bind.

Emergence is a game design principle closely aligned with autonomy, a balance between structure and agency. Emergence essentially refers to a structure where there are a few, simple rules, but the overall gameplay is designed such that unexpected patterns can still organically surface. Emergent gameplay gives players a sense of ownership and power over a game, allowing them to develop their own unique tools, strategies, and experiences.

The Legend of Zelda: Breath of the Wild is a popular open world game where players are given goals, but can explore and interact freely with the entire map and its objects in whatever combination, sequence, and pace they choose. There is never only a single way to achieve goals within the game. If you look up walkthroughs (guilty) for any quest, there will be a wide variety of methods and items players use to accomplish a task.

The Legend of Zelda: Breath of the Wild

Alternatively, emergence is often designated to player-to-player interactions in multiplayer games. Give players as much ability to self-organize and coordinate as possible, while arming them with the structure and tools to do so. Different permutations of people then use different tools to make different decisions resulting in different outcomes. EVE Online is a game famous for its emergent properties, designed around how players collaborate.

Aside from collaborative gameplay, emergent player-to-player interaction can be facilitated through virtual economies. A basic virtual economy can be rather simple, but as games get more multiplayer, interactive and complex, such as massively multiplayer online games (MMOs), economies must become more robust in order to function properly.

For example, the virtual economy must be able to adapt to the fluctuating number of players and the resulting inflation from constantly inflowing currency. Games then must create needs to spend currency (completing tasks, buying/trading assets) and the requisite opportunity costs (time/risk to craft/obtain assets or complete tasks). The game also then needs to create mechanisms to manage the supply and demand of resources and crafted assets (rarity, item upgrades/destruction) and their pricing (centralized (NPC) vs. dynamic (player-to-player)). These are just a few examples of potential considerations for virtual economies, but evidently, these economies can be just as, if not more lively, than real-world economies.

Players can also generate new user-generated content (UGC) as a means of emergence. This could include new maps, new assets/items, as well as new markets/economies for newly-introduced features, objects, and mods. A classic example of a game that thrives from UGC is Minecraft where players can spin up new mods/servers and design them with entirely distinct aesthetics, assets, and goals. At some point, the modding may even become the gameplay itself, rather than the original designated game objective.

UGC even includes creating entirely new games, a major driver of innovation in the video game industry. Take Counter-Strike, which is considered one of the best games of all time on Steam (according to user reviews) and one of the most played on the platform (Counter-Strike 2). Counter-Strike began in 1999 as a mod of Half-Life. Valve (creator of Half-Life) would then acquire the rights to the mod and release it as a standalone game in 2000, going on to include several games in the series since then. Dota 2, also currently one of the most played games on Steam, began as a mod for Warcraft III called Defense of the Ancients (DotA) in 2003. DotA would then go on to lay the foundation for the entire multiplayer online battle arena (MOBA) category. Valve acquired the rights to DotA (even though Warcraft was originally created by Blizzard) and released Dota 2 in 2013. Auto Chess then started as a community-built mod for Dota 2 called Dota Auto Chess, later becoming a standalone game and the original inspiration for many autobattler games that would soon follow—i.e., Dota Underlords from Valve.

Dota 2

Types of Players

Before putting principles like autonomy and emergence into practice, we must consider that there are different categories of players, each with unique goals, motivations, and preferences for gameplay. Jon Radoff designed a general framework for classifying players, drawing upon the classic work of Richard Bartle.

Game Player Motivations framework by Jon Radoff

In this simplified framework, Radoff uses two dominant axes for types of games: number of players and type of rewards. He then identifies the dominant mode of player motivation for each style of game.

Based on these player archetypes, game designers can better assess how different types of players may engage with different types of games and design experiences accordingly. For example, a player who values a more immersive, multiplayer experience may value autonomy and coordination tools more than a player in an achievement-oriented single-player game who may want explicit rewards and point systems. A game might appeal to only one of these player quadrants, while another might try to appeal to a variety of players.

The true essence of a game derives from the interplay of narrative and gameplay in its overall environment. Different genres of games may focus on these components with varying intensity, but they go hand-in-hand.

Adventure games, role-playing games (RPGs), and visual novels usually focus on narrative, the winding story that unfolds as a game narrates lore to the player. Meanwhile other games, like platformers and casual mobile games, tend to be more concerned with gameplay, giving players clear tasks and rules and the means to accomplish them. Different players with different preferences may value narrative and gameplay differently.

In both cases however, the ultimate goal of a game is immersion—successfully drawing the player into the experience:

Narrative immersion: The goal of narrative immersion is to make the player feel like a living entity in the game world; the transition between character and player becomes practically seamless. The keys to narrative immersion are rich storylines and characters with strong personalities or backgrounds. An example of a game with strong narrative immersion but perhaps limited gameplay is Persona 5 Royal, which is structured as a visual novel where the player is taken through a rich, manga-style storyline, but active participation is basically restricted to turn-based combat or limited choices.

Persona 5 Royal

Gameplay immersion: Gameplay immersion relies more on engaging tasks, clear rules, and smooth game mechanics. Bad UI and clunky tech are absolute killers of gameplay immersion, where the immersion goal is often to encourage “button-smashing.” Examples of game genres that usually prioritize gameplay include casual mobile games, certain types of combat games, or racing games.

Mario Kart 8: Deluxe

We make the distinction between narrative and gameplay immersion not to say that one is objectively better than the other, but to understand that each form may have different design priorities and tradeoffs. Whether through narrative or gameplay, achieving full game immersion is crucial because this is where players choose to buy into the rules of the game. The player enters willingly, suspending disbelief, embracing the new reality of the virtual world. But the developer must set the stage and provide the tools in order to compel the player.

Digital Physics and Map Design

The way a player fundamentally interacts with a virtual world is determined by its digital physics (a crypto-native term, but we’ll use it more broadly here) and map design.

Digital physics is similar to real-world physics insofar as it creates the baseline constraints for how objects appear, interact with each other (collide), and move through space and time. Sound digital physics are instrumental to keeping players engaged with the narrative, coordinating players, and maintaining a game’s mechanics and performance.

Timekeeping is an important aspect of designing a virtual world not only for sake of gameplay immersion, but also as a core mechanic for how games update. For sake of simplicity, you can generally think of games as turn-based or real-time games. In turn-based games that are basically “I go, then you go,” configuring time is straightforward; time progresses only when certain events and actions occur. However games that are based in realism usually simulate real-time. Effectively simulating continuous time and motion requires the game to update its internal logic/state and the player's console and display to render frames to the player at smooth speeds—known as ticking (tick rate) and framerate (frames-per-second), respectively. These mechanics, usually determined in a game engine, are essential game primitives that can be technically challenging to design across players with different hardware, software configurations, internet speeds, and geographical locations.

In regards to map design, an open world’s topography crucially informs its gameplay. For The Legend of Zelda: Breath of the Wild, the open world design was actually incredibly difficult to pull off. During development, the team had to completely redesign the terrain of the game world in order to nudge players towards different parts of the map without giving them marked paths.

Climate is also closely related to topography and can be used as a core mechanic of a game. A game’s climate can trigger certain characters, events, and challenges, or it can even dictate a player’s pace. In Zelda, weather is a very contentious topic that drives discussion and community among players. Many players appreciate how immersive and realistic the effect is, while others find it extremely inconvenient and unnecessary.

https://www.reddit.com/r/Breath_of_the_Wild/comments/8zbu78/im_sure_this_has_been_posted_before_but_its_still/

The machine is the primary conduit through which players can express physicality in a virtual world. Remember, we began this exploration by describing a video game as a cybernetic software system in which the player and machine play each step of the game together. Innovation at the machine-level inevitably bubbles up to its environment and players.

Machines, historically, informed much of game design. Consider the arcade game—often played in a public place where play is restricted and timebound. These games often are designed around the concept of finite lives whereas computer/console games require a single purchase and then can be played freely on one’s own device. These games are often measured by health score, rather than finite lives, allowing longer, more flexible gameplay including incremental power-ups, pauses, and saves. Similarly consider the advent of mobile games, where games are often designed around scrolls or fluid finger motions rather than clicks or button-smashing combinations.

As a counter-example to the importance of the machine-game relationship, mobile gaming and multi-platform/cross-platform support have emerged over the past few years as paradigm-shifting developments.

Crossplay will likely prove instrumental to the next decade of video game development at-large due to the pressure it places on gaming studios and publishers both from technical and distribution standpoints. Technically speaking, each platform from PlayStation to Nintendo consoles to mobile has different technical and graphics requirements that make adapting games to be multi-platform a nontrivial lift. From a distribution standpoint, platforms historically develop moats from the games/IP they offer. For example, most Nintendo games can only be played on Nintendo consoles, meaning Nintendo gains massive IP moats from series such as Mario, Zelda, etc.

While still nascent in development, the convergence of meta-trends like crossplay and mobile gaming drastically limit moats that gaming companies traditionally rely on such as tying IP to consoles, making the probability of a more open, player-driven future for gaming much higher.

When discussing the intersection of crypto and gaming, the framework often looks something like this:

• Web 2.5: games bring assets (i.e., skins) onchain with NFTs; use ERC20 tokens for in-game currency, and build onchain market infrastructure for assets and tokens; most, if not all, game state/logic is offchain

• Web3: all game state and logic is fully onchain

The reality is that different types of games with different structures and goals are probably better suited for different onchain elements (if any), and it may be better to structure the conversation around game-technology fit rather than rely on a purity spectrum. With the high-level framework for game elements we developed in Part I, we can explore ways that onchain components can improve and revolutionize games.

Maslow's Hierarchy of (Video Game) Needs

The absolute primitive components of a game are its engine and physics—the substrate for designing a virtual world. The more open this level is, the more malleable the levels above it become.

Games built with blockchains at the base layer enable truly open modding, rather than relying on companies to issue composable tooling that they can close at any time or underground hacking (jailbreaking, reverse-engineering) that cannot easily scale. With natively open modding, players can permissionlessly and directly contribute to virtual worlds they already love, rather than having to create separate, derivative environments from scratch—and they can continue to do so until the end of time, regardless of any permissions or whether or not the original client continues to exist. Similarly, bringing all game state and logic onchain opens the design space for permissionless new clients which can even be built cross-platform, a usually centralized and demanding task as discussed earlier.

We’ve already seen onchain modding manifest in games such as Dark Forest. Without core developer intervention, players have created new marketplaces, guilds, game modes, and an entire library of plugins, all of which are onchain.

Dark Forest

Compare this to earlier examples of modding we considered, where a general pattern appears: company provides game tooling (Warcraft World Editor, Half-Life SDK, Dota 2 Workshop, etc.) → community builds mod (Counter-Strike, DotA, Dota Auto Chess) → IP gets acquired by a big company and is released as a stand-alone, closed game. The overall effect of this dynamic is fragmentation and cold-start problem for newer games, versus having the ability to seamlessly extend an existing world.

There is a more existential question to be asked, however: Do players genuinely want more control and autonomy over their games? The nuanced answer here is that there will likely be players that prefer games that look more like curated theme parks and players that prefer games that look more like buildable cities. Neilson has an excellent meditation over the complex role of player autonomy in games here:

“Players are becoming designers, creating new rules for the game, automating new players, creating new autonomies—a process of positive feedback. [...] There are games in which players play at design while still remaining firmly inside the game, RollerCoaster Tycoon and Fortnite are somewhat like this. That is ok. However, when a player is fully able to change the rules of a game, they are no longer inside it. That is also ok. To truly make players into designers is to upend the game entirely.”

Perhaps the most material implication of open modding for core game developers is that they must pay careful, close attention to determining which constraints and details of a world must be formally and strictly defined (i.e., laws of time and physics, alchemy of materials, etc.) and which details may have softer boundaries and be open to change. The immutability of blockchains means that the original developer can still instantiate permanent rules that ensure the integrity of the virtual world; after the introduction of these rules, no party can alter them.

In some ways, these capabilities bring a game even closer to reality than further from it—allowing players and developers to build, interact, and coexist in a lively world that still remains stable and unyielding in its core fabric of reality. These ”Autonomous Worlds” may very well defy our perceptions of not only games, but of digital spaces entirely.

There are many complex challenges to bringing game physics—namely time, state, and collision—onchain. We covered some of the basics of timekeeping and the challenges it presents, but bytes and yonada detail in-depth considerations for onchain timekeeping in their post “Timekeeping For Digital Gods.” To summarize: implementing ticking in a blockchain context based on discrete blocks and transactions is not a trivial task.

There are currently workaround solutions to these challenges such as custom rollups to implement ticking, designing games around unsynced time, or more broadly “lazy updates,” but each approach comes with its own complexities and is still in early experimentation.

Another interesting consideration for building onchain games is the challenge of incorporating hidden information into a global, shared environment (blockchains). Hidden information is a major cornerstone of gameplay. The thrill of a game is making strategic decisions despite not knowing the statuses of your opponent(s) or what treasures/traps the virtual world may hold in store. This becomes especially crucial when you consider that developers have open access to onchain game state and data and can build other features atop them.

Dark Forest used ZK to tackle hidden information, enabling the game to verify critical information, like player and asset location, while keeping the information hidden from other players. This method of verifying and storing game state without publicly sharing that information is critical to making games like MMOs and real-time strategy games (RTSs) work onchain.

While there are certainly challenges to hiding information onchain, there are also net-new unlocks that are enabled by a new form of data privacy. Intuitively speaking, the more data you have to work with, the better you can program games dynamically and expressively. And the more that that data is also able to be kept secret, the more that the data can be utilized without disrupting gameplay or compromising user privacy (i.e., more robust third-party clients because game states are provable).

The set of privacy tools for games is quickly expanding, incorporating other cryptographic mechanisms like MPC, TEEs, and interactive shielding. However these fields remain nascent, expensive, slow, and overall difficult to implement.

An immersive world fosters an engaged community that desires to contribute and proliferate its narrative. The popularity of fanfiction sites like Wattpad (acquired by Naver in 2021 for $600M), Fanfiction.net (12M+ registered users), or Archive of Our Own (6M+ published stories) make this clear.

With the ability to co-author a virtual world comes the power to build its lore in much more meaningful ways. Related to our earlier discussion around emergence, players can contribute to a game’s lore in two principal and often overlapping ways:

1. User-generated content (UGC)

2. Player-to-player (P2P) coordination

We spoke previously about UGC mostly in terms of building entirely new games and assets, but UGC can also materialize in much simpler ways—creating new stories, theories, memes.

THIS CURSED MACHINE lore

Another Zelda example: Koroks, although a relatively small character in the game, became a major theme for many players. In Tears of the Kingdom, players were able to interact with Koroks more “creatively” than in Breath of the Wild, unleashing a swath of player engagement around a feature mostly inconsequential to the main game.

Traditionally, these forms of UGC exist in siloed, side forums like Reddit but more decentralized, open games offer opportunities for players to integrate UGC more directly and expressively into games without permissioned access. However, it’s important to note that open access does not render incremental features such as creator tooling, content-exchange, and content moderation irrelevant. If anything, making these tools accessible to a wider audience becomes more essential.

Player-to-player coordination is another primary channel of lore-building. Player-to-player coordination can vary from chatting on side forums in Reddit to game-native chat rooms or collaborative core gameplay. Much of the lore in EVE Online was developed by stories about its players, rather than the game itself. There’s even entire books detailing the various wars players have independently waged against each other in EVE Online. It’s also worth mentioning that EVE Online announced the development of a game in 2023 called Project Awakening, which will leverage blockchain technology.

EVE Online

Making community-developed and community-owned features like UGC and P2P coordination first-class game citizens creates a core dynamic shift between game stakeholders. Usually, major companies and game developers are trusted to design a game with adequate guardrails and considerations for fun and safe gameplay. However, the more a game is community-driven, the more that power shifts to players, creating the need for strong mechanisms around player governance and identity.

Governance tools are paramount for games that are team-based or inherently collaborative in nature, enabling players to effectively self-organize into teams, organizations, guilds, etc. Informal governance tools largely already exist in games today but making these tools more powerful and programmatic becomes more crucial as games become increasingly open and community-driven.

Governance tokens are an existing model for more open and organized governance that have yet to be fully utilized in games, specifically. A more exploratory vision for game governance tools are mechanisms that allow players to directly govern a game’s code. For example, players that obtain a level of achievement in a game (through the accrual of tokens or otherwise), could be programmatically granted more access to the core mechanics of a game.

A precursor to effective player governance is robust tooling and mechanisms for identity and reputation. Most gaming platforms have methods for players to build profiles, but in a world in which 1) games persist beyond single platforms (cross-platform play), 2) more independent and community-developed games/forums gain industry power (driven by more open tooling and open play), and 3) games generally become more player-driven, identity must become extensible and interoperable.

Onchain identity tools—ranging from cross-platform wallets to soulbound tokens (SBTs) to attestations and flexible signatures—enable players to build holistic reputation across games and platforms, to more effectively self-organize and socialize with other players, to discover new relevant games and be identified by new game developers, and to build stronger trust with each other, rather than relying on a central authority to create restrictions or guardrails within single games (increasingly difficult in an open-game paradigm).

The most experimentation in onchain gaming has undoubtedly been in onchain economies—colloquially known as GameFi. A very direct method to drive player engagement is to create monetary incentives where upside and downside are demonstrably high. For sake of scope, we’ll focus on games outside of casino game genres.

