Von Fat Protocols bis zur Kettenabstraktion: Wie wird die Anwendungsschicht die Werterfassung in Kryptowährungen umgestalten?

Originalautor: Adrian

Originalübersetzung: TechFlow

Alt L1s – speed up again?

In each crypto cycle, the most successful investments tend to be early bets on new base layer infrastructure primitives (such as PoW, smart contracts, PoS, high throughput, modularity, etc.). If you look at the top 25 assets on Coingecko, there are only two tokens that are not native tokens of the L1 blockchain (excluding anchored assets), which are Uniswap and Shiba Inu. Joel Monegro first explained this phenomenon in 2016, when he proposed the Fat Protocol Theory . The theory points out that the biggest difference between Web3 and Web2 in value accumulation is that the value accumulated by the crypto base layer exceeds the total value obtained by the applications built on it. This value comes from:

1. Blockchain provides a shared data layer for settling transactions, a structure that promotes positive-sum competition and supports permissionless composability.

2. The positive cycle driven by token appreciation is: token appreciation > attracting speculators to participate > converting speculators into actual users > increasing users and token appreciation attract more developers and users, forming an ever-expanding ecosystem.

The original fat protocol theory

By 2024, the original fat protocol theory has been through multiple industry debates and is being challenged as a result of tectonic changes in industry dynamics:

1. Commoditization of block space – As infrastructure premiums are realized, the emergence of successful alternative L1s (such as Solana in terms of high throughput and Celestia in terms of data availability) makes them category definers, attracting builders and investors to participate in alternative L1 investments in each cycle. In each cycle, there are new blockchains that excite investors and users because of their differentiated characteristics, but they may eventually become ghost chains (such as Cardano), that is, blockchains that lack actual user and application support. Overall, this has led to an excess of block space in the market, but a lack of sufficient users and applications to utilize these resources.

2. Modularization of the base layer – As more and more specialized modular components emerge, it becomes increasingly complex to define what the “base layer” is, not to mention how to decompose the value accumulated at each layer of the stack. However, I think what is clear in this shift is that:

• In a modular blockchain, value is dispersed across the entire stack. For an individual component (like Celestia) to be valued above the integrated base layer, that component (like Data Availability DA) must become the most valuable part of the stack, and the “applications” (modular blockchains) built on it need to generate more usage and fees than the integrated system;

• Competition among modular solutions drives more economical execution and data availability solutions, further reducing costs for users.

3. Towards a chain abstraction future – Modularity has led to fragmentation of the ecosystem, resulting in a cumbersome user experience. For developers, this means facing too many choices to decide where to deploy applications; for users, this means jumping from application A on chain X to application B on chain Y requires overcoming many obstacles. Fortunately, many smart people have realized this problem and are working hard to build a future where users do not need to understand the blockchain running behind them when interacting with crypto applications. This vision is called chain abstraction and is a theory that excites me. The question now is, how will value accumulate in the chain abstract future?

I believe that crypto applications are the main beneficiaries of the shift in the way infrastructure is built. In particular, the intent-centric trading supply chain, as well as order flow exclusivity and intangible assets such as user experience and brand , will increasingly become competitive barriers for these applications, allowing them to achieve profitability more effectively than existing models.

Order Flow Exclusivity

Since Ethereum completed the merger and introduced Flashbots and MEV-Boost, its MEV (maximum extractable value) landscape has changed significantly. The dark forest once dominated by searchers has evolved into a commoditized order flow market. In this market, the current MEV supply chain is mainly dominated by validators, who receive about 90% of the generated MEV in the form of bids for each participant in the supply chain.

Ethereum’s MEV Supply Chain

Validators capture the majority of extractable value, which has displeased many participants in the trading supply chain. Users want to be compensated for generating order flow, decentralized applications (dapps) want to retain the value brought by user order flow, and searchers and builders want to increase profits. Therefore, participants eager to capture value have begun to try a variety of strategies to extract excess returns, one of which is the integration of searchers and builders – the core of this strategy is that higher profit margins can be achieved by increasing the certainty of inclusion of searcher packages. A large amount of data and literature shows that in a highly competitive market, exclusivity is the key to value capture, and applications with the most valuable traffic will have pricing power.

This phenomenon is also seen in retail stock trading through brokers such as Robinhood, which maintains “zero-fee” trading by selling order flow to market makers and profits by capturing kickbacks. Market makers such as Citadel are willing to pay fees for this order flow because they can profit from arbitrage and information asymmetry.

