Author: Shijiu Jun
Reviewer: 0xmiddle
Source: Content Guild – Investment Research
Introduction
Today, it has been over three years since the explosion of DeFi Summer, and more than half a year since the approval of the benchmark ETF for compliance. Has the situation changed?
Looking back, Ethereum’s smart contracts have enhanced the programmability of blockchain, expanding it from a single accounting function to an infrastructure that supports various applications. Among many tracks, there is no doubt that the decentralized migration of traditional finance is the most practical application scenario.
Let’s take a look at the DeFi TVL data from DeFiLlama. Currently, the TVL of DeFi applications has exceeded 80 billion USD. In recent years, many public chains have emerged, and even Ethereum’s L2 is diverting the space of Ethereum L1. However, Ethereum still securely locks more than half of the total DeFi assets on a single platform.
Image source: defillama.com/chains
The initial ambition of DeFi was to disrupt traditional financial systems’ business models in lending, payments, insurance, etc., allowing users to complete these operations without relying on banks or other traditional financial institutions. However, the TVL of DeFi has, in fact, stagnated for a long time without a breakthrough in scale.
Most opinions suggest that DeFi is limited by issues such as the performance and cost of the Ethereum network, making it difficult to achieve large-scale applications and complex financial scenarios. However, the DeFi ecosystems on various L2s and high-performance new public chains have not brought about a breakthrough in DeFi scale; instead, they have led to liquidity fragmentation and decreased interoperability. Ethereum still retains the most complete DeFi ecosystem and the most sufficient interoperability, remaining the preferred platform for deploying DeFi projects.
Today, a new trend is emerging: a new DeFi paradigm based on AO—AgentFi. This innovation is breaking the limitations of traditional DeFi.
AO, based on the Arweave storage layer, has built a computing layer that supports parallel running processes, solving scalability issues and achieving almost limitless scalability. The combination of AO and Arweave is an implementation based on SCP (Storage-based Consensus Paradigm).
On AO, smart contracts exist in the form of processes. By freeing themselves from performance constraints, anyone can run their own processes to act on their financial behaviors, with consensus managed by Arweave’s storage layer. This is the foundation of AgentFi.
Will this new form of DeFi, AgentFi, replace traditional DeFi and become the new mainstream form of DeFi? Let me elaborate.
Limitations of Traditional DeFi
In traditional blockchain architecture, block space is designed as a scarce resource, and both users and applications must compete to obtain this resource. When the network is congested, people have to pay more costs to compete for block space, which is the fundamental reason for performance limitations. Ethereum’s performance limitations have become evident, with only around 30 TPS[1], which is quite inadequate. During peak periods, gas fees often surge by dozens of times, and people have become accustomed to this. In fact, L2 and most high-performance public chains also face performance ceilings; while their ceilings may be higher, accommodating the scale of traditional financial business remains challenging.
To save on performance usage and reduce gas costs for users, traditional DeFi has been designed to use a single smart contract to manage business assets and run financial operations. Since both funds and business logic are managed by a unified contract, it becomes difficult to achieve true diversification and personalized business operations. Although this design simplifies management processes and ensures consistency, it also deprives users of autonomy in business logic and financial operations, making it hard to meet the increasingly diverse user needs.
For developers, writing contracts must consider gas call fees and avoid writing complex contract code as much as possible. On Ethereum, the gas limit for an ETH transfer is 21,000 gwei, while for an ERC20 token transfer, it is 65,000 gwei. Slightly more complex scenarios, such as swaps, NFT transactions, and lending, require at least 300,000 gwei[2]. If the business becomes even more complex, gas consumption will become increasingly burdensome for users. This greatly limits the creative space for developers and restricts the richness and innovation of DeFi.
To fundamentally solve these issues, the market needs a more powerful infrastructure and a supporting financial system.
Thus, AO was born, and AgentFi is a new exploration of the next generation of DeFi within the AO ecosystem.
AO: An Infrastructure with Almost Unlimited Scalability
AO stands for Actor Oriented, which, as the name suggests, is a decentralized computing protocol based on role orientation.
In fact, compared to Ethereum, AO is closer to the concept of a world computer. I understand AO as a super computing layer, with the core goal of providing trustless and collaborative computing services without scale limitations.
Let’s take a look at the workflow diagram of the super-parallel computer built on AO:
Image source: AO white paper
Message Generation: Users or processes initiate requests by creating messages. These messages must comply with the specifications set by the AO protocol to be correctly transmitted and processed in the network.
Messenger Unit (MU) Relay: The Messenger Unit (MU) is responsible for receiving user-generated messages, acting as a router to direct messages to the appropriate SU nodes in the network. During this process, the MU will sign the messages to ensure data integrity.
Scheduling Unit (SU) Processing: When a message arrives at the SU node, the SU assigns a nonce to the message to ensure its order within the same process and uploads the message and nonce to the Arweave consensus layer for permanent storage.
Computing Unit (CU) Calculation: After receiving the message, the Computing Unit (CU) executes the corresponding computational tasks based on the message. After computation, the CU generates a signature with the computation result and returns it to the SU. This signature ensures the correctness and verifiability of the computation result.