Game assets such as skins have proven over the past few decades to be a robust market, with certain assets selling for thousands of dollars, and some sources estimating the size of the gaming cosmetics market to be $50B. Platforms like Steam that run asset marketplaces can take fees on these sales and can also direct portions of sales revenue back to game developers. Trading points or in-game currency within games or gaming marketplaces is a much less common and usually banned practice unless trade is native to the game’s economy; doing so is also usually technically impossible without trading account credentials.

Recall that earlier we discussed the complexities of designing a sustainable virtual economy. Currency inflation/deflation, asset supply/demand, and pricing all must be carefully manufactured in order to keep a player engaged and active in the game’s economy. While these parameters are usually strictly and manually controlled by the developer (often for good reason), the appeal of tokenizing in-game assets is that it makes these assets more dynamic. Onchain assets and in-game entities (NPCs) can interact more programmatically and autonomously, making the economy more robust and lively.

Onchain game assets are also more easily updatable, composable and interoperable across games. This is ideal in an open, Kingdom Hearts-type multiverse where players can combine game lore—technically possible in a fully onchain world, but unclear today how narratively feasible that is. Perhaps more realistically, bringing game assets onchain makes it easier to combine, upgrade, and trade assets and characters between players. Onchain game assets also present possibilities for game access controls based on asset ownership.

As a more meta note on tokenizing in-game assets: in a world in which “canon” is fluid and player-driven, it’s perhaps easiest to canonize the introduction of a new asset by attaching “value” to it in the form of a market price (whether purely in-game or real-world).

Early play-to-earn games like Axie Infinity explored at-scale the prospects of bringing game assets onchain (NFTs) in order to earn in-game currency (ERC20s) that could be swapped and withdrawn for fiat currency. However, designing open, sustainable in-game economies is a difficult endeavor when gameplay is bifurcated into players and farmers and retention is highly unpredictable. At its peak, Axie Infinity had almost 2.8M monthly active players, whereas today that number is closer to 300K.

Axie Infinity

As a traditional gaming example, Diablo III (2012) introduced an auction house for official in-game trading, but was quickly lambasted by players as they felt that the core game loop was completely broken to focus on the auction house. The auction house was later removed.

Other areas for experimentation in onchain gaming economies include prediction markets and more nascent mechanisms like staking and AI-powered components like sentient NPCs and AI-generated assets. For example, ZK and ML could be combined to leverage ML models verifiably in games, creating “sophisticated agents/NPCs and concurrent storylines” as outlined in EZKL’s “ZKML and Autonomous Worlds.”

Onchain game economies also enable powerful flywheels for mod incentives. While most mods in traditional gaming are separate instances, onchain mods allow value to flow programmatically through the core game and back to its contributors—both core game developers and mod developers—creating powerful social and economic network effects. Designing aligned incentives between large gaming companies and players may seem like a secondary concern, but it becomes more important as you zoom out to the meta trends we’re seeing in gaming at-large. Gaming is becoming more player-driven. The moats companies traditionally rely on are being chipped away by developments like mobile gaming, crossplay, and more indie game development and subsequently more digitally-native game discovery. Creating strategies for value alignment between core game developers and their communities will become a crucial requirement for sustainable game development.

Games are a fantastic playground for exploring the applications of frontier technologies, but games first and foremost have one mission: to create fun, immersive experiences for their players.

We built a general framework for understanding the elements of a game, examining the intricate relationships between players, game environments, and machines.

Understanding player autonomy and emergence as fundamental principles highlights the importance of giving players agency while still maintaining the integrity of gameplay. Within a game itself, the interplay between narrative and gameplay must be carefully crafted to create game immersion, with different genres of games prioritizing these components differently. The machine, as the conduit for player interaction, has historically influenced game design, but the rise of cross-platform play is reshaping the gaming landscape. This development reduces the influence of platform-specific IP and challenges game studios to adapt to a more player-driven future.

Looking ahead with this framework in mind, opportunities for blockchain rails to revolutionize gaming emerge:

For games that are open and built around modding

Robust onchain game engines allow mods to become more composable, enabling players and mod developers to combine and expand upon existing game mechanics and assets seamlessly. This composability creates a flywheel effect for value creation, as modding becomes more accessible and the community grows. Core game developers benefit from the influx of creative content and can even monetize successful mods. Simultaneously, mod developers are still able to benefit from the network effects of existing games, while earning social capital and programmatic rewards for their work.

For games driven by player-driven lore and collaborative gameplay

Onchain games empower players to become co-authors of their favorite games' lore. They can actively shape and expand the game's narrative, which was previously confined to external venues like fanfiction sites or community forums. This newfound power to contribute directly to a game environment adds depth and new life to the storytelling, enhancing player engagement and immersion. With more player power comes the need for extensible identity and governance tools, which can also be facilitated by onchain mechanisms such as attestations, wallets, and DAO tooling, just to name a few. These tools improve players’ abilities to self-organize and collaborate, whether it's forming teams, guilds, or engaging in cross-platform play. Trust and recognition become more transferable, fostering stronger social bonds among players.

For games driven by upgradeable, dynamic gameplay

Games that rely on dynamic, ever-evolving gameplay can benefit immensely from composable onchain assets. These assets enable faster-paced generation and upgradeability (perhaps aided by generative AI), allowing game developers to introduce new content and mechanics rapidly. Players can adapt and customize their in-game experiences in real-time, keeping gameplay fresh and exciting.

For games driven by markets and economies

In games where markets and economies play a pivotal role, onchain economies enable markets to dynamically evolve and thrive. Players can trade assets, purchase items, and engage in sophisticated economic activities permissionlessly, with clear real-world value. The ability to convert in-game assets into real-world value adds an exciting dimension to gameplay, attracting a broader audience while providing tangible rewards for players' efforts.

These opportunities were identified within the scope of how we understand games today, which I felt was particularly important for setting the stage and context for what current users and players expect from their games.

However, it’s important to acknowledge that new developments in crypto and other rapidly emerging technologies may create opportunities that we can only dream of—truly testing the limits of not only the question “What is a game?” but also “what is a world?” While the exact details of the future are unclear, it is glaringly obvious that we are hurtling towards a more user-driven paradigm of play. As players and technologists ourselves, we’re excited to explore that future with you.

Thank you to GVN, baz, Tarrence, Lia Zhang, Neilson Koerner-Safrata, Dante Camuto, guiltygyoza, Emerson Hsieh, Brian Cho, Vivek Bhupatiraju and my Archetype colleagues Katherine Wu, Benjamin Funk, Danny Sursock, Nick Pai, Aadharsh Pannirselvam, and Dmitriy Berenzon for thoughtful review and feedback on drafts of this post.

Reference list of sources instrumental to this post:

• Games: Agency As Art by C. Thi Nguyen

• Gaming: Essays on Algorithmic Culture by Alexander R. Galloway

• Gamecraft by Mitch Lasky and Blake Robbins

• “The Open Problems of Onchain Games” by Charlie Noyes and Doug Feagin

• “Autonomy & Automation” by Neilson

• “Infinite Modding” by Rafael Morado

• “Timekeeping for Digital Gods” by bytes and yonada

Disclaimer:

This post is for general information purposes only. It does not constitute investment advice or a recommendation or solicitation to buy or sell any investment and should not be used in the evaluation of the merits of making any investment decision. It should not be relied upon for accounting, legal or tax advice or investment recommendations. You should consult your own advisers as to legal, business, tax, and other related matters concerning any investment or legal matters. Certain information contained in here has been obtained from third-party sources, including from portfolio companies of funds managed by Archetype. This post reflects the current opinions of the authors and is not made on behalf of Archetype or its affiliates and does not necessarily reflect the opinions of Archetype, its affiliates or individuals associated with Archetype. The opinions reflected herein are subject to change without being updated.

Written by Katie Chiou, Graeme Boy

The word that best sums up consumer technology in the 2010s is gamification. In retrospect, this makes sense, given where technology was at the time. We were entering the mobile and the social eras simultaneously, where everyone essentially now had a connected, networked game device in their pocket at all times.

The early gamification trend ushered in a wave of companies that sought to make games out of normally mundane activities and transform them into booming businesses. It turned visiting places into a game (Foursquare, 2009), monitoring traffic into a game (Waze, 2008), language learning into a game (Duolingo, 2011), the list goes on. What these companies realized was that gamification was an effective strategy for generating promotion, marketing, engagement, and loyalty with their users.

One of the common elements of gamification is a point system, where you can translate qualitative measures of progress into quantifiable metrics. Point systems fundamentally accomplish two ends: binary, legible outcomes (number go up, number go down) and channels to easily direct intrinsic motivation toward extrinsic motivations (perks, streaks, and rewards).

Blockchains are natural infrastructure for point systems because they’re designed as a universal ledger of entities with rails that can programmatically distribute value to these entities based on certain actions.

Historically, this value has largely been distributed through tokens on Ethereum (ERC20s)—financial assets whose value adjusts in real-time in open markets. Tokens are powerful tools for identifying, coordinating, and compensating users who contribute productively to a network with financial rewards and/or shares of ownership.

Token incentives have been critical for blockchain usage. The promise of tokens as financial rewards act as a counterbalance to the relatively high costs and often high risks of transacting on L1s like Ethereum. However, this dynamic can create a vicious cycle. The high cost of onchain transactions means that rewards often go to the users who are willing to pay high fees (often mercenary capital) and are generally not favorable to participants who are less willing to pay high fees or are more risk averse (often new users).

As blockchains transactions rapidly become cheaper—through the proliferation of L2s and L3s—broader classes of non-financial actions become feasible to bring onchain without the urgency and expectation to compensate users with requisite financial rewards. This new paradigm signals the emergence of new onchain primitives such as attestations to identify, coordinate, and engage a complex, decentralized network of users.

Onchain attestations are a method for identifying and classifying users, allowing users to self-attest to their own attributes and to attest to those of others. However, attestations have their own limitations. Attestations are often qualitative, which makes them difficult to use in a low-context, computational environment such as a blockchains. For example, it’s generally much easier to compare a player with 20 kills in a game vs. a player with 12 kills in the same game than it is to compare a player who killed the Green Boss vs. a player who killed the Blue Boss in the same game. This can be improved by increasing the context of the environment, and further scaling combined with developments in AI and LLMs will also make this type of analysis easier. However, given these limitations, it’s likely that more quantitative forms of attestations are most appropriate for where blockchain scalability is today.

We’ve seen experimentation with point systems in crypto begin to take off such as Blur points, which utilizes forms like “Listing Points” and “Lending Points” to incentivize specific actions and to distribute rewards that may include $BLUR tokens. More recently, Rainbow began issuing Rainbow Points to reward users for making transactions in the Rainbow wallet. To date, these point experimentations have largely been offchain, which makes them relatively similar to web2 points programs, at least implementation-wise.

Beyond traditional point systems, onchain points present an interesting opportunity to use points trustlessly within blockchain environments for purposes such as token redemptions for ownership distribution, access gating for sybil resistance, or improving market functionality in DeFi.

The rest of this post serves to illustrate the differences and tradeoffs between tokens, offchain points, and onchain points, and to explore the extent to which onchain points can serve as an additional primitive for builders and users with its own unique benefits and challenges.

In the case of tokens, there are many characteristics that are carefully scrutinized pre-launch and can materially impact the resulting traction of the project and price of its token. Some of these factors include, but are not limited to:

• Supply and Issuance: Will the token be inflationary or deflationary?

• Usage: Will the token be used for governance, and if so, will holding governance tokens represent a claim on any fees generated by the project and control over the allocation of the project’s treasury? Or will the native token be used for utility? Will it be the unit of account/integral to using the project?

• Value accrual: Are there staking mechanisms or lockups? Are tokens spent and/or burned as a means of scarcity and value accrual?

• Distribution: Will tokens be distributed through airdrops or emissions? Will there be vesting schedules?

In the case of points, they are usually non-financial, mutable, and controlled by the issuer, meaning that point systems can be easily adjusted without immediately impacting any market dynamics. Point supply can be unlimited, and the method by which points are used/redeemed can be modified. Moreover, the tradeability of points is also determined by the issuer, whereas tokens are tradeable by design.

Being able to adjust point systems and receive community feedback in real-time without fundamentally changing market dynamics, product mechanics, or user behavior gives teams much more time and awareness to understand and better retain users. In the case that points are used as precursors to tokens, points help remove the urgency for a project to define its token model and distribution too early since it can determine later what proportion of the token supply will be allocated to the aggregate point pool.

Notably, of course, because point systems have established precedence in web2, evaluating them from a regulatory lens is arguably less questionable.

Not only are points more simple to design and execute for builders, they’re much simpler for users. Given the dynamicity of token price, users can find it difficult to know how to conceptualize a certain token: Should I treat it as an investment or as a utility/access tool? For example, imagine an arcade game where you have to pay a quarter to play the game. If you knew that tomorrow that quarter could be worth $10, you might be more hesitant to feed that quarter to the machine.

Points, alternatively, can be thought of as “meta-currencies,” where points can convert into financial value and influence usage, but this conversion can be designed to be less or more direct, depending on the situation. In this model, the redeemability of points becomes much more flexible.

In terms of point utility, points can be redeemable for a variety of options including direct product perks, ownership/equity of the project, governance rights, and/or directly swapped for income. These configurations can also be based on an opt-in basis for users.

The more flexible nature of points raises an obvious question of what differentiates onchain points from offchain points. A key tension that emerges when thinking about tokens vs. points is that ERC20 tokens maximize composability and minimize issuer flexibility, while offchain points minimize composability and maximize issuer flexibility.

Implementing points onchain, rather than offchain, will likely sit somewhere between these two ends, allowing for flexibility while maintaining the benefits of blockchain auditability and composability.

But in practice, what does this really mean and why does it matter?

Composability

In a way, we can regard onchain points as quantitative attestations that people can view and leverage globally. Anyone can issue points to anyone else onchain, as well as build point systems based on other parties’ product usage or native point systems. Onchain points can add a new dimension to a user’s onchain identity, similar to accruing other onchain credentials, that can integrate into various modular protocols. With this framework, onchain points become a powerful tool that projects and brands can use to identify power users across products, and even attract prospective customers with discounts and airdrops.

Provenance

Onchain points also guarantee provenance and auditability, enabling transparency into the total allocation of points in the system, as well as a historical account of the methods of allocation. This transparency is vital to the extent that the point system becomes valuable to the project’s community and the demands for fairness in the allocation process.

For example, brands and agencies often work with influencers based on engagement metrics across platforms like YouTube, TikTok, Instagram, etc. However, these platforms configure and manipulate their algorithms for amplification and distribution in black box environments, making the logic behind metrics indiscernible.

Trust Guarantees

Blockchains allow for explicit guarantees on a user’s current point allocation and redemption options. These guarantees enable safe redemptions of points for other onchain assets with minimal trust assumptions, imbuing onchain points with a potential for value unprecedented in web2 point systems. Without blockchains, point systems that attempt to bridge value will suffer the same criticisms in the crypto community that we levy against web2 platforms—i.e., that they fail to satisfy a level of trust commensurate with their value—and that any stated redemption mechanism can be “rugged” without notice or historical trace.

Sybil Resistance

Point systems are also likely to impact “farming” activity that often accompanies web3 product launches. Bots can farm points just as they can tokens, but point systems can serve as a helpful communication mechanism between project teams and early adopters by explicitly signaling types of rewards that aren’t associated with a token and be used to encourage certain contributions to the product or network—for example, providing liquidity to a protocol or stress-testing certain features.

Community Accountability

Point allocations can also be held to community scrutiny before any redemption mechanisms are revealed in a more explicit manner than traditional airdrops, reducing risk of post-airdrop controversy. Onchain point allocations can even be audited, with a timestamped verification from a third-party.

As we mentioned earlier, points can be designed for a variety of types of rewards ranging from discounts to product perks to ownership/equity of the project to governance rights to direct income. Similarly, points will likely differ widely in implementation across projects, ranging from some form of attestations to modified ERC20 tokens to soulbound tokens. While each method will have its own benefits and tradeoffs, we’ll walk through a likely common flow: redemption for ERC20 tokens.

While ERC20 tokens are the most composable method for distributing rewards, they generally minimize issuer flexibility and maximize speculative behavior. You can make modifications to effectively make them non-transferable or in unlimited supply; however, you still run into the common conflation of the token with a form of currency.

There’s also a cost consideration for implementing points as ERC20 tokens. The transaction costs of transferring ERC20 tokens onchain every time a user joins and/or a point balance is updated can get prohibitively expensive for the issuer. Alternatively, you could accumulate points in an offchain database into a Merkle tree and periodically publish the Merkle root onchain in a smart contract. When a user wants to claim the tokens, they submit a transaction to the smart contract that includes a Merkle proof that, when combined with the user's address and claim amount, can be verified against the published Merkle root (this is essentially how Merkle airdrops work).  This is a common method of distributing tokens because it pushes transaction costs to the end user instead of the project—thereby distributing the total cost (which might be in the millions of dollars) across all the token holders.

Stack* has built a solution for redeeming points for ERC20 tokens trustlessly on any EVM chain, with a distribution method that is cheaper than traditional Merkle airdrops.

While the exact specifications of a point or token system can and will vary on a case-by-case basis, we’ve included a general delineation of characteristics of offchain points, onchain points, and tokens below for guiding reference.