In addition, more and more transactions are conducted through private memory pools, which have reached an all-time high of 30% on Ethereum. Decentralized applications (dapps) realize that the value of user order flow is being extracted and leaked into the MEV supply chain, and private transactions provide more opportunities for customization and monetization around highly sticky user flows.

(Chart source: X )

As we move toward a future where chains are abstracted, I expect this trend to continue. Under an intent-centric execution model, the trading supply chain is likely to become more fragmented, with applications constraining their order flow to the network of solvers that can provide the most competitive execution, which will drive increased competition among solvers, driving down margins. However, I believe that the majority of value capture will move from the base layer (i.e., validators) to the user-facing layers, with middleware components that are valuable but have lower margins – that is, frontends and applications that can generate valuable order flow will have pricing power over searchers and solvers.

How to accumulate future value

We are already seeing this trend play out in some specific types of order flow that leverage application-specific ordering mechanisms, such as Oracle Extractable Value (OEV) auctions (e.g. Pyth, API 3, UMA Oval), which provide lending protocols with a way to recapture liquidation bids that would otherwise go to validators.

User Experience and Brand as Sustainable Moats

If we further analyze the sources of the 30% of private transactions mentioned earlier, we can find that most of them come from frontends such as Telegram bots, decentralized exchanges (Dexes), and wallets:

Segmentation of transaction origin via private memory pool

While cryptocurrency users are often considered to have short attention spans, we are finally seeing some level of user retention. Apps are demonstrating that brand and user experience can be powerful moats—

• Benutzererfahrung: Alternative front-ends introduce entirely new experiences, starting with connecting a wallet on a web app, which naturally attracts users who demand a specific experience. A good example is Telegram bots like Bananagun and bonkbot, which have generated over $150 million in fees and allow users to easily trade memes in Telegram chats.

• Brand: In the cryptocurrency space, brands that have established a good reputation can increase fees by gaining the trust of users. Swap functionality built into wallets, while known for high fees, is a successful business model because users are willing to pay for convenience. For example, Metamask’s swap functionality generates over $200 million in fees per year. Finally, Uniswap Lab’s front-end fee switch has netted $50 million since its launch. Transactions that interact with Uniswap Labs contracts through the unofficial front-end do not incur this fee, but their revenue is still increasing.

This suggests that the Lindy effect is just as present in applications, and perhaps even more pronounced than in infrastructure. Typically, the adoption of new technologies (including cryptocurrencies) follows a sort of S-curve, as we transition from early adopters to a wider mass audience — the next wave of users may be less tech-savvy and therefore less price-sensitive, allowing brands that are able to achieve critical mass to monetize in creative (or simple) ways.

The S Curve of Cryptocurrency

Abschluss

As someone who focuses primarily on infrastructure research and investment, this post is by no means intended to deny infrastructure’s place as an investable asset in crypto, but rather to encourage a shift in mindset when thinking about new types of infrastructure that can support the next generation of applications. These applications will serve users at the higher end of the S curve. New infrastructure needs to demonstrate entirely new use cases at the application level to attract attention. At the same time, there is already enough evidence at the application level that user ownership directly promotes sustainable business models for value accumulation. Unfortunately, we may have passed a stage where every new hot L1 project will bring exponential returns; however, those with significant differentiation may still deserve attention and value.

Instead, the “infrastructure” that I spend more time thinking about and understanding includes the following aspects:

• AI: This includes the AI Agent Economy, which automates and improves the end-user experience; compute and inference markets, which continuously optimize resource allocation; and verification technologies that extend the computing power of blockchain virtual machines.

• KUCHEN stack: Many of my previous points have suggested that we should move towards a future of chain abstraction, and there is still a lot of room for design choices in most components of the stack. As infrastructure supports chain abstraction, the design space for applications will naturally expand, which may make the boundary between applications and infrastructure less clear.

• DePIN: I have always believed that DePIN is a key real-world application of cryptocurrency, second only to stablecoins, and this view has not changed. DePIN takes advantage of the advantages of cryptocurrency: permissionless resource coordination, market launch, and decentralized ownership through incentive mechanisms. Although each network type still faces specific challenges, significant progress has been made in solving the cold start problem. I am very much looking forward to seeing founders with industry expertise use crypto technology to launch their products.

If you are working on a project related to the above, please feel free to contact me and I will be happy to discuss it with you. I also welcome any feedback or objections, because frankly, investing would be much simpler if I were completely wrong.

“The most exciting applications for the Ethereum blockchain may be ones we haven’t even thought of yet.” — Vitalik Buterin, 2014

This article is sourced from the internet: From fat protocols to chain abstraction, how will the application layer reshape crypto value capture?

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