So, where does consensus come from?
In AO, storage is equivalent to consensus. During the operation of processes, messages are transmitted, and these messages are written to Arweave, creating a “holographic state.” This means that the operational state of the process can be verified. In other words, Arweave’s immutable storage guarantees verifiability. This may seem counterintuitive, but if you fully understand the SCP paradigm, it will become clear instantly. If it’s still unclear, you can think of it in terms of inscriptions.
In addition to verifiability, we also need to address the question of who verifies. With verifiability, anyone can provide verification services. In AO, applications can choose their own verification services, flexibly determining their security based on their business nature. Combined with the economic game of optimistic challenges, the reliability of verification can be ensured.
On the computer built on AO, applications are constructed from any number of communication processes.
AO does not allow processes to share memory, but it does allow them to communicate through native message-passing standards.
Since message passing is asynchronous, by focusing on message passing, AO achieves a scaling mechanism similar to traditional Web2 distributed system environments.
This means that, theoretically, AO does not have performance limitations.
For developers, they can choose public nodes, but they can also run their own services on their own nodes. In this case, if they encounter performance bottlenecks, they can directly scale their own nodes, just like running Web2 services.
Moreover, this working mode also brings additional benefits—computing nodes can provide computational power support for AI scenarios. We will have the opportunity to discuss this later.
What Makes AgentFi Different?
Unlike traditional DeFi, which relies on a unified smart contract to manage funds and run financial operations, the concept of AgentFi allows everyone to run processes on the AO computer and manage their own funds, acting on their financial behaviors. What does this look like? Let’s take the leading DEX Permaswap on AO as an example.
In traditional DeFi, suppose Alice wants to swap Token A for Token B. On a DEX, a liquidity pool is first needed, with funds managed by a smart contract to provide the exchange function for A/B tokens. The exchange rate is determined by the market-making curve used by that smart contract (e.g., x*y=k). In Permaswap, each LP manages their own market-making funds through their proxy processes and customizes the market-making curve and strategy. Of course, LPs can also adopt an “extreme market-making strategy”—simply placing a limit order.
In fact, we find that Permaswap can integrate both AMM and order book trading forms. For users, when they initiate a trade, the entity that matches them and helps complete the trade could be an AMM, a limit order, or even both.
Overall, AgentFi has three characteristics:
Self-Custody: Users manage their own funds and execute their own trading strategies through their controlled proxy processes, rather than entrusting them to a unified contract.
Personalization: Users can flexibly set their financial business parameters through their controlled proxy processes. This means that it is akin to users opening their own exchanges, allowing them to customize trading strategies and fees. If extended to lending, it can be understood as users opening their own banks, customizing interest rates. Furthermore, users can run customized financial strategy programs through self-custodied processes, which can even integrate AI-driven intelligent strategy programs.
Peer-to-Peer: The matching of supply and demand is no longer a traditional DeFi point-to-pool model but returns to a peer-to-peer model.
On Ethereum, there is a distinction between contract accounts (CA) and externally owned accounts (EOA), with different financial scenario functions implemented through different contract codes, requiring human participation in financial behaviors. In AO, it is another concept oriented towards Agents, where different Agents can achieve different functions, and financial behaviors can be acted upon by Agents. I believe the concept of AgentFi is more like building blocks, allowing for a richer decentralized financial ecosystem.
With a large number of self-custodied processes, how can they communicate with each other and achieve composability? This brings us to the FusionFi Protocol, which is a development standard and communication specification for Agents on AO. Almost all financial operations can be abstracted as the circulation and processing of bills, and the FusionFi Protocol defines a set of standard formats for these bills. With such a standard, complex and diverse financial forms can be integrated. Developers can implement various financial operations such as exchanges, lending, futures, and even stablecoins based on the FusionFi standard. In the future, the FusionFi Protocol can refer to the models of industry-standard proposals like BIP, EIP, and NIP, allowing more people to participate in formulating protocol standards and promoting the sustainable development of the ecosystem.
I will write a separate article to elaborate on the FusionFi Protocol.
Conclusion
The performance and cost issues of Ethereum limit the current pace of DeFi development. Although the scaling of L2 and new public chains has been effective, there still exists an invisible ceiling that restricts the development of financial operations.
To completely break this ceiling, a network different from traditional blockchain paradigms—the AO super-parallel computer—has emerged. Due to AO’s infinitely scalable performance, AgentFi has become possible. Users can run their own processes, manage their funds, and customize their financial operations.
The Agent-oriented financial model has a broader range of application scenarios compared to traditional DeFi.
Data Sources:
Ethereum TPS Interpretation
https://www.chaincatcher.com/zh-tw/article/2102262
Ethereum Transaction Gas Usage Statistics
https://etherscan.io/gastracker
References:
Technical Explanation of AO Super-Parallel Computer
AO Protocol: Decentralized, Permissionless Supercomputer
https://x.com/kylewmi/status/1802131298724811108
Smart Finance: From AgentFi to FusionFi
https://www.notion.so/permadao/AgentFi-FusionFi-6461feb8915c4ea5a1252eca80aa6a4a
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