Apart from any technical or crypto-specific implementation considerations, there are still plenty of other crucial design decisions for creating a point system. A few thoughts:

The primary goal of a project’s point system should be to encourage product usage, not to encourage point accrual. Ensuring that point schemes eventually drive users back to your own product ecosystem is key to successfully kicking off a flywheel driven by points, rather than encouraging farm and churn behavior. This is particularly important for value sustainability. Any value lost by offering rewards must be compensated by value elsewhere—more users, higher value transactions, upsells, subsidies through ads, etc. Channeling points directly into product benefits is particularly helpful for maintaining a closed feedback loop and testing the success of specific features/products. An example of this is Farcaster Warps, whereby points earned in the app can be used as gifts to other users, or used to discount in-app NFT purchases. This explicit use-case for points within the product reduces the risk that points are viewed primarily through a speculator’s lens; i.e. only as the basis for some future financial incentive.

An effective points system also requires an intuition of what will move the needle for both your users and your product. For example, if your users are relatively price insensitive, discounts may not be as interesting; other levers like personalization or social access/rewards may be more compelling for products that benefit from strong network effects. If your product is driven by time-in-session, dripping smaller rewards often and consistently may be more productive vs. products driven by large volumes may benefit from issuing higher-value rewards less often.

The story of gamification is not a new one, and there are many case studies that demonstrate that gamification can lead to positive habit-forming, incentive alignment, and increased loyalty between brands and users.

When we look to the future, it becomes clear that decentralized, user-owned networks will define the new internet. In an onchain world, gamified points can serve as a unique way to identify and reward users for their actions and contributions in an even more powerful and holistic way than in web2. Therefore, it’s important to understand the goals and roles of decentralization and ownership in your product and design point systems with those goals in mind. While tokens are incredibly powerful tools to coordinate and govern these networks, they’ve proven to also be more rigid than originally conceived. Onchain points serve as a potential new primitive for teams to use alongside tokens to explore paths to better user identity, user ownership, and incentive alignment. However, points will only be conducive towards these goals to the extent that they’re carefully leveraged with these ends in mind. We’re excited to explore the possibilities of this new primitive with you.

*denotes an Archetype portfolio company

Thank you to Sina Habibian, Andrew Hong, Shreyas Hariharan, Linda Xie, Patrick Rivera, and Archetype colleagues Ash Egan, Benjamin Funk, Danny Sursock, Nick Pai, Tyler Gehringer, and Dmitriy Berenzon for thoughtful review and feedback on drafts of this post.

Reference list of sources instrumental to this post:

• “Beyond Tokens: The Era of Onchain Points” by Graeme Boy

• “Lessons on Points Programs for Crypto Apps” by Li Jin

• Addiction by Design by Natasha Dow Schüll

Disclaimer:

This post is for general information purposes only. It does not constitute investment advice or a recommendation or solicitation to buy or sell any investment and should not be used in the evaluation of the merits of making any investment decision. It should not be relied upon for accounting, legal or tax advice or investment recommendations. You should consult your own advisers as to legal, business, tax, and other related matters concerning any investment or legal matters. Certain information contained in here has been obtained from third-party sources, including from portfolio companies of funds managed by Archetype. This post reflects the current opinions of the authors and is not made on behalf of Archetype or its affiliates and does not necessarily reflect the opinions of Archetype, its affiliates or individuals associated with Archetype. The opinions reflected herein are subject to change without being updated.

Written by Katie Chiou

Communities and cultures are nourished by rich context. Historically, context was a natural product of communities that were local and physically constrained.

The internet ushered in a Cambrian explosion of connection, allowing us to find each other while thousands of miles apart. People began forming communities around factors beyond location, such as personal interests and ideologies. In some ways, the internet felt like the only venue where one could fully and freely express themselves and find other like-minded people without borders.

Developing rich context in mercurial cyberspace, where both people and information move at the speed of light, is a challenge. Digital communities are tight knit, but are often more narrow—focused on one or two key traits rather than any holistic, shared identity.

Platforms and their Algorithms are the all-powerful gods in this climate, the providers of context. While feeding you niche, personalized recommendations, platforms control your rapidly individualized view on the world and alienate you from everyone else. I’ve written about this before in the context of music discovery:

“Constructing identity—both as an artist and as an average listener—is complicated in a Big Algorithm society. I wrote earlier that broadcast and algorithmic feeds are isolating, but the method by which these platforms isolate you is not just by literally cutting you off from local content or discourse. Endless feeds and global search offer access to an infinite scroll of new contextual layers through which to view yourself. While then identity becomes more dynamic and fluid, finding platforms and communities that support these nuances becomes another challenge.”

When you’re alienated from other people, you become even more reliant on the platform to feed you information—namely the creators specifically anointed by the algorithm. There are a few problems that result from this dynamic:

Creators must play by the platform’s rules in order to participate. Pay the platform for amplification, be subjected to their business models and take rates, adhere to the platform’s arbitrary policies and optimizations—or fall through the cracks. As platforms gain more power over who gets elevated, they eventually gain more influence over general cultural production. Kyle Chayka shares an anecdote about an artist, Hallie, in his book Filterworld that illustrates this point:

“Hallie also realized that the Instagram feed rewarded specific qualities. She had always combined visual art and writing, but posts with clear written messages got the most engagement. [...] It was a meme-like assembly-line process perfectly suited for Instagram: the bright colors and simple text added a little spice to her followers’ feeds along with simple moral messages. Followers came to rely on her account for those pieces alone. [...] The pressure that Hallie felt to make the rest of her artwork similarly bright, clear and simple is much like the pressure that a musician feels to frontload the hook of a song so it succeeds on TikTok or a writer feels to have a take so hot it lights up the Twitter feed.”

Culture submits to power-law like distribution. The only semblance of any “shared” culture in an Algorithmic society values mass scale and commercialization above all else, coalescing around major IP from a wildly different past or breakthrough moments that dissipate as quickly as they appear. Attention consolidates around a few mega stars/trends like Beyoncé or Taylor Swift (whose careers took off pre-Youtube) and bottoms out drastically. You see the ramifications of this dynamic perhaps most clearly in the resurgence of reboots, spinoffs, and sequels. According to Adam Mastrioanni:

“Until the year 2000, about 25% of top-grossing movies were prequels, sequels, spinoffs, remakes, reboots, or cinematic universe expansions. Since 2010, it’s been over 50% every year.”

In 2022, the top ten highest-grossing movies were all reboots or sequels.

Consumption-focused design patterns make social platforms less sticky. There has been growing concern about why new consumer social applications have struggled to break out, with theories for cause ranging from domination by existing giants to the influx of tools has made it almost “too easy” to build an app today. One of my personal theories is that it’s a result of the fact that “social platforms” today have become more broadcast-based, rather than actually social. Eugene Wei refers to this development as the transition from “social networking” to “social media.” Platforms are increasingly designed to be consumed, rather than to foster interpersonal connection.

The result then, ironically, is that the platform's network effects diminish, as you’re less bound by the social graph of the platform. Instead, people flee from app to app en-masse without any actual loss or consequence. Social graphs retreat to what Venkatesh Rao refers to as the “cozy web,” insular group chats that retain intimacy, but lose the benefits of discovery or legible digital presence.

In a climate where users are more wary of platform influence than ever before, many are also retreating to physical spaces: underground local clubs, independent studio/community spaces, physical pop-up stores and experiences, etc.

The likelihood of a true retreat to the physical world is unlikely, given how intertwined the digital and physical worlds have become. Digital spaces have undoubtedly become first-class citizens alongside physical spaces, but an interesting tension emerges here:

How do we leverage the expansiveness and connectivity of the digital world, while avoiding manipulation by platform monopolies and maintaining the strong context and intimacy of the physical world?

To answer this question, I believe the next generation of consumer platforms and networks will have to account for the following considerations into their designs:

The user journey across online and offline is incredibly fragmented. As the boundary between the physical and digital planes continues to blur, the ability to form a truly legible, representative identity disintegrates. There is a massive opportunity to build experiences that seamlessly blend the physical and digital, particularly where social graphs can move freely between online and offline.

For individuals/communities: How can my favorite channels online better inform and tie to the people, groups, and places I spend time with offline and vice versa?

For brands: How can a brand better understand how a consumer who bought a product in-store spends their time online and engage them on those platforms?

As a firsthand example, I have a friend who is an interdisciplinary artist whose work generally focuses on the intersection of art and technology (and therefore, is often digital). He works primarily with global, blue-chip art galleries and institutions to exhibit his work, and he also distributes his films on digital platforms such as Metrograph’s streaming service. Because his direct client base is institutions and galleries, he has very few ties to the individuals who actually engage with his work through these channels.

This lack of connectivity creates a few major issues. His work is siloed into infrequent, large-scale exhibitions without clear opportunity for smaller, more intimate releases that directly target and engage his audience; lack of ability to connect with his audience also diminishes the opportunity to take advantage of organic, word-of-mouth marketing that is native to digital, social channels. For example, if I, as an artist, am able to understand what other artists my fans engage with through social channels, I can find ways to collaborate with those artists and increase my own reach.

Today, digital social channels are great for organic distribution that underpins more material monetization opportunities such as partnerships with institutions. A future where creators, influencers, and artists can directly monetize within these channels in a way that improves the relationships between artist and audience and funnel this distribution to other monetization opportunities IRL without relying as heavily on intermediaries would be game-changing unlock.

The concept of “digiphysical” isn’t new, and there are plenty of primitives that were built to bridge users from online to offline: attestations, NFT tickets, POAPs, NFC-chipped objects. General, extensible primitives such as these are useful from a composability and open experimentation perspective, but primitives hold the most power and utility when imbued with context and meaning, such as clear vertical focus or closed product loops. For example, collecting points in a game is only compelling when I know that those points will bring me closer to some certain goal or reward.

An example model to look towards is Blackbird, which has designed a closed product loop for user loyalty and rewards. Power diners/foodies attest to being at physical restaurant locations in order to claim $FLY, which they can redeem for perks at other restaurants.

In regards to user-generated content and media, there are two high-level trends currently occurring in parallel: Individual users are gaining more cultural power, thanks to social media, and users are more wary of monolithic media platforms.

These trends are uncomfortably contradictory, but we see them come to a head clearly in the decline of cultural criticism and the toppling of existing media institutions. Social media platforms have given the average user enough distribution to become their own cultural journalist and critic. Simultaneously, longstanding media institutions and platforms lose prestige and cultural credibility. Yancey Strickler writes about this in, “The Prestige Recession”:

“The death of Pitchfork and cultural criticism is evidence that the mainstream is going through a prestige recession. [...] Rather than prestige, this cultural moment is dominated by metrics, [...] It was once critics who helped shape cultural values – spotting a trend here, putting a scene on the map there – but now the process is driven by metrics. Context, the land of the artist and the critic, has been determined valueless (unless algorithmic) by the mainstream, which honestly never much cared for it to begin with. Instead, art and culture have been safely neutralized as interchangeable commercial objects just like everything else.”

To tie these threads together a bit more tightly, algorithmic feeds have both given users more cultural power and also stripped away power from traditional media institutions that have historically curated and distributed media. However, users have quickly caught onto the fact that algorithmic feeds have become a new form of monolithic platform, coalescing curation around scalable metrics and flattened cultural sensibilities. Essentially, the skepticism towards Big Media has shifted power towards Big Algorithm.

The next generation of consumer social platforms will likely follow a structure where individuals are encouraged to co-create and self-curate their own digital community spaces, abstracting away more centralizing platform mechanics that veer towards explicit scale and monoculture. Every user is able to actively build a community and elevate their own “digitally local” curators, rather than passively consume a single mega-feed that is designed to scale to the masses—think Facebook group pages, Subreddits, NTS channels, Discord servers, etc. A newer platform aligned with this co-creation model is Metalabel, which enables groups to coordinate and publish creative work together.

In order for these digital spaces to grow, the platform will still have to provide sufficient mechanisms for identity and reputation so that users can discover relevant collaborators, communities, and audiences. This process emerges rather naturally in physical, local environments, but bringing these mechanics online is tricky given the natural scale.

To date, digital social discovery and reputation mechanisms have been markers such as “likes” and “followers,” but I imagine we’re bound to soon see more creative mechanisms for users to signal taste and cultural capital to each other, as platforms and communities trend smaller and more intimate.

Consumer social applications have become fleeting almost by default—see Poparazzi, BeReal, Dispo, etc. This is due to a variety of factors including patterns trending more consumption-based versus social discovery-based and therefore less sticky (as I mentioned in the beginning of this post), the arena for attention has become infinitely more competitive in the last decade, etc.

The next generation of consumer social platforms will have to account for and remain resilient to [sped up] trend cycles. Such resilience will become even more crucial as AI-powered, generative content becomes more widespread and accessible.

Umbrella-like or channel-like product structures with sandboxed subspaces are typically more durable because spaces can develop their own unique color, but remain isolated so that they may “burn brightly, explode, and fade away,” to use Packy’s analogy. The caveat to this structure is that it adds complexity for the user in terms of navigation and discovery, and also is a less plausible structure for platforms that are already vertical-specific or particularly narrow in scope.

There are also different schools of thought related to whether a more broad, extensible approach or a more focused approach with a single, unified product experience is more effective. For example, should you build a platform that communities of all shapes and forms can use or should you specifically target and build for one community? You also see this type of question arise around gaming-related platforms: Should you build an app store-like platform or focus all your energy on a single game? My general belief is that while developing a generalized platform is tempting, opinionated, narrow products with closed feedback loops can better retain initial users. Once user trust has been established around a single, quality experience, it becomes easier to expand scope if later desired.

The “drop” model is also another option to consider to keep users consistently engaged, serially launching small-scale products that are generally differentiated, but contained by the overarching brand/ecosystem (ie: MSCHF). The challenge with a drop model is managing retention across drops and making sure the social value of each drop still directly ties to the overall brand equity.

Other writers I admire have offered their own commentary and solutions to this phenomenon.

In “Small Applications, Growing Protocols,” Packy McCormick cites protocols as the layer that may ultimately yield the most long-term value from ephemeral apps that contribute users and data to the base protocol/network. Protocols can then incentivize app developers to build strong products on their protocols through tokens.

Li Jin extends this point further in her post, “Multi-Hit Wonders: Embracing Apps With Short Shelf Life” where she posits that teams can use a token model to capture value from a series of more transient, experimental apps. Moreover, tokens can be used to bootstrap product usage, seize attention and conduct self-marketing, and to create composable ties between different products.

A challenge to designing token models is that financial primitives can often create emergent incentives for other stakeholders that may be difficult to manage. For example, evaluating early product-market fit is extremely difficult when a material percentage of users may be driven by token incentives, rather than product affinity. Effectively leveraging tokens without compromising sustainability of the product will be a key design consideration for teams looking to use tokens as mechanisms for threading value across multiple products.

Throughout this post, I’ve touched on a few different topics that would each be deserving of its own dedicated exploration: identity, social media, traditional media, subcultures, communities, brand loyalty, etc. However, the overarching narrative remains abundantly clear.

Users, culture, and value are flowing more rapidly, more abundantly, and more expansively across physical and digital spaces than ever before. We are still in the very early innings of developing new tools for individual identity, community-building, and culture creation for this new paradigm. The products of tomorrow will look wildly different than the products of yesterday, and they’re already being built today.

Thank you to Patrick Rivera, Eugene Wei, Brian Kim, Jose Mejia, Jad Esber, and Archetype colleagues Ash Egan, Benjamin Funk, Danny Sursock, Tyler Gehringer, and Dmitriy Berenzon for thoughtful review and feedback on drafts of this post.

Disclaimer:

This post is for general information purposes only. It does not constitute investment advice or a recommendation or solicitation to buy or sell any investment and should not be used in the evaluation of the merits of making any investment decision. It should not be relied upon for accounting, legal or tax advice or investment recommendations. You should consult your own advisers as to legal, business, tax, and other related matters concerning any investment or legal matters. Certain information contained in here has been obtained from third-party sources, including from portfolio companies of funds managed by Archetype. This post reflects the current opinions of the authors and is not made on behalf of Archetype or its affiliates and does not necessarily reflect the opinions of Archetype, its affiliates or individuals associated with Archetype. The opinions reflected herein are subject to change without being updated.

Written by Nick Pai, Katie Chiou

At Archetype, we believe that understanding where new interoperability projects are positioned within the infrastructure stack is crucial to making sound investment decisions. The technical stack for blockchain infrastructure has changed drastically over the years, demanding that frameworks for understanding interoperability adjust as well.

With this post, we want to reflect on the evolution of the blockchain interoperability stack, unpack each of its components, and share our mental model for thinking about what comes next.

Native Layer 1s

Native Layer 1s (L1s): In 2017, the blockchain landscape consisted of isolated chains that could only be connected somewhat through centralized exchanges (CEX) as hubs.

“Alt” L1s: As Ethereum gained market share, it became table stakes for other blockchains to have native bridges to Ethereum, rather than having to always go through a CEX. These connections helped bolster Ethereum’s dominance over other chains even further, creating the “Alt L1” narrative.

"Alt" Layer 1s

Layer 2 (L2)-centric: The next evolutionary step saw new networks that not only connected to Ethereum but used it as a data availability layer. These networks, like Arbitrum and Optimism, offered an enhanced UX to end users without trading security, because they used Ethereum as their settlement layer. Naturally they were called “Ethereum L2s” or rollups.

Layer 2-centric

This brings us to today, where L2s have gained a lot of momentum, the Ethereum roadmap is “rollup-centric,” and there are now connections between each of the L2s, a big step from the state of blockchain infrastructure five years ago where there was a handful of independently-secured blockchains that were only connected by CEXs.

Today, the design questions around blockchain interoperability are generally constructed around the following factors:

• L2s that offer very fast and cheap UX

• L2s and L3s (appchains) serving as the home to new user applications

• More chains leveraging shared security and infrastructure

• A focus towards communication between L2 chains rather than just L1 to L2 chains

The future?

The number of connections between blockchains has created a lot more obscurity for people who want to better understand how everything works.

How do my tokens transfer from L2 to L2?

Who is securing my data, and who am I implicitly trusting to keep my data safe?

To answer these questions, we need to understand each layer of the stack.

What we’re going to cover:

• L2s

  • Why are L2s fast and cheap and how are they secured

  • The relationship between L2 and Ethereum (L1)

  • The relationship between L2s and Data Availability (DA) layers

• Sequencers

  • What is a sequencer

  • Shared sequencers

• Fraud Proofs, Validity Proofs, and Proof of Authority (PoA)

• Bridges

  • Types of bridges

  • Bridges vs sequencers

• Intents

  • What are intents

  • Intents vs bridges

• CEXs and DEXs

Let’s dive in.

Users interact with dApps, and users demand that those dApps are fast and cheap, which is why dApps today are often deployed on L2s like Polygon, Arbitrum, and Optimism, and not on Ethereum.

L2s process transactions offchain and periodically publish batches of finalized transactions to some onchain layer that ensures the data was in fact published and made available to verify (data availability). The reason why L2s can be so fast is that they record user interactions offchain on a private server, offering a “web2” experience. In the background, L2s publish batches of these transactions to a data availability layer, offering additional transparency and security.

Choosing a secure data availability layer is the most important security decision an L2 makes. If an L2 is an “Ethereum Rollup,” then it publishes its transaction data to Ethereum.

There are two reasons to choose Ethereum. First, Ethereum is the “most immutable” layer. Once a rollup posts transaction data to Ethereum, it is infeasibly expensive to reverse finality on Ethereum. So, L2s can publish their state to Ethereum and have a very high degree of confidence (following Ethereum’s finality period of ~13 minutes or 2 epochs of 32 slots taking 12 seconds each) that their transaction will not be removed. The second reason is Ethereum’s high availability of data. Ethereum has a large number of nodes replicating and verifying transaction data, making it highly unlikely that data would ever disappear or be entirely unavailable.

However, using Ethereum for data availability is famously expensive. While Ethereum is generally the most secure data availability layer, it wasn’t optimized to just store data—it’s a generalized computing machine.

Until EIP4844 is implemented, there is no way to request blockspace only; you have to pay the same gas as everyone else sending normal transactions on Ethereum. So if an L2 chooses to publish state on Ethereum, it’s choosing the blue chip option but it’s also paying a premium for its security.

What options are available to an L2 that wants to pay less to post state? Enter the DA layer.

Data Availability (DA) layers like Celestia are optimized to offer a place specifically for data availability, where demand for blockspace is lower and blockspace itself is cheaper.

The natural downside is that newer DA layers are less economically secure than Ethereum at launch, given the necessity and time needed to bootstrap a network. Another downside to a pure DA layer like Celestia is that you can’t naturally do computation on the data, which adds a layer of complexity when arbitrating or validating proofs. When sending a transaction on an L2, you should be asking: Which DA layer does this L2 publish its state to, do I trust it, and how can I later access that data?

Modular DA layer

Posting state on an external DA layer removes a centralization vector for L2s insofar as it allows for permissionless, independent verification of state. In the case of optimistic rollups, data availability is needed to generate fraud proofs. In the case of ZK rollups, data availability is needed to ensure censorship resistance and liveness.

If an L2 never published its state onchain publicly, then it would just be in a private server. Users would be at the complete mercy of the L2 operator, which also introduces questions around liveness (what if the centralized operator goes offline?).

If the L2 publishes its state to a chain that is relatively insecure, then users would also be at the mercy of that chain. For example, if L2s posted their history snapshots to Tron, then Justin Sun would have the ability to change the L2’s history.

This is why most L2s choose to publish state to highly secure and battle-tested chains like Ethereum. Users want to know that they have control of their data and that their transactions won’t be modified or reversed.

A key point worth repeating: An L2 is only as secure as the DA layer/L1 that it publishes state to.

Rollups without DA:

They compete for blobs of data; post-EIP4844, these DA layers will compete directly with the Ethereum “Blob” market.

For other types of transactions like sending tokens or interacting with DeFi apps, Ethereum competes with other turing-complete blockchains like Solana, BSC, and Avalanche that don’t publish their state to Ethereum.

Sequencers are the parties that actually publish L2 state to the DA layer. They are in charge of determining the canonical order of transactions on an L2 and publishing snapshots of that history to a DA layer. Sequencers pay the DA layer fees to post the data, and sequencers earn revenue by collecting all fees paid by users who send transactions on the L2s. Sequencers can be single, whitelisted parties, or they can be competitors in a decentralized market vying to publish the next set of L2 state. Typically, sequencers needs to be aware of:

1. State on the DA layer so that it can publish data to it/mint bridged assets (if the DA layer supports smart contracts

2. State on the L2 layer so that it can sequence the L2 transactions

Most of these dynamics assume that the sequencer is also a block builder (which is true of sequencers in production today), but these roles could be decoupled depending on design/development around decentralized sequencers, shared sequencers, and PBS

Generally speaking, proposals for shared sequencers today separate transaction ordering and execution; shared sequencers don’t execute transactions. This design decision makes shared sequencers scalable–they’re fast, sequencer node requirements are light because ordering is stateless, and it becomes relatively easier to decentralize the sequencer set.

However, because these sequencers don’t execute transactions, this places a centralizing force on block builders–the parties that actually execute the state transitions across the connected domains. The more rollups connect to shared sequencing layers, the higher requirements that are needed for builders to be competitive across domains. The higher the resource requirements, the risks of centralization at the builder level. The design space around decentralized block building and proposer-builder separation is vast and for sake of scope will not go down that rabbit hole here.

Another issue: shared sequencers alone don’t offer cross-rollup atomic conditional transaction execution.

For example, a common demand is for a user to bridge tokens from Optimism to Arbitrum and then swap tokens on Arbitrum. Ideally the user would want both of these actions to execute in order, or none at all. In the worst case, the user would end up with tokens on Arbitrum that are not swapped.

To enable this conditional execution for transactions between rollups A and B, a shared sequencer would need to sequence both A and B and publish a shared L2 state to a DA layer containing both conditional transactions.

This is likely where the shared sequencer evolution will go next: interdependent L2 state secured by either “shared fraud proofs” or ZKPs. To get there, shared sequencer behavior and system contracts will have to change to support publishing multiple L2 states in a single L1 transaction.

Prediction: If shared sequencing becomes the dominant paradigm over single sequencing, then state validity between L2s using a shared sequencer will be interdependent.

Here is an interesting proposal introducing this concept of “shared fraud proofs,” and here’s another recent article expounding on tradeoffs in running a sequencer.

Another potential concern around shared sequencers is that teams utilizing shared sequencer networks may lose control over certain operational parameters and value capture opportunities. For example, shared sequencers could extract intra-rollup MEV that would have been valuable to the rollup itself. Given that this would be an obvious race to the bottom in the shared sequencer market, the higher likelihood is that shared sequencers will focus on extracting inter-rollup MEV that wouldn’t have been as easily accessible to individual rollups anyway.

We’ve established that an L2 should post its data somewhere transparent, but how do we verify the data?

If whatever data the L2 sequencer publishes to L1 is considered valid, then what prevents the L2 sequencer from posting an incorrect snapshot of the L2 history? Couldn’t the sequencer pay themselves a little bit extra ETH out of user wallets?

In optimistic rollups, L2 state is published optimistically and is not considered final until it passes through a challenge window (e.g. a 7 day challenge window). During this challenge window, anyone can dispute an L2 state commitment if they believe that the commitment is missing the correct transaction history. To submit a dispute, one must publish a fraud proof that is used in an interactive process to resolve the dispute.

The main advantage of fraud proofs is that they only need to be generated when there is a dispute.

A validity proof claims that the L2 state is valid and proves it at the time of publishing. There is no dispute window; if the proof is verified by an L1 contract designed to verify such proofs, then the L2 state is valid.

The main advantage of proving L2 state via validity proofs is that the L2 state published to L1 can achieve immediate finality. This means that L1 contracts can instantly take the L2 state as “final” and act upon it. This is why L2 to L1 withdrawals for ZK Rollups are very fast (~24 hours), compared to the 7 day challenge window for optimistic rollups.

The last way of validating L2 state is through a Proof of Authority (PoA) mechanism. This is when the sequencer publishing the L2 state basically is given the authority to claim: “This is valid because I am publishing it.” This is how many rollups work in practice today; sequencers run permissioned full rollup nodes that validate state via PoA.There are no challenge windows, there are no proofs. Users simply trust these sequencers to not modify the L2 state.

These proofs are very difficult to implement and expensive to verify. They essentially require simulating the L2 VM execution for a set of alleged L2 transactions and an initial state. If the resulting state that is produced following those alleged transactions on the initial state differs from what the sequencer published to L1, then the state is disputable.

These proofs must be verified on the same DA layer that the L2 state is published to, which makes their verification expensive to run.

The main tradeoffs between fraud and validity proofs:

• Cost to Validate Proof: Validity proofs are generally much more expensive than fraud proofs.

• Speed: Fraud proofs use a Dispute Time Delay (DTD) system–the challenge window–meaning transactions don’t reach finality on L1 until the window passes, whereas validity proofs are verified immediately in a single transaction.

• Implementation Complexity: Both types of proof verification contracts are difficult to build. Validity proofs rely more on the succinctness property of cryptographic tools so that they can simulate L2 state in a single transaction. Fraud proofs are interactive and therefore require fewer cryptographic tools but more offchain infrastructure is needed to support an interactive proving system.

• L2 VM Implementation complexity: L2 state that is validated via validity proofs usually requires a modification to the EVM in order to make the validity proof verification cheaper. L2 state validated by fraud proofs can more easily mirror the EVM exactly.

• Running Cost for Sequencer: Validity proofs require a payment for each submission to L1 while fraud proofs only impose costs when a challenge is submitted. In the case that a challenge is submitted, however, fraud proofs require payment for every interaction between the parties arbitrating the dispute (interactive), whereas each validity proof is generated in a single transaction (non-interactive).

• Upper Limit on Funds at Risk: If a fraudulent sequencer is not disputed, all L2 funds are at risk. If a sequencer does not submit a valid validity proof, then the L2 state is effectively frozen but no funds are lost.

• Operating Cost for Validators: In a fraud proof system, there should always be at least one honest validator watching the sequencer’s submissions. In a validity proof system, there is no need for external validators assuming the validity proof is submitted

It’s worth noting that there are designs for non-interactive fraud proofs in development, though more technically challenging to implement.

There is a lot more to dive into on this topic. We find these resources particularly helpful:

• Validity Proofs vs. Fraud Proofs Strike Back

• Optimistic time-travel

Before diving into specific examples, it’s worth teasing out subtle differences between how bridges are discussed in different contexts.

An arbitrary message bridge (AMB) is a protocol that keeps track of arbitrary cross-chain state—arbitrary meaning anything from token transfers to data storage to anything else. Even more simply, message bridges essentially make state from one chain available on another chain. (This sounds a lot like a shared sequencer.)

Diving into the mechanisms by which bridges are validated/secured is out of scope for this post, important to understand. A few resources that may be helpful can be found here and here (DYOR!)

A token bridge is an application of a message bridge that uses the cross-chain state to transfer assets/capital between chains.

For example, if the token bridge sees that transaction A, a 10 ETH “burn” has happened on Optimism, then it instructs a contract on Arbitrum to release 10 ETH to the user. If the 10 ETH burn gets wiped from history, then the token bridge is likely held liable for this loss. A token bridge is built on top of a message bridge because it needs to be aware of state on both origin and destination chain and also needs to know when transactions get finalized on the origin chain before it acts on the destination chain.

The safest, albeit slowest, way to move assets between L2s is to withdraw via the origin L2’s canonical token bridge to the L1 and then deposit from L1 to the destination L2 via that L2’s own canonical token bridge. Using a canonical token bridge is often a slow process as it’s dependent on withdrawing from an L2 to L1.

A “canonical token bridge” is essentially a special service offered by L2 sequencers. Depositing to an L2 via the canonical token bridge means locking funds on a sequencer’s contract on L1 and requesting that the L2 sequencer mint an equivalent amount of funds on the L2 chain.

Withdrawing from an L2 requires sending funds to a special contract on the L2 to be “burned” and waiting for the sequencer to publish proof of this burn to L1.  Once that proof is confirmed, like any other L2 state published by the sequencer to the L1, the sequencer’s L1 contract can release tokens to the user.

Using the canonical token bridge is as slow as waiting for the rollup full nodes to finalize L2 state on L1, but it’s also as “safe” as it gets when interacting with the L2.

A faster way to transfer assets between L2s is to use a fast bridge. A fast bridge temporarily custodies your capital on a non-sequencer contract that then fronts you your capital on a destination chain. This means that the user is temporarily placing trust in the fast bridge to not modify their information or steal their funds.

How fast bridges work:

The diagram above shows the flow of funds that enable the user to receive their funds quickly, the fees that the bridge earns for providing the fast bridge service, and the finality risk that the bridge assumes for the user.

First of all, fast bridges credit users their bridged amount minus fees on their desired destination chain. In this case, this is 10 ETH minus a 0.1 ETH fee. The user walks away happy to have received their expected amount of funds so quickly.

Let’s pretend that the bridge prefers to custody assets on Ethereum. So, unbeknownst to the user, the bridge protocol will withdraw the user’s deposit via the slower canonical bridge to Ethereum. Once the canonical bridge withdrawal finalizes (e.g. seven days later in the diagram above), the bridge protocol has ended up with a fee surplus of 0.1 ETH on Ethereum (10 ETH user deposit minus 9.9 ETH credited to the user).

In exchange for getting paid for this service, the bridge assumes the finality risk of the user’s deposit: If the user deposit is reverted by the origin chain’s sequencer any time during the seven day finality period, then the bridge will lose funds. This is because the bridge has already credited user funds on the destination chain but will no longer receive the user’s original deposit via the canonical bridge.

How can users be assured that if they deposit 10 ETH on the origin chain that they’ll receive 10 ETH on the destination chain (minus fees)? This boils down to that respective bridge’s security mechanism, which we’ll see looks eerily similar to a sequencer’s security mechanism.

When the bridge credits funds to the user on the destination chain, the user needs a way to verify that the bridged funds were correctly received. Ideally, the bridge also offers a recourse option in the case of an error. One way the bridge can offer this assurance is to allow the user to challenge the bridge in a challenge window. Much like the fraud proof process, this allows users to take their security into their own hands and provide proof of fraud in the case that they never received their funds as expected. This is why it’s important that the bridge publish its transaction history to an immutable DA layer—to offer transparency to users and assure them that if they do ever challenge the bridge, that the bridge cannot modify its history and must correct the error.

So it should be apparent now that both fast bridges and sequencers require DA layers in order to give users confidence that they are processing transactions honestly.

A bridge is only as secure as the DA layer that it posts state to and its dispute mechanism.

These fast bridges serve as a way to provide economic atomicity to users without technical atomicity.  If users could express their preference to execute a transaction on one rollup and conditional on another transaction on another, and is only willing to pay if both of these conditions are met, by providing these economic incentives fast bridges give users the properties of technical atomicity by outsourcing the execution of that to specialized parties in the absence of some actual communication or shared sequencing layer between different rollups.

Bridges can also offer security assurances to users by accompanying messages published to the destination chain with validity proofs. These types of bridges are called ZK bridges. The destination chain requires a contract to be deployed that can simulate the origin chain’s consensus and can verify that an event happened as claimed on the origin chain. The validity proof is used as input into this verification contract to prove to the contract that the message sent to the destination chain is an accurate representation of the request sent on the origin chain.

Of course, bridges can also use PoA if they don’t want to publish data anywhere transparently and immutably.

An intent is a set of preferences that the user wants to be fulfilled including the destination chain(s) where they want those preferences fulfilled.

A marketplace for intents offers to store a canonical history of intents across one or more chains. An intent marketplace allows users to signal their preferences, relayers to fulfill those preferences, and offers validation for the fulfillment of those preferences. If a user feels that a relayer did not correctly fulfill their intent, then the intent marketplace should offer a way for the user to dispute or challenge the relayer.

This is starting to sound a lot like a bridge.

Intents are innovative because they open design space for a different, more flexible mechanisms/language for expressing and executing transactions.

An intent marketplace does not have to be cross-chain but it’s well-positioned to be, given it’s already defining a new paradigm and language for expressing preferences and storing a canonical history of intents.

Cross-chain intent marketplaces can therefore be thought of as a more specific form of general message bridging.

The Archetype team outlines specific examples of intent systems (SUAVE, Anoma) in a previous post here.

We began this post by reflecting on how, in what feels like eons ago in crypto time, CEXs were the main hub for crypto assets. Given all the evolution since then that we’ve just outlined, where do CEXs/DEXs fit into today’s framework?

CEXs essentially function like both dApps and token bridges insofar as you can use them as a way to transfer tokens from one network to another. You can almost think of CEXes as Proof of Authority bridges. The exchange offers little recourse for users in the case that it steals your funds. The main recourse is to challenge the CEX legally, in person. GLHF. DEXs that exist on a single chain are dApps. Cross-chain DEXs are like token bridges plus dApps.

Let’s revisit the full diagram of the model that we’ve built:

• Users interacting on L2s pay L2 sequencers

• Users looking to jump across chains pay Fast Bridges (and L2 sequencers)

• Bridges pay sequencers on the destination chain to carry out bridge activity

• L2 sequencers pay DA layers to store data

• Shared sequencers get first shot at extracting MEV between the L2s that they sequence Shared sequencers also get paid by multiple L2s and can reduce their costs by publishing both of the L2 states in a single, batched transaction to the DA layer

The blockchain interoperability stack has seen multiple iterations over the past several years, leaving trails of valuable takeaways for folks who have closely watched the space throughout history. Regardless of which cyclical buzz word you use (sequencers, bridges, and cross-chain intent marketplaces), interoperability infrastructure begins from the same first principle functions:

• Ordering transactions canonically (whether single chain or across multiple chains)

• Posting data to a transparent and immutable DA layer

• Offering data proof/verification mechanisms

Keeping these principles in mind, we can ask better questions and better assess where value will accrue in the interoperability stacks of the future.

Thank you to @0xFunk, @mrice32, and @pumatheuma for thoughtful review and feedback on drafts of this post.

Disclaimer:

This post is for general information purposes only. It does not constitute investment advice or a recommendation or solicitation to buy or sell any investment and should not be used in the evaluation of the merits of making any investment decision. It should not be relied upon for accounting, legal or tax advice or investment recommendations. You should consult your own advisers as to legal, business, tax, and other related matters concerning any investment or legal matters. Certain information contained in here has been obtained from third-party sources, including from portfolio companies of funds managed by Archetype. This post reflects the current opinions of the authors and is not made on behalf of Archetype or its affiliates and does not necessarily reflect the opinions of Archetype, its affiliates or individuals associated with Archetype. The opinions reflected herein are subject to change without being updated.

Originally posted on Archetype Mirror

Written by Katie Chiou, Benjamin Funk

We’ve seen a lot of lively discussion (and sometimes confusion) around

1. What a sequencer actually does–is it building blocks? Is it proposing blocks? both?

2. How does MEV look different on L2s?

3. What are intents, preferences, and meta-transactions? Why do they matter?

We want to provide an overview of what answers we have to these questions today, why they matter, and how they’re all related. To frame the discussion, we’ll cover the following:

PART I: A step-by-step look at how smart contract rollup transactions work today, and what role sequencers play in the process – transaction ordering, leader election, L2 consensus, finality

PART II: Shared sequencers and what they mean for decentralization + MEV implications – cross-domain MEV + atomicity

PART III: Rethinking the transaction lifecycle, order routing, and proposed frameworks – SUAVE, Anoma, etc.

Let’s walk through how a smart contract rollup transaction works today.

1. User signs transaction, transaction gets sent to sequencer

2. Sequencer orders transactions

3. Sequencer produces pre-confirmation

4. Sequencer posts to DA layer + Rollup node posts updated state to L1 bridge contract

Pretty straightforward.

Pause. “Ordering” here suggests two parts – deciding how the transactions are ordered (transaction ordering) and who constructs the block (leader election).

You can also think about this distinction as building and proposing. It’s worth noting, however, that the exact order in which these events take place depends on the assumption that a sequencer is responsible for both roles (building and proposing), versus whether the roles are unbundled.

Currently, the way rollup sequencers function is that there exists a single, centralized sequencer run by the team. This is not ideal for several reasons:

• Liveness: A single, centralized sequencer is highly efficient, but could also provide weaker real-time liveness––the guarantee that the system is always available and functioning correctly. If the sequencer goes down, what backstops/backups are there to make sure transactions are ordered? One solution is to decentralize the sequencer set; however, decentralization can introduce complexities that may compromise liveness. While Espresso’s piece explains this in depth, the main point is that, if decentralized sequencers also engage in consensus, decentralization can lead to worse liveness if synchronicity (messages between nodes are delivered within a known amount of time) is lost. The extent to which losses to synchronicity affect liveness depends on the categorical choice of consensus mechanisms (dynamically-available vs optimistically responsive).

• Censorship Resistance: How do you ensure that the single, centralized sequencer is not censoring transactions? Technically, users can already force withdrawal/inclusion of transactions directly through the rollup contract, but this is expensive and inefficient. A main benefit of a sequencer is that it amortizes the cost of posting transactions to the contract across a batch.

• Centralized chokepoint: A single, centralized sequencer has the autonomy to maximize rent extraction to the detriment of users.

Sequencers on L2s, in addition to largely being centralized entities, also operate similarly to both an L1 builder and an L1 proposer–they both build the blocks with transactions from users and searchers and propose blocks to their underlying layers. Centralized sequencers operated by L2 teams run full nodes, meaning they're responsible for ordering transactions, committing them to the data availability (DA) layer, and executing transactions such that they can post validity or fraud proofs to the L1 bridge contract.

Decentralizing the sequencer set means removing the trust assumption that the team(s) running the sequencer(s) will not act maliciously or in an extractive manner and unbundling the roles within sequencing so that they specialize in ordering and allow the computation of fraud and validity proofs to be permissionless.

A key competency of sequencers today is transaction ordering — how are transactions packed in a block (MEV!)?

Transaction ordering methods can usually be categorized in three (not mutually exclusive, often used in tandem) ways: auctions, encryption, and fair ordering.

• MEV Auction (MEVA):  Sequencers can permissionlessly bid in an auction for the right to order transactions, with rights awarded to the highest bidder (could be slot-based, block-based, time-based, etc.). Designing the optimal block auction is a difficult task, given the auction can be designed around several vectors: block vs slot-based, time vs bid-based, or batch vs streaming-based. Moreover, MEVA can introduce unwanted latency.

• Encryption: The basic idea of private/encrypted mempools is that users submit encrypted transactions, and block producers commit to these transactions before decrypting them. Encryption doesn't inherently provide a mechanism for ordering transactions, but it can be used as a method to ensure the pre-execution privacy of transactions so that the sequencer's ability to extract MEV through transaction reordering or censorship is restricted. Sequencers receive and commit to these transactions in their encrypted form. The decryption process, which reveals the actual transaction data, can occur at a later stage when transaction validity is being verified. One of the major challenges to utilizing encryption is that it creates a vector for DOS attacks. Shutter’s approach to solving this issue implements the requirement for the user to include a signed envelope within the encrypted transaction that covers fees (instead of specifying a gas limit) at the time of its inclusion within a block (not execution). While metadata leakage becomes a vector for MEV here, it’s possible ZK proofs could play a role in preventing that issue. Different methods of encryption offer different drawbacks/are in different stages of development but a few are summarized below:

  - Secure Enclaves: Using trusted hardware technologies like Intel's SGX or AMD's SEV, sequencers work on transactions within a secure, isolated space. To prevent MEV extraction, additional rules (like deterministic ordering) need to be enforced within the enclave.

  - Threshold Encryption: A group of block producers jointly decrypt encrypted transactions for execution after ordering, distributing the decryption responsibility to limit potential MEV extraction. In the Ferveo protocol, for example, a group of validators produces a shared public key, dividing its corresponding private key into individual shares. Transactions are encrypted with this public key, and require a threshold of validators pooling their private key shares in order to be decrypted. After decryption, transactions are executed strictly as per the committed order, preventing the insertion of MEV-inducing transactions. However, it's critical to note that the complexity of key generation, sharing, and management escalates considerably among validators in threshold encryption schemes. This makes achieving high levels of decentralization (comparable to Ethereum mainnet) practically unattainable, limiting such schemes to between 100-999 validators.

  - Timelock Encryption: Users send transactions in a time-locked "safe" to the sequencer. The sequencer includes these locked transactions in the block, and they are only "unlocked" (decrypted and executed) after a certain time or condition is met, keeping the transaction details hidden from the sequencer until execution.

• Fair Ordering: Fair ordering protocols/frameworks that implement specified ordering policies can be used in tandem with decentralized sequencer networks, such as that of Themis or Aequitas. Chainlink Fair Sequencing Service is another example. However “fair” ordering as a concept is hotly debated. A recent talk on fair ordering you may have seen recently. Even more on fair ordering.

Note: We could write an entire piece of equal length and density exclusively on transaction ordering + MEV broadly. A lot of this is already covered in discourse for L1s, so we’ve intentionally kept the above section high-level for sake of brevity. We encourage you to dive into this rabbit hole, separately! A fantastic resource: Frontier Research. We discuss MEV more later in the context of rollups and implications for cross-domain MEV, but keep scope limited.

The other key competency of sequencers–that becomes increasingly important for a decentralized sequencer set–is choosing who has the right to propose each block to the network.

This is an important distinction because in a world in which proposer and builder roles are unbundled, sequencers/proposers can still create blocks that are partially pre-ordered by external builder parties, and still include their own ordered set of transactions.

A few different mechanisms for leader election:

• Proof-of-Authority (PoA): The role of the sequencer could be assigned using a simple round-robin algorithm, especially suitable for a permissioned set of sequencers given the trust assumptions that sequencers act fairly. This is not to say that round-robin constitutes PoA. Rather, it's one way to distribute the sequencing responsibility among a trusted set of entities in a PoA-based rollup system.

• MEV Auction (MEVA): The auction between who builds a block (which we already covered) and who proposes a block can be distinct (leader election). Whereas MEVA for block building can be modularized to other parties, sequencers remain concerned with rights to propose the next block, hence using MEVA. Penalties would still need to be introduced to reduce the risk of bad actors. Proceeds of the auction could be distributed, burned, or go towards some treasury. The limitation of MEVA is that there are still plenty of vectors for centralization risk, such as collusion between sequencers during the auction process. Generally, MEVA in both instances of transaction ordering and leader election could look rather similar.

• Proof-of-Stake (PoS) for Leader Election: You can use PoS for leader election, where it's permissionless to join as a sequencer but you must stake the native rollup token. Increased stake improves your chances of being selected as leader (centralization vector). Since the sequencers are now staked, they can be held accountable through slashing penalties. In this case, the rollup would still use the L1 for consensus.

While most mechanisms implemented lead to the election of a single leader/proposer, protocols like Multiplicity allow for Multiple Concurrent Block Proposers (MCBP). In this setup, validators each create a special bundle of transactions, sign it, and send it to the leader, who must include at least 2/3 of these stake-weighted bundles in the proposed block for it to be valid. This prevents the leader from excluding transactions present in more than 1/3 of these bundles, which helps mitigate the potential for rent extraction and censorship resistance that occur in granting single leaders/sequencers/proposers monopolies on transaction inclusion.

When users send transactions to the sequencer, there’s a time gap between when the sequencer receives the transaction and when the eventual batch is posted to the L1. In the meantime, the sequencer gives a pre-confirmation:

“I promise I will order and eventually publish this transaction to the L1 as expected.”

This is referred to as “soft finality.” The period of time that exists between soft finality and actual finality depends on several factors, perhaps the most notable being whether the rollup uses fraud proofs or validity proofs.

In the case of a centralized sequencer, pre-confirmations are pretty simple because transactions are finalized under the assumption that the single, trusted sequencer won’t act maliciously. In a decentralized paradigm, this gets more tricky.

Rollups can also incorporate their own consensus mechanisms, which strengthens the finality guarantees sequencers make by ensuring the inclusion of transactions in blocks prior to the final consensus on the DA layer. Centralized sequencers provide soft finality rapidly, often in under a second, due to their role as sole block producers. However, the strength of the pre-confirmations hinges on the accountability mechanisms in place, as dishonest actions by sequencers can weaken the guarantees of soft finality.

The addition of L2 consensus adds a layer of accountability (often economic), as sequencers are penalized if they fail to include a transaction in a block after providing a pre-confirmation. L2 consensus can be implemented through various traditional consensus mechanisms such as PoS leader election or BFT consensus, each carrying their own trade-offs in terms of sequencer overhead and implementation time. However, it’s a hot topic for discussion whether L2s need local consensus (especially if it's PoS-based), potentially introducing more vectors for validator collusion and decreased efficiency. Colluding validators could charge inflated fees, censor transactions, or reap other economic benefits. It’s also possible that if L2 validators capture more value, there may be less incentive over time for L1 validators, compromising overall network security.

One option to address concerns with PoS-based L2 consensus, in particular, is to leverage restaking, which is what Espresso plans to do with EigenLayer. Restaking in this context would help to further decentralize the sequencer (reducing susceptibility to DOS attacks) and improve shared security with the L1.

Next generation consensus mechanisms are being introduced to address the aforementioned issues, we’ve included a few proposals by different teams below:

• HotShot: HotShot is a consensus protocol introduced by Espresso, based on the HotStuff protocol. HotShot seeks to offer high throughput and fast finality for decentralized sequencer networks.

• Proof of Efficiency: Proof of Efficiency is a consensus mechanism introduced by Polygon Hermez meant specifically for ZK rollups. It involves a two-step model that splits activities between a sequencer and an aggregator.

  - Sequencer: aggregates L2 transactions into batches and posts them to the L1

  - Aggregator: submit validity proofs on L1 for batches posted by the sequencer

In the case of optimistic rollups, the sequencer posts transaction data to the DA layer, and this transaction data is used by the specific rollup nodes known as "proposers" (not to be confused with block proposers) to compute the updated state root. Then, the updated state root is submitted to the rollup’s enshrined bridge contract, along with an associated bond. If a proposer makes an incorrect attestation to state updates, it's detected by another type of full nodes, known as "verifiers.” Verifiers execute rollup state transitions and, if necessary, can slash the bonds of proposers through a fraud proof game.

In the case of ZK rollups, the sequencer is usually responsible for passing on the block of ordered transactions to a prover, which then generates the validity proof and passes it to a rollup full node–along with the associated full transaction data or state diffs. Data sent by rollup full nodes to the availability layer can be complete transaction data, offering high transparency and quick finality but at high resource cost, or state diffs, which are space-efficient and cost-effective but sacrifice transparency and delay finality. The choice between these options hinges on the specific needs and constraints of the ZK rollup implementation.

Much of how and when finality is determined depends on consensus design as described above and whether the rollup uses fraud proofs or validity proofs.

As soon as the rollup posts transaction data on the data availability layer, rollup nodes can compute the new state root of the rollup and finality is achieved within the realm of the rollup. For the L1 however, which hosts the rollup bridge smart contract, finality is achieved once this state root has been verified through a validity proof (ZKR) or after the fraud proof window (ORU) has passed.

One mental model, offered by 0xrainandcoffee, for the finality levels of rollups is categorizing them into 4 different stages, depending on the rollup. These are:

1. Pending_On_L2: Soft commitment given by the rollup’s sequencer(s) that the users’ transactions will eventually be committed and finalized on the underlying layer, of which it derives security.

2. Finality_On_L2: The sequencer(s) has committed to the state transition function of the rollup, and the block(s) have been added to the canonical chain of the rollup

3. Pending_On_L1: Transaction input or output/state transition function has been posted to the L1, but the dispute period or validity proof has yet to be posted, or period ended – this requires two successive epochs to have passed for Ethereum. This is the point where most Optimistic rollups say finality has been reached, however according to the canonical bridge – there’s still, at this point, an arbitrary 7-day challenge period.

4. Finality_On_L1: The dispute period has ended for Optimistic rollups, or the validity proof has been posted and verified, as well as confirmed in two successive epochs with a supermajority.

In the context of “sovereign rollups,” the sequencer's role is primarily to order transactions within each block, which are then posted to the DA layer responsible for coming to consensus on the order of blocks. Sovereign rollup full nodes execute transactions to ensure their validity, but inherit the re-org and censorship resistance as well as liveness guarantees from their DA layer. As for light clients in a sovereign rollup, they rely on validity or fraud proofs generated by full nodes. While the sovereign rollup inherits the security of the DA layer for natively issued assets on the rollup, there is currently no way to safely transfer assets from said DA layer to the sovereign rollup like with smart contract rollups. However, we know work is being done by teams to address this exact issue.

Now, we generally understand how a rollup transaction currently works and the nuances in the process. Perhaps, most importantly, we can differentiate between the tasks of a sequencer to include 1) building blocks 2) proposing blocks and understand why these roles should be unbundled/sequencer sets decentralized.

Let’s now evaluate new models for how sequencing could work.

Rollups can look to shared sequencers for decentralization, rather than designing their own methods for decentralizing their own sequencer set. A shared sequencer is a network that aggregates and orders transactions across multiple rollups.

Leveraging a shared sequencer across multiple rollups enables easier and stronger decentralization, which gives the general benefits of a highly decentralized sequencer set including liveness, censorship resistance, economic security, and stronger pre-confirmations. Shared sequencers, in particular, also expand the design space around rollup interoperability and MEV.

Astria is one of the first teams to build a shared sequencer network, Metro. A key property of how Metro works is that it separates transaction ordering from execution. The sequencer is responsible for ordering transactions, but does not execute them. Isolating the function of the sequencer to ordering without having to run a full node materially reduces overhead, allowing for higher sequencer network decentralization (higher censorship resistance). Once transaction ordering has been agreed to, execution (and proving) can later be deferred to an entirely different party, which doesn’t need to rely on censorship resistance.

After the sequencer orders the transactions and publishes them to the DA layer, now “lazy” rollup full nodes can simply download the transactions, optionally apply a fork choice rule to select a subset of transactions, perform any arbitrary transaction processing, and apply those transactions to the state. Headers can then be generated and gossiped to light clients. Lazy rollups by default share a mempool with the sequencer set. Given shared sequencers don’t check for invalid state transitions, lazy rollups must be able to deal with invalid transactions.

Also notably, rollups are able to fork from the shared sequencer at any time because they still maintain sovereignty (transaction data is retrievable from the DA layer).

Espresso is another team working on a shared sequencer network. The core principles of the Espresso sequencer are similar to Metro, with architectural differences. It’s worth noting that the concept of “lazy” blockchains was popularized by Celestia (closely tied to Astria), uniquely informing Astria’s architecture. The Espresso sequencer is secured by EigenLayer (restaking), is built on HotShot consensus protocol (mentioned above), and Espresso also provides data availability (Astria uses Celestia as the DA layer).

Another noteworthy shared sequencer project is Radius. Instead of decentralizing the sequencer set that orders transactions, Radius employs self-limiting cryptography on a single centralized sequencer. In their approach, users create time-lock puzzles and send them along with their encrypted transactions. These time-lock puzzles delay the sequencer's ability to discover a symmetric key, but once found, the key is used to decrypt the users' transactions. To mitigate the risk of invalid transactions causing a DOS attack on the sequencer, Radius incorporates ZK proofs as attachments to the encrypted transactions, offering a means to verify their validity without relying on a signed envelope within the encrypted transaction, as done in the Shutter-style method mentioned earlier.

Shared sequencers also have interesting implications for cross-domain MEV and atomicity.

As more rollups join the same sequencer network, more cross-domain MEV becomes extractable. There are growing concerns that rollup interoperability and cross-domain MEV introduce additional centralization vectors. Sequencers could collude to control cross-domain MEV. Validators who participate in multiple PoS consensus protocols for independent domains have greater access to and potential control of cross-domain MEV opportunities.

In the case of cross-chain atomicity, cross-chain messaging is traditionally done asynchronously, but shared sequencers expand this design space. A classic example of where cross-chain atomicity is relevant is atomic arbitrage. Cross-chain atomicity ensures that the trades are executed conditionally/simultaneously. However, you will still never have the same guarantee that you would have if you were transacting entirely on L1.

It’s also worth noting further emphasizing that the shared sequencer ensures atomic inclusion, but not execution. This is because sequencers can’t make any guarantees over the fallibility of transactions. If one leg of the intended atomic cross-rollup operation fails, the sequencer has no way to control that as their responsibility is to order, not execute. The implications of this detail mean that simple atomic arb can be executed atomically, but transactions like swaps can’t be. However, using a shared sequencer combined with additional infrastructure like timelocks and cross-chain messaging protocols for rollup nodes to verify the state of the other rollups could still enable wider cross-chain capabilities.

In a multi-rollup environment, the potential for extracting MEV atomically diminishes as the scope for probabilistic MEV capture increases. This shift occurs due to the fragmentation of dapps across multiple domains and the inherent lack of cross-chain atomicity across these environments.

This landscape presents unique MEV opportunities; however, they come with higher barriers to capturing them. The absence of cross-chain flash loans increases capital costs, and the lack of atomicity across environments means more uncertainty surrounding the successful execution of all components of an MEV strategy. Consequently, searchers capable of handling additional inventory risk are well positioned, as well as searchers equipped with specialized algorithms and infrastructure adept at managing probabilistic MEV.

All of these factors point to the fact that those with more capital are better positioned to capture opportunities in this cross-domain world, and that the resulting environment could lead to increased block builder centralization.

This potential future underpins the motivations and benefits of developing solutions like SUAVE that provide stronger guarantees around cross-chain atomicity amongst other more direct benefits to users.

Now that we better understand the transaction lifecycle, we can dive into how proposals like SUAVE and Anoma and high-level concepts like preferences and intents seek to improve how we think about transactions and order routing.

A key point we wanted to drive home in earlier sections was the distinction between the following roles: building, proposing, executing. SUAVE is a proposal for a decentralized block building market. SUAVE is often called a “sequencing chain,” but this can be a little confusing because it’s specifically focused on block building.

SUAVE is an independent network that functionally serves as an aggregated mempool and decentralized block builder across multiple domains. Users express preferences by signing a transaction indicating a particular goal (you can think of preferences analogously to “intents” or “meta-transactions” in other frameworks––the user signs a preference to indicate a particular goal ie: I want to transfer ETH).

Following this, “executor parties” (block builders) engage in a competitive auction to have their bundles included. During this process, the potential MEV subsidy to the builder begins as negative and increases over time, all while builders running SGX brute force different orderings of preferences until a winning executor finds a point at which, if the bundle is mined, the total arb value > marginal cost of the MEV subsidy–leading to optimal execution and MEV minimization for users.

You can think of SUAVE as a shared builder, and a shared sequencer as a shared proposer.

Once an executor has won the auction, they could create a proof that the bundle of transactions follows certain validity rules and send it to a shared sequencer network where it can be permissionlessly and privately aggregated with other bundles from other rollups into batches, which are finally posted to each respective rollup’s DA layer.

While SUAVE doesn’t require the existence of shared sequencers to work, its architecture can be synergistic with shared sequencer networks. SUAVE could also work with centralized and/or decentralized sequencers that are more vertically integrated into the rollup as well.

While SUAVE improves upon trust assumptions present in MEV Boost in the sense that bundle proofs are used instead of a trusted third party (TTP) like a relay, it’s important to note that once the bundles have been confirmed by the destination rollup, an oracle (which introduces trust assumptions!) sends updates to SUAVE that the state transition has occurred.

SGX, a TEE produced by Intel, introduces another trust assumption as its enclave has been compromised in the past. While it serves as a production-ready option for executing computations on encrypted data, it isn't the only option. A new wave of trustless cryptographic solutions, which fall under the umbrella of homomorphic cryptography, offers alternatives. Justin Drake has an excellent talk on existing and future solutions to this challenge, which are summarized in the following slide.

Anoma is another protocol proposing an alternative framework for preference expressions that is very different from how we think about transactions today–designed fundamentally differently from existing smart contract platforms like Ethereum.

Ethereum today offers programmable settlement, where the chain is primarily occupied with settling state transitions. Settlement is sufficient if the parties involved know 1) who they are, 2) what they want, and 3) with whom to coordinate.

However most transactions don’t fulfill these requirements, they are multi-party and need counterparty discovery–helping counterparties discover each other, coordinate with each other, and agree what to settle.

Today, applications handle counterparty discovery themselves, largely through the following approaches:

• putting everything onchain–expensive! (ie: DEX)

• having a centralized server offchain–additional trust assumptions! (ie: centralized sequencer, OpenSea)

• having an app-specific sovereign chain–development complexity! lack of composability! (ie: DyDx)

More details on the above presented by Adrian Brink from Anoma

Anoma presents an architecture that is intent-centric, allowing users to express what they want, not how to get it (we’ll cover this distinction in a later section).

In Anoma, users sign binding intents (you can think of intents analogously to “preferences” or “meta-transactions” in other frameworks––the user signs a preference to indicate a particular goal ie: I want to transfer ETH) and then submit it to intent gossip node(s) that form pools of intents (could be a global pool or more specified). “Solvers” (analogous to “executors”) monitoring the pool of intents will then aggregate compatible intents into a state transition that fulfills all the intents of the users and submit the transaction to any full node.

It’s important to emphasize that Anoma is not inherently a blockchain, but an architecture that can be implemented by any chain. Each instance of Anoma is referred to as a “fractal instance.” For example, the first fractal instance of Anoma is Namada, a Layer 1 PoS chain.

Anoma and SUAVE provide interesting alternative frameworks for how we think about transactions, converging on the general concept of intents.

We’ve skated conveniently over intents and preferences so far, so let’s unpack what they mean.

Justin Drake said recently on a podcast about MEV, “Users generate intents, they don’t generate transactions.” While this is true conceptually, we’re still far from an implementation system that goes from intent to transaction formation to optimal execution efficiently.

Today, when a user signs a transaction, they authorize a function call which, depending on the state of the chain at time of execution, can have radically different outcomes. This is very counterintuitive to how most people would expect transactions to work: a user indicates their goal, and then the transaction achieves said goal.

In a truly intents-centric world, a user declares/signs their preferences, and how that desired state is achieved is left to a network of third-party actors, (solvers/executors), to execute these preferences on their behalf. Going a step further, what Justin goes on to point out is that in an ideal world, intents can be aggregated and fulfilled in a single, optimized master transaction that executes all users’ intents simultaneously by leveraging coincidences of wants across each users’ intent.

The best infrastructure to express, communicate, and execute intents should minimize MEV, maximize censorship resistance, and ideally be optimized for cross-domain interactions.

Moreover, they should consider the extent to which the burden is placed on the user to communicate their intent more granularly, which might overcomplicate UX–a decision that will fundamentally affect the architecture of said intents protocol.

Alternative transaction types have emerged in discussion to address the limitations of today’s architecture, but they also introduce additional trust assumptions around economic censorship. You still have a lack of system-level guarantees that the solver/bundler is not excluding a particular set of transactions from the mempool (re-introducing a commonly discussed issue with transactions today).

In ERC4337, for example, introducing offchain infrastructure like alternative mempools means that bundlers (which act as solvers for user preferences) are needed to communicate with onchain smart contracts. Consequently, we need to make sure that these bundlers don’t selectively censor intents they don’t want to broadcast. There are a couple of solutions to this problem, and if you’re thinking, “wait, don’t Anoma/SUAVE solve this,” that’s absolutely right–SUAVE does so through the *onchain* auction between executors/block builders.

More generally, having these agents (bundlers, executors etc…) come to consensus over what the list of valid user intents are, is one of the main ways we can create censorship resistance (also inclusion lists!). While the implementation details of the type of consensus required here are TBD, we know that this is what blockchains are good for! On the other hand, this involves communication overhead that introduces latency and reduces throughput. Another potential solution to this model could be plugging into an optimistic model, but this introduces the necessity for bonds on the part of users and solvers, decreasing capital efficiency and complicating UX.

One possible solution: build the logic into smart contracts. Then, we wouldn’t necessarily have to specify an alternative transaction type for users to optimize their preferences. Unfortunately, this is when theory doesn’t meet practicality–the difficulties of onchain scalability make it harder to express more creative, complex logic in smart contracts (there are folks working on this, Soon!). Long-term, provable guarantees of offchain computation with cryptographic guarantees through ZK could be the solution to intent expression. ZK has the potential to improve the speed and cost of executing users' desires and the quality of their execution, without creating an alternative transaction type and the baggage that comes with it.

What this doesn’t address is interoperability. In a multichain world, approaches reliant on app-specific integrations could lead to insufficient UX abstractions.

Systems like SUAVE and Anoma that instead enable a network of permissionless solvers running full nodes across domains to execute these preferences could lead to more optimal execution because these solvers can incorporate more information *faster* about the state of other chains without needing to communicate information to users or integrating with the latest DEX on BSC where liquidity for Mongoose Coin was just seeded.

iykyk

Interestingly, we’ve actually seen intents implemented before–just in a more narrow context. Just as intents “outsource” how the desired state is achieved to a network of competing third-party actors, (solvers/executors), RFQ broadcasts for trades get routed to solvers. Doug Colkitt’s explanation elegantly conveys the “lookback option” problem in solver-based RFQ systems that exist today, providing interesting lessons for designing generalizing intent systems moving forward. What’s important to note is that the obvious implications of RFQ literature apply to the context of trades, but in general intents can be used to specify any desired end state not just for a trade.

The TL;DR here is that it’s fair to say that as an industry, we haven’t converged on the optimal architecture for users to express intents––whether it’s ERC4337 (meta-transactions), Anoma (intents), or SUAVE (preferences)––nor have we determined where in the stack the orchestration of these intents will be housed.

One hypothesis: wallets––the interfaces where users sign transactions––are best placed to enable users to specify their intents and to allow for programmatic expression of user needs and conditions within transactions, helping to sidestep the principal-agent issue. However, in the short term, there exists a temptation for some wallets to bypass builders/searchers competing to redirect MEV back to users, choosing instead to extract MEV themselves through the bundles they control. While some wallets will probably do this, it’s a strategy that overlooks long-term viability. Regulatory developments will eventually extend the principle of best execution from traditional finance into crypto markets, likely making this self-serving MEV extraction on the part of wallets illegal. Beyond regulatory concerns, it’s probably still a -EV strategy for wallets considering the transparency of onchain MEV extraction and the ease by which users can migrate their keys to competing alternatives. With these realities in mind, leading wallets, as the conduit for users’ intents, will strategically uphold their fiduciary duties regarding best execution for their users. There are several ways they can do this: by routing user intents directly to neutral platforms like SUAVE's mempools; indirectly through their own or a trusted external ERC4337 bundler; or via other forms of Multi-Party Computation (MPC) or Account Abstraction (AA) that serve the same purpose without necessitating an ERC4337 bundler.

Design space in crypto is an ever-expanding plane. We are constantly pushing the boundaries for performance, expression, and decentralization. The way these boundaries manifest is through blockspace. How do we build blocks in a way that is most performant, aligned with users’ goals, and resistant to centralized parties and censorship? These are questions that have been asked since Day 1 of the Ethereum network.

Emergent architectures around sequencers ask us to reconsider these questions in a rollup-centric world. On L2s, we’re moving past the pre-PBS era, where centralized sequencers currently act as both the proposer and builder.

Systems like SUAVE and Anoma push us on even more questions, like how blocks should be constructed in a privacy-preserving, cross-domain world and how we should think about transactions at their most abstract level of meaning.

Today, how we think these decisions manifest, is that sequencers–whether centralized, decentralized, or shared–will either plug into alternative mempools designed to enable alternative transaction types that increase the scope of what preferences users can express–or keep chugging along what they’re doing will innovations in scalability solutions take care of expanding the expressibility of smart contracts and user preferences.

However, the questions we’ve posited are complex and the community is discussing them in public forums day in, and day out. We’re excited to be there with you.

Thank you to @0xJim, @Hactar0, @jillrgunter, @_danielmarzec, @PossibltyResult,

@willkantaros, and @mountainwaterpi for thoughtful feedback on drafts of this post.

Our work builds upon incredible research from others, and we cannot spotlight them enough:

• Jon Charbonneau, dba

• 0xrainandcoffee, Maven11

• Alex Beckett, Celestia

• James Prestwich

• Patrick McCorry, Arbitrum

• Flashbots

• Espresso

• Celestia

• Anoma

and countless other sources.

Disclaimer:

This post is for general information purposes only. It does not constitute investment advice or a recommendation or solicitation to buy or sell any investment and should not be used in the evaluation of the merits of making any investment decision. It should not be relied upon for accounting, legal or tax advice or investment recommendations. You should consult your own advisers as to legal, business, tax, and other related matters concerning any investment or legal matters. Certain information contained in here has been obtained from third-party sources, including from portfolio companies of funds managed by Archetype. This post reflects the current opinions of the authors and is not made on behalf of Archetype or its affiliates and does not necessarily reflect the opinions of Archetype, its affiliates or individuals associated with Archetype. The opinions reflected herein are subject to change without being updated.

Working in crypto has always garnered a lot of intrigue (and sometimes skepticism) from the people around me, but in the aftermath of some of the most disastrous crypto headlines in history, I’ve been fielding more questions than ever before.

My answer is always some variation of the same: “It’s an incredible time to be in crypto.”

The most resilient companies are born in this type of environment: Chainalysis (2014), MetaMask (2016), OpenSea (2017), Bison Trails (2018), and Uniswap (2018) just to name a few.

As investors focused on nascent technologies, it’s fascinating and gratifying to be able to learn from and support these brilliant founders. I wanted to share a few themes I’m especially eager to see evolve over the next year.

One of the biggest challenges within blockchain design is cryptoeconomic security, and more specifically scaling/aggregating network security. More nascent chains are being built with this in mind, ie: Cosmos + Interchain Security. However, innovation in Ethereum remains stifled at this level. Any middleware application built on top of Ethereum is responsible for bootstrapping its own security/trust network, a process that is extremely costly and resource-intensive. As investors in Obol*, which is bringing distributed validator technology (DVT) to Ethereum, we’re well aware of the necessity and challenges of building Ethereum middleware. Not only is building middleware expensive and time-consuming, but it also fragments trust/security within the ecosystem. And the issue of fragmented security only continues to persist/worsen as more applications are built.

Restaking addresses the issue of fragmented trust networks within Ethereum by introducing a generalized marketplace for decentralized trust. Restaking is a twist on the idea of merged mining whereby a PoW miner mines two blockchains at the same time and commits a block hash that works for both chains. This allows miners on the chain with a higher difficulty level to mine blocks on lower-difficulty chains at little cost. However, merged mining failed because there was no disincentive to merged miners. Restaking is powerful because it is built on top of PoS and introduces disincentives for bad restakers (slashing conditions), addressing the original issues of merged mining.

The pioneering team of restaking is EigenLayer, which offers a service that allows users to repurpose their staked $ETH that is already being used to secure Ethereum to secure other protocols. EigenLayer essentially enables a market for pooled security for Ethereum, allowing validators to adjust their risk/reward parameters across services.

The implications of restaking as a primitive are boundless, but just to start, restaking will fuel experimentation and innovation in Ethereum middleware, as developers can more freely focus resources on building products rather than bootstrapping security. A few of our favorite ideas that could leverage restaking: lightclient bridges, more secure oracles, and decentralized sequencers.

Despite Mark’s sincerest efforts, I think it is clear that we will not all be living within the confines of our Meta Quests any time soon. I do, however, think we are steadily moving towards a world in which the physical and digital are inextricably linked.

But as the initial hype around Fortnite concerts and “Baby Birkin”-type schemes cools down, brands/creators will have to think long and hard about the actual utility of their digital offerings beyond novelty. I’m particularly interested in the use of hardware combined with NFTs,

ie: NFC chip-embedded products → wallet creation/onboarding → NFT mint → exclusive rewards/user analytics

We’re already seeing parts of the infrastructure stack like Endstate* and IYK emerge and web3-native success stories like 9dcc, but this is only the beginning phase of exploring the design space for these new hybrid forms of commerce and engagement.

A few other digiphysical case studies I’m watching:

• Real World NFT Governance/Fandom: The go-to case study for the power of fans is K-pop, which is now a $5B industry. Modhaus is creating tripleS, the “first decentralized Kpop idol group.” Voting K-pop artists into stardom is not a new mechanism à la audition shows and music charts, but tripleS members are voted into the performance group through NFT governance with Polygon NFTs.

• Tokenized Asset Marketplaces: Seamlessly giving physical goods the powers of digital objects (liquidity, fractionalization, borrow/lend power, etc.) goes beyond tokenization, but also requires custody, supply chain logistics, etc. Marketplaces like Americana and 4K are working to make this as easy as using existing web2 marketplaces.

• Nike x RTFKT: Nike’s acquisition of RTFKT in 2021 was one of the first major signals that web2 brands’ commitment to entering web3 is here to stay. The collaboration dropped its AR Genesis Hoodie in July 2022, and has shown no signs of slowing down shipping. Many brands are looking to giants like Nike to see just how they leverage blockchain technology. Nike continues to make new moves in crypto, recently announcing the launch of .SWOOSH, its own hub for its digiphysical efforts moving forward.

The disastrous collapse of FTX was a wakeup call for the crypto industry, and a reminder that there are no shortcuts when it comes to security. After all, “not your keys, not your crypto.” However, onboarding the next million users into crypto, while also keeping those users’ funds secure is a daunting task. Today, users have to make a zero-sum choice: ease of use or sovereign control.

There are two ways to improve on the current UX of self-custody: smart contract wallets and MPC wallets. For sake of brevity, I’ll focus on smart contract wallets (more specifically, account abstraction) here.

Smart Contract Wallets

There are currently two types of accounts in Ethereum:

• Externally Owned Account (EOA): accounts that are controlled by private keys to a corresponding public address (these are most accounts used by wallets today)

• Smart Contract Wallet: accounts that are controlled by code, allowing for deployment of arbitrary logic

Account Abstraction is the process of abstracting away the differences between these accounts. More granularly, account abstraction brings programmability to transaction validity rules. A single contract account type for all the Ethereum accounts will empower developers to provide orders of magnitude better UX for users, enabling the following features:

• Custom Access Control: multisigs, sub-accounts, spending limits, allow/blocklists

• Session Keys (major for on-chain gaming)

• Social Recovery

• Multi-call Transactions

• Gas Sponsored Transactions

• Enhanced Privacy

The road to account abstraction has been a long one including multiple EIPs–EIP-86 (2017), EIP-2938 (2020), and most recently ERC-4337 (2021) which seeks to give standard EOA functionality to smart contract wallets without any consensus-level changes.

We’re still a ways away from a usable ERC-4337 native client wallet, but several teams have answered the call to build: Soul Wallet, StackUp, Candide, etc.

In the meantime, it’s worth noting that 1)  zkSync and StarkWare are among the first L2s to have native account abstraction support in their protocols. For example, Argent supports StarkWare and zkSync. 2) Hybrid solutions (AA wallet + MPC key management) are also entirely viable.

More resources on account abstraction (and perhaps a spicy counter-take on its limitations)

To quote Chris Dixon quoting ​​Clay Christensen (quote-ception?), “the next big thing will start out looking like a toy.” 2021/2022 was NFTs’ toy moment. We had our fun with 10K PFP collections and their copypastas (still $7B+ market cap, btw), and now the real work begins–finding real-world, scalable use cases for NFTs.

My bet is that NFTfi, hybrid NFT + DeFi mechanisms, will be the next major unlock for NFTs to tap into deeper liquidity and extend composability. 2022 saw $500M+ in cumulative NFT loan volume, laying the groundwork for an imminent explosion in NFTfi. Though NFT trading volume overall has plummeted, the economy is resilient–NFT borrow volume still persists significantly beyond levels during the 2021 bull market. And this is just the tip of the iceberg.

While I’m excited to see experimentation in marketplace token incentives and new financial instruments like NFT derivatives, the current NFTfi market still remains relatively small, mostly serving the long-tail. NFT liquidity is still rather low, driving lenders to give unfavorable loan terms, deterring people from entering these protocols all-together.

In order for NFTs to become their own established asset class, core pieces of infrastructure that unlock deeper liquidity will need to be refined including NFT AMMs like Sudoswap and liquidity aggregators like Reservoir*––not dissimilar from early innovations in DeFi. Demand for NFTfi will also surge as NFT utility expands beyond PFPs to other use cases such as in-game assets, real-world assets, brand loyalty passes, etc. I’m especially eager to see the NFT pricing issue get solved. NFT pricing historically has been incredibly obscure, relying largely on floor price (lowest buy price). Floor price is a poor metric, as it reduces the value of rarity/desirability within a collection, and is also susceptible to manipulation. Upshot, Abacus, and Waterfall are just a few of the laser-sharp teams working on this.

These are just a few examples of the countless number of innovations being built in crypto excluding some other heavy-hitter topics the Archetype team is also thinking about such as zero-knowledge roll-ups, next-generation DAOs, cross-chain interoperability, and more.

I’m expecting to be extremely validated and equally humbled this year, but I’m excited to be strapped in along for the ride.

-

Whether you’re noodling on an early idea or actively building with a team, I'd love to meet you––online or in NYC where Archetype is headquartered. You can reach me at katie@archetype.fund or on Twitter @katiewav.

Thank you to Nick, Ash, Benji, Edgar, and Sean for thoughtful comments and feedback.

*denotes Archetype portfolio company

Working in crypto has always garnered a lot of intrigue (and sometimes skepticism) from the people around me, but in the aftermath of some of the most disastrous crypto headlines in recent history, I’ve been fielding more questions than ever before.

My answer is always some variation of the same: “It’s an incredible time to be in crypto.”

The most resilient companies are born in this type of environment: Chainalysis (2014), MetaMask (2016), OpenSea (2017), Bison Trails (2018), and Uniswap (2018) just to name a few.

As investors focused on nascent technologies, it’s incredibly fascinating and gratifying to be able to learn from and support these brilliant founders. I wanted to share a few themes I’m especially eager to see evolve over the next year.

One of the biggest challenges within blockchain design is cryptoeconomic security, and more specifically scaling/aggregating network security. More nascent chains are being built with this in mind, ie: Cosmos + Interchain Security. However, innovation in Ethereum remains stifled at this level. Any middleware application built on top of Ethereum is responsible for bootstrapping its own security/trust network, a process that is extremely costly and resource-intensive. As investors in Obol*, which is bringing distributed validator technology (DVT) to Ethereum, we’re well aware of the necessity and challenges of building Ethereum middleware. Not only is building middleware expensive and time-consuming, but it also fragments trust/security within the ecosystem. And the issue of fragmented security only continues to persist/worsen as more applications are built.

Restaking addresses the issue of fragmented trust networks within Ethereum by introducing a generalized marketplace for decentralized trust. Restaking is a twist on the idea of merged mining whereby a PoW miner mines two blockchains at the same time and commits a block hash that works for both chains. This allows miners on the chain with a higher difficulty level to mine blocks on lower-difficulty chains at little cost. However, merged mining failed because there was no disincentive to merged miners. Restaking is powerful because it is built on top of PoS and introduces disincentives for bad restakers (slashing conditions), addressing the original issues of merged mining.

The pioneering team of restaking is EigenLayer, which offers a service that allows users to repurpose their staked $ETH that is already being used to secure Ethereum to secure other protocols. EigenLayer essentially enables a market for pooled security for Ethereum, allowing validators to adjust their risk/reward parameters across services.

The implications of restaking as a primitive are boundless, but just to start, restaking will fuel experimentation and innovation in Ethereum middleware, as developers can more freely focus resources on building products rather than bootstrapping security. A few of our favorite ideas that could leverage restaking: lightclient bridges, more secure oracles, and decentralized sequencers.

Despite Mark’s sincerest efforts, I think it is clear that we will not all be living within the confines of our Meta Quests any time soon. I do, however, think we are steadily moving towards a world in which the physical and digital are inextricably linked.

But as the initial hype around Fortnite concerts and “Baby Birkin”-type schemes cools down, brands/creators will have to think long and hard about the actual utility of their digital offerings beyond novelty. I’m particularly interested in the use of hardware combined with NFTs,

ie: NFC chip-embedded products → wallet creation/onboarding → NFT mint → exclusive rewards/user analytics

We’re already seeing parts of the infrastructure stack like Endstate* and IYK emerge and web3-native success stories like 9dcc, but this is only the beginning phase of exploring the design space for these new hybrid forms of commerce and engagement.

A few other digiphysical case studies I’m watching:

• Real World NFT Governance/Fandom: The go-to case study for the power of fans is K-pop, which is now a multi-billion dollar industry. Modhaus is creating tripleS, the “first decentralized Kpop idol group.” Voting K-pop artists into stardom is not a new mechanism à la audition shows and music charts, but tripleS members are voted into the performance group through NFT governance with Polygon NFTs.

• Tokenized Asset Marketplaces: Seamlessly giving physical goods the powers of digital objects (liquidity, fractionalization, borrow/lend power, etc.) goes beyond tokenization, but also requires custody, supply chain logistics, etc. Marketplaces like Americana and 4K are working to make this as easy as using existing web2 marketplaces.

• Nike x RTFKT: Nike’s acquisition of RTFKT in 2021 was one of the first major signals that web2 brands’ commitment to entering web3 is here to stay. The collaboration dropped its AR Genesis Hoodie in July 2022, and has shown no signs of slowing down shipping. Many brands are looking to giants like Nike to see just how they leverage blockchain technology. Nike continues to make new moves in crypto, recently announcing the launch of .SWOOSH, its own hub for its digiphysical efforts moving forward.

The disastrous collapse of FTX was a wakeup call for the crypto industry, and a reminder that there are no shortcuts when it comes to security. After all, “not your keys, not your crypto.” However, onboarding the next million users into crypto, while also keeping those users’ funds secure is a daunting task. Today, users have to make a zero-sum choice: ease of use or sovereign control.

There are two ways to improve on the current UX of self-custody: smart contract wallets and MPC wallets. For sake of brevity, I’ll focus on smart contract wallets (more specifically, account abstraction) here.

Smart Contract Wallets

There are currently two types of accounts in Ethereum:

• Externally Owned Account (EOA): accounts that are controlled by private keys to a corresponding public address (these are most accounts used by wallets today)

• Smart Contract Wallet: accounts that are controlled by code, allowing for deployment of arbitrary logic

Account Abstraction is the process of abstracting away the differences between these accounts. More granularly, account abstraction brings programmability to transaction validity rules. A single contract account type for all the Ethereum accounts will empower developers to provide orders of magnitude better UX for users, enabling the following features:

• Custom Access Control: multisigs, sub-accounts, spending limits, allow/blocklists

• Session Keys (major for on-chain gaming)

• Social Recovery

• Multi-call Transactions

• Gas Sponsored Transactions

• Enhanced Privacy

The road to account abstraction has been a long one including multiple EIPs–EIP-86 (2017), EIP-2938 (2020), and most recently ERC-4337 (2021) which seeks to give standard EOA functionality to smart contract wallets without any consensus-level changes.

We’re still a ways away from a usable ERC-4337 native client wallet, but several teams have answered the call to build: Soul Wallet, StackUp, Candide, etc.

In the meantime, it’s worth noting that 1)  zkSync and StarkWare are among the first L2s to have native account abstraction support in their protocols. For example, Argent supports StarkWare and zkSync. 2) Hybrid solutions (AA wallet + MPC key management) are also entirely viable.

More resources on account abstraction (and perhaps a spicy counter-take on its limitations)

To quote Chris Dixon quoting ​​Clay Christensen (quote-ception?), “the next big thing will start out looking like a toy.” 2021/2022 was NFTs’ toy moment. We had our fun with 10K PFP collections and their copypastas (still $7B+ market cap, btw), and now the real work begins–finding real-world, scalable use cases for NFTs.

My bet is that NFTfi, hybrid NFT + DeFi mechanisms, will be the next major unlock for NFTs to tap into deeper liquidity and extend composability. 2022 saw $500M+ in cumulative NFT loan volume, laying the groundwork for an imminent explosion in NFTfi. Though NFT trading volume overall has plummeted, the economy is resilient–NFT borrow volume still persists significantly beyond levels during the 2021 bull market. And this is just the tip of the iceberg.

While I’m excited to see experimentation in new financial instruments like NFT derivatives and marketplace token incentives, the current NFTfi market still remains relatively small, mostly serving the long-tail. NFT liquidity is still rather low, driving lenders to give unfavorable loan terms, deterring people from entering these protocols all-together.

In order for NFTs to become their own established asset class, core pieces of infrastructure that unlock deeper liquidity will need to be refined including NFT AMMs like Sudoswap and liquidity aggregators like Reservoir*––not dissimilar from early innovations in DeFi. Demand for NFTfi will also surge as NFT utility expands beyond PFPs to other use cases such as in-game assets, real-world assets, brand loyalty passes, etc. I’m especially eager to see the NFT pricing issue get solved. NFT pricing historically has been incredibly obscure, relying largely on floor price (lowest buy price). Floor price is a poor metric, as it reduces the value of rarity/desirability within a collection, and is also susceptible to manipulation. Upshot, Abacus, and Waterfall are a few of the laser-sharp teams working on this.

These are just a few examples of the countless number of innovations being built in crypto excluding some other heavy-hitter topics the Archetype team is also thinking about such as zero-knowledge roll-ups, next-generation DAOs, cross-chain interoperability, and more.

I’m expecting to be extremely validated and equally humbled this year, but I’m excited to be strapped in along for the ride.

*denotes Archetype portfolio company

—

Whether you’re noodling on an early idea or actively building with a team, I'd love to meet you––online or in NYC where Archetype is headquartered. You can reach me at katie@archetype.fund or on Twitter @katiewav.

Thank you to Nick, Ash, Benji, Edgar, and Sean for thoughtful comments and feedback.

The original promise of technology, and more specifically of the internet, is rooted in decentralization––open networks and the transparent dissemination of information. However, in the rapid emergence of a paradigm in which “software is eating the world,” we have largely ceded the stewardship of software to institutions that seek to instead consolidate this power.

From Josh Stark:

“The problem with software eating the world, is that behind most software is an institution. The internet we have reflects the shortcomings of institutional hardness. It is increasingly balkanized, carved up along nation-state boundaries. It is a fragile and unstable foundation, as the individual companies that control it rise and fall. And most of it is owned by a handful of companies, controlled by a small group of people, who live in one country.”

The promise of crypto, and blockchain technology at-large, is that it gives us tools to compete with traditional institutions, enabling us to coordinate anyone, anywhere, anonymously. This vision is deeply embedded in the history and culture of crypto. The Cypherpunk movement was ushered in by a group of just three Bay Area computer scientists, a mailing list, and a core conviction: the importance of a sovereign internet. They managed to both embrace the promise of the internet, while also anticipating the ways in which its power could be co-opted by centralized institutions.

Crypto’s use cases have evolved far beyond the original vision of the Cypherpunks, but its values remain strong to this day: transparent, permissionless, composable, community-owned.

Throughout its multiple cycles, crypto has driven the invention of truly groundbreaking technologies from electronic cash, to programmable blockchains, to NFTs, to DAOs, etc. But while every cycle sees new innovation, we also witness more institutions entering the space with the hopes of using the technology to replicate old structures that consolidate power. This is all to express that crypto, and technology in general, is not inherently “good” or “bad.” Instead, we must view it as a tool we may use to accelerate a shared vision of a just future.

For example, I’d like to a see a future that enables the following:

• Communities to self-organize and govern

• Communities to self-custody, coordinate, and deploy capital

• Users to own and selectively share/their identity/data

• Strong rails for cross-border payments/financial infrastructure

The exhilarating part about the world of crypto is that it is rapidly evolving every day. Don’t forget, the ERC-721 standard didn’t even exist until fairly recently. Crypto is able to progress so quickly because of its level of talent and its open-source culture. History tells us time and time again that the future is forged by builders. Founders, not blockchains, are architecting our collective digital future.

Like with the Cypherpunks, the future will be paved by small groups of folks with high conviction and a clear vision for what they want to see in the world. It’s true that in the past these small groups have often been elite and homogenous, but blockchain rails give us hope. The infrastructure to empower diverse, distributed communities of builders is stronger than ever before.

At Archetype, we are committed to surfacing and supporting founders with unique insights and perspectives on the future of crypto. This has been at the core of Ash’s investing practice since 2015, having been an early investor in now pillar companies in crypto and blockchain including Chainalysis, Balancer, Dapper Labs/FLOW, Bison Trails, and many more.

When I think of what kind of investor I’d like to be, the type of investor I believe that Ash is, I think of the philosophy of record producer, Rick Rubin––when he works with an artist, the goal is to not inject any of himself into the music or to leave any imprint, but to catalyze and nurture the artist so that they may create work that is the most true to themselves.

When I was at Coinbase Ventures, I had the incredible opportunity to see hundreds of companies and to have a high-level pulse of the ecosystem at large, but I was missing the opportunity to work side-by-side with founders. Now, I’m excited to narrow in, dive deep, and work on the ground with teams to accelerate their visions of the decentralized future.

Whether you’re noodling on an early idea or actively building with a team, I'd love to meet you––online or in NYC where Archetype is headquartered. You can reach me at katie@archetype.fund or on Twitter @katiewav.

—

Giving thanks:

I have always been, and will always be, people-first. Thank you to the communities, founders, friends, and mentors who have brought me this far in my crypto journey: KERNEL, Friends with Benefits, Sean Thielen-Esparza, Tina He, Jon Yan, Carl Cortright, Katherine Wu, Nick Kim, Ryan Yi, Steven Willinger, Jason Yeh, Brian Cho, and more.

More of my writing on crypto: katiewav.mirror.xyz

Writing that has been instrumental to how I think about crypto:

Atoms, Institutions, Blockchains by Josh Stark

Hyperstructures by Jacob Horne

Progressive Decentralization: A Playbook for Building Crypto Applications by Jesse Walden

In 2021, more than 50 million Americans left their jobs.

It has become painstakingly clear that our current models of work are not fulfilling or effective for the modern-day laborer. In the past, such rigid structures may have been justifiable – corporate structures reduced the friction and transaction costs of contracting individual work on the free market. However, while such sentiment may have been plausible in the early 20th century, new technology has and will continue to transform how we think about work and coordination (ie: cloud computing!).

Crypto is a prime example of a technology accelerating the future of work. Crypto has already proven to be powerful tool for finance, but it also has allowed the creation of new tools for governance and coordination:

• Private/pseudonymous identity and credentialing (DID) (ie: Sismo, Disco)

• Revolutionary justice systems and algorithmic dispute resolution (Kleros)

• Transparency of cash flow and other on-chain activity (Gnosis, Llama, Etherscan)

etc…

Decentralized Autonomous Organizations (DAOs) promise to bring these tools into practice, creating a new paradigm of coordination and making it possible for mass mobilization of resources beyond physical constraints. The promise is alluring –– according to DeepDAO, there are already almost 2M holders of DAO governance tokens and 500k+ active voters and proposal makers in DAOs.

Despite its viral emergence, the discourse around the definition of a DAO is fragmented. And to be clear, that’s okay. DAOs will exist for different purposes, work toward different goals, and operate within different parameters.

However, today’s DAOs do often coalesce around two key primitives:

• A token: participation/governance

• A multi-sig wallet: a shared resource/treasury

And what do these two tools have in common –– cryptoeconomics.

Nathan Schneider wrote an incredible article on the limitations of cryptoeconomic governance, and I generally agree with Schneider that, at least in their current, mass-adopted form, DAOs will permit the radical financialization of everyday interactions. If the minimum viable DAO is a group with a shared crypto wallet or a token on the free market, it’s difficult to imagine a world in which finance is not at the heart of a DAO. And what would it mean for the future if the minimum viable DAO relies entirely on financialization?

In response to Schneider’s article, Vitalik wrote his own response where he develops the following thesis: “finance is the absence of collusion prevention”:

“Finance can be viewed as a set of patterns that naturally emerge in many kinds of systems that do not attempt to prevent collusion. Any system which claims to be non-finance, but does not actually make an effort to prevent collusion, will eventually acquire the characteristics of finance, if not something worse.”

In non-blockchain systems or “‘real life’” to use Vitalik’s turn of phrase, “[efforts] to prevent collusion” mean existing guardrails (usually legal) like shareholder regulation. Obviously, these existing guardrails are liable to corruption and often are corrupted.

The promise of blockchain coordination tools is that they enable technically embedded guardrails and structures that can defend systems against collusion and resist pressure from economic actors.

These blockchain guardrails may include the tools mentioned at the very beginning of this piece or even entirely bespoke systems––of which many already exist (MakerDAO, Yearn V2, Moloch, MetaCartel, etc.)

However, while the opportunity for innovation exists, DAOs, in their current state, often don’t adopt blockchain tools other than the financial primitives, leaving them largely open to speculation and the corruption of bad actors, perhaps even similar to those we often see in the traditional corporation.

While the fear may be premature, I find it far too easy to compare the current standard implementation of a DAO to that of a corporation (and I hear this comparison made often in conversation).

Generally speaking, purchasing a DAO governance token is similar to purchasing the share of a company. The difference is three-fold:

1. Speed: In a corporation, you’d only be able to vote on key issues once a year during the AGM versus in a DAO, you can vote/participate in governance decisions on a much more frequent cadence. This also means bad actors with power can be held accountable much more easily in a DAO than a company.

2. Participation: Unlike in a corporation filled with legal jargon and practice, it’s much more common for any DAO member to be able to create a governance proposal and get it passed. A single DAO member’s vote usually carries much more weight than that of a single shareholder in a company, given sheer size of tokenholder vs shareholder bases (this could stand to change depending on trends in token allocation, distribution and design: example case study). Innovations in governance design/blockchain mechanisms create opportunity for fluidity in how votes are weighed/valued.

3. Execution: Depending on the design of the DAO and the inclusion of blockchain mechanisms, governance decisions can be executed autonomously/trustlessly in DAOs versus in traditional corporations.

In this case, the implementation of a token does little to effectively build accountable guardrails into the organization. Speed and accessibility in the governance process are strong benefits to a DAO, but many of the other current benefits occur simply because it’s easier to buy into a DAO than a company and tokenholder bases are typically smaller –– both meaning the DAO is inherently more democratized. However, this could easily change if/as DAOs grow expand, teams distribute tokens to more strongly benefit insiders, or even if DAOs collude in meta-governance. Classic narratives of corporate collusion and bad actors may re-emerge, as we’ve seen already occur in several cases (ie: Olympus, Toucan Protocol, Build Finance).

Some may argue that collusion or bribery in crypto is perhaps a feature, not a bug. [REDACTED] CARTEL, a project with an ambition to become a meta-governance by aggregating assets with governance rights, recently launched The Hidden Hand Marketplace. The platform provides “bribery-marketplace-as-a-service” for DAOs, enabling protocols to “purchase” certain governance decisions by buying their native tokens. On the one hand, the financialization of rights unleashes a new era of D2D composability, where the highest bidder at the table attains their rights to influence a project. On the other hand, the financialization makes the already convoluted value chain of the ecosystem more difficult to newcomers and contributors looking to earn their way to influence. Early conversations around labor unions emerge, yet equally effective mechanisms have yet to be created to provide leverage for contributors, especially late-comers. Such imbalance of influence could lead to consolidation of existing power on the one hand and perverse incentives to join versus starting a DAO on the other.

My goal is not to criticize cryptoeconomics at its core or to curtail the emergence of DAOs. In fact, we have already seen numerous examples of how these cryptoeconomic tools have already catalyzed a transformation in the future of coordination (ie: ConstitutionDAO's bid for the US Constitution, The Krause House’s bid for an NBA team, etc.)

However, I do urge the space to think critically about what frameworks and tools still have yet to be commonly adopted/explored that enable subsets of coordination such as modularity, arbitration, privacy/pseudonymity, credentialing, etc. Financialization itself isn’t sufficient to steward long-term value, and financial primitives are far from sufficient in fulfilling the full potential of DAOs. And as we unlock those tools, a true revolution in the future of work will emerge.

In his seminal 1937 essay, The Nature of the Firm, economist Ronald Coase explained why companies exist—to reduce the friction and transaction costs of contracting individual work on the free market. While perhaps a truth of the past, traditional corporations with bloated management and poor incentives for employees and users no longer effectively create value. Rather than focusing on practicing the craft at hand, tremendous energy is wasted optimizing for zero-sum games of equity vesting, salary negotiation, and organizational politics.

We've seen a collective stirring around redefining work through the creator economy and platform economy, which offer individuals the flexibility and autonomy to discover demand for their gifts. The last generation of innovation in platforms accelerated the inevitable rise of a globally distributed workforce. Companies now recognize that, without a steep increase in transaction or bureaucracy costs, they can flexibly scale up or down throughput through a new class of labor—freelancers.

On the one hand, the silhouette of a self-deterministic, dream-bearing, free-roaming, modern-age worker emerges as an aspiration. Ironically, these workers are also often the most alienated from the fruits of their labor. The dichotomy between 'us' and 'them' is stark. The product sees an absence of credit or attribution to freelancers at an organizational level. While their work may have persisted in sustaining the essence of a product, their very own identity as a contributor is abstracted away by the company.

Many recognize this stark reality despite the compelling narratives around the future of work. While freelancing offers the flexibility in individual lifestyle, individuals may not feel incentivized to invest in the long-term success of the collective. Traditional companies, with rigid hierarchies but abundant resources, make competing for attention internally exhausting for all participants.

It’s clear that the most thorny problems facing humanity today—climate crisis, cybersecurity, income inequality to name a few—will not be solved by one corporation or one individual. These problems need to be addressed with the scale and efficiency of a corporation, without compromising on individual autonomy, creativity, and ownership. They require fluid and multidisciplinary collaboration that transcends the borders of institutions, from corporations to nation-states.

Pioneering collectives have persisted throughout history, and we are seeing a new form also begin to emerge. These groups  are congregating online in forums, on Twitter, in Telegram groups, mobilizing resources and exchanging information.

The viral emergence of DAOs is simply a symptom of the demand. We desire to become a 'core contributor' to a historical moment. As collective participants and owners, we get a taste of long-lost idealism, community, and optimism since COVID has taken hold of our daily rituals. PleasrDAO's bid for Snowden’s Stay Free. ConstitutionDAO's bid for the US Constitution. The Kraus House’s bid for an NBA team. Group bids are fleeting moments of glory. They demonstrate how with a clearly defined goal and a well-defined action — contributing capital — a group of people can be coordinated in record speed.

It's become clear, however, that pure exuberance can't last forever. Without guardrails on how to further their impact and continuously bring their unique value to a collective, contributors can feel lost, unrecognized, and eventually leave.  In the absence of a management team or an HR department to delineate the paths of a contributor, how can we incentivize everyone in a network of communities to discover where they can contribute the most value? How can we empower each other to work flexibly and autonomously, while still fostering a sense of security, belonging, and identity?

The promise of DAOs lies in self-governance. With the appropriate tools and mechanics, contributors can onboard, coordinate, reward one another, rather than relying on one single point of failure.  In absence of such infrastructure, decisions will continue to be made arbitrarily and consensus cannot scale across the network.

Contributors must be able to port their body of work across organizations. In the current labor system, workers are made legible by the institutions they belong to. A worker's entire identity—their work, reputation, relationships—exists in the blackbox of an insular permission-controlled database. Once a worker leaves the organization, their identity is effectively erased and they must rebuild and retell their narrative within the context of another institution. Web3 allows contributors to have ownership over their body of work while their entire system of record exists on-chain, providing the context needed for contributors’ reputation to become legible to multiple communities. Contributors can even thrive through pseudonymous accounts that ensure privacy.

Contributions and credibility must be interoperable and fluid. To create a network of fluid organizations, we can no longer rely on traditional enterprise software with rigid control permissions and a centralized database. In an interoperable world, a contributor's work to one community can be leveraged in another, as on-chain data and smart contracts are largely interoperable by default. Reputation is another currency coveted within a traditional corporation, and one that is often lost in the realm of purely individualized work. There is no standard for inter-organizational reputation. The concept of "co-signs" or "endorsements" aren't new but lack legitimacy across different communities. Infrastructure that is designed around interoperability will allow stronger inter-network cooperability and fluidity to emerge.

Power and authority in the contributor economy must be emergent, not assigned. In traditional systems, compensation and authority are explicitly defined and pre-negotiated (titles, roles, and compensation), even though trust and responsibility are implicitly earned. Token mechanisms create infinite possibilities for how credit can now be attributed granularly to all project contributors. For example, imagine your contribution is assessed on multiple programmable vectors rather than on a say of a single person or single metric. Tokens also enable stronger value allocation among contributors, as votes of high trust or appreciation. Creating more multidimensional opportunities for power and authority to flow between individuals and communities will enable a higher degree of overall decentralization.

Web3 has opened the gate of opportunity to reexamine the building blocks of an organization from the bottom-up,  to assess the appropriate role of technology in sociopolitical progress, and to question the relationships between capital, contribution, reputation, and power. Understanding these relationships will pave the pathway for a fundamental redistribution of value, rather than relying on normative presumptions of  'this is how the world works.’  The  future of work is coming, and we are all its contributors.

The future of work is coming, and we are all its contributors.

If these are questions you’d also like to explore, we invite you to become a contributor to the Station protocol or to participate in our research efforts through Newstand, Station’s publication focused on exploring the possibility of work in an era of hyper connectivity and fluidity. Station Newstand is open 24/7 for submissions and experimentations from contributors around the pluriverse.

Special thanks to Mind, xuannü, Alex, David, Jasmine, and Humphrey for contributing to the edits.

But I also fear that we have hastily declared absolute decentralization** as the panacea to the plagues of Web2. I don’t aim to decry decentralization, but instead to explore hybrid paths forward.

In KERNEL, we call this style of thinking quantum thought:

“Rather than using dualities like 'decentralization good, centralization bad'; or 'DeFi is innovative, fiat is boring', […] recognize that there is no good without evil; no attraction without repulsion, no North with South, no up without down. We could describe this as quantum thought - being able to contemplate both 0 and 1 simultaneously, and the spectrum of probability between.”

Let’s take decentralization and centralization as our 0 and 1.

In their current iteration, DAOs are conceptually marketed as fully decentralized, self-serve organizations.

To use my own journey as an example of how that manifests, the first time I joined a DAO Discord, I was elated to see hundreds of people gathered together in cyberspace to explore what’s possible in a decentralized future. That elation quickly transformed into overwhelm and a nagging question: “What am I supposed to do now?” I scoured the server for direction, but felt extremely lost and disappointed. When there are unclear paths to contribution, participation becomes bleak. It may even also centralize power in unintended ways.

A (simplified!) example of a fully decentralized and participatory governance model:

Let’s say that in your local community, you are 100% in charge of your own decision-making, but it’s your job to stay informed by attending town halls. That’s great, but who will be able to go to all the town halls? Probably not folks who have to work 12-hour shifts or be a full-time caretaker, etc., etc. Those who can actually participate are only those who have the privilege of time, resources, etc. In this case, I would make the case that a representative democracy is much more effective than a participatory one, though representative democracy has its own issues (More on this: How Blue Cities Became So Outrageously Unaffordable , The Tyranny of Structurelessness).

These problems are not lost on DAO organizers/web3 leaders. Many have talked about the drawbacks of decentralization in this regard:

“The success of Web 3 governance models doesn’t seem to lie in a thousand people making a thousand decisions, but rather a thousand people electing a small group of leaders to make decisions for them, and supporting those leaders through usage, distribution, and feedback.” - Alex Zhang, Friends with Benefits

“Failing to formalize real community participation can land projects in an uncanny valley of decentralization theater. A symptom of being caught here is an apathetic community with low participation rates, and a heavy dependency on founding teams. In this situation, formalizing control (e.g. through delegation) may be a better path to building trust, whereas hiding under the pretense of decentralization is a quick way to undermine it.” - Jesse Walden, Variant Fund

In the case of strong centralization (Web2), the solution to these issues would be to create a hierarchy analogous to the C-suite of a traditional company, where leaders are responsible to guide users, but are also padded into legacy positions with the ability to hoard power and wealth, etc., etc. with little intervention (we see these manifest in companies like Facebook, Apple, etc.).

Okay so if absolute decentralization and centralization are both "bad," then how might we move forward?

The answer is unclear and many incredible folks in the DAO community are working on solutions for this, but I propose the following first step: We should not hide under the pretense of decentralization.

Frankly, there is currently inadequate tooling to create effective, fully autonomous DAOs. Consequentially, I'd argue DAOs need strong central leadership right now. DAO theory looks to the co-op and open source models for inspiration, and in both cases there are precedents for leadership (More on this: A Prehistory of DAOs). To preach DAOs as fully autonomous in their current stages is, candidly, a disastrous mismanagement of contributor expectations.

The difference then, between a fully decentralized model and the current Web2 governance, is that DAOs should have early strong leadership but be transparent in building processes and provide material evidence that the team is building devices for progressive decentralization.

These devices may look like robust documentation, strong self-serve onboarding, high-reward bounties, constant voting proposals, token airdrops, other generous and transparent compensation mechanisms, etc. These tools will give members an actionable sense of ownership of the DAO (incentivizing participation), and ensure a stronger transfer of responsibility to community members later when DAO operations are sustainable, having retained enough tokens to benefit from fees and growth.

In sum, there needs to be hard conversations about what it means to start or join a DAO. I believe that rather than rallying around a marketable word like "decentralization," we should first investigate what we owe each other as DAO netizens. This means managing expectations and aligning all contributors to understand the merits of different models of decentralization. Only then will we build a sustainable model for DAOs, and a stronger Web3.

**a quick note: I’m using a layperson’s definition of decentralization to describe the absence of any central roles/hierarchies in an organization; I definitely admit that decentralization as a formal property is much more nuanced, but would argue that it may be unclear (fairly) to someone new to web3/DAOs.

Prescient source and inspiration: Progressive Decentralization: A Playbook for Building Crypto Applications