Understand Aperture in One Article: Issuing DeFi Operation Commands to Chatbots

This article will mainly introduce Aperture and address the growth challenges currently faced by the DeFi industry.

The goal of Aperture is to challenge and surpass the traditional trading methods that have hindered the mass adoption of DeFi, moving closer to a "intent-based" future.

In Short: Ten Times the Execution Efficiency, One-Tenth the Workload

Aperture is building a new chatbot experience for users, supported by an underlying intent infrastructure, allowing users to "express their goals" in natural language and leverage a network of solvers for better execution and more favorable pricing than the current trading paradigms.

User Experience: Intent DSL Driven Aperture LLM

First, Aperture will start from the foundational condition for any mass adoption: User Experience (UX).

The current DeFi UX is transaction-method-centric, requiring users with varying levels of technical understanding to sign state changes, which also alters the "final state" in the user's mind. Through intent, Aperture places the "final state" at the core of the user experience.

With the power of modern LLMs and a proprietary intent-focused programming language, Aperture aims to enhance the expression of user intent. This will enable users to articulate their trading goals and preferences more intuitively and effectively, making it easier and more precise to harness the potential of blockchain.

Imagine a user who does not understand the principles of blockchain technology, faced with a plethora of "knobs and buttons" on a traditional DeFi interface. Clearly, Aperture's approach of "supporting users to express their intent in natural language" is simpler. This requires converting natural language into blockchain code—this is where Domain-Specific Language (DSL) comes into play.

Unlike GPL (General Purpose Language), which is applicable across a wide range of fields, DSL is a specialized computer language tailored for specific application domains. The design and utilization of DSLs are integral to domain engineering, often involving the creation of new DSLs or the adaptation of existing ones to facilitate more effective expression of problems and solutions within a specific domain.

In Aperture, the design of the DSL takes into account human reading habits and language conventions, which is crucial for supporting clear and intuitive intent expression. Other DSLs may prioritize aspects such as programming efficiency or machine-level optimization.

On Aperture, the LLM allows users to express their intent in natural language and feedback that intent in a highly readable DSL format, bridging the gap between technical functionality and user-friendly interfaces. This DSL can then be provided to solvers as the user's "true statement."

Using a real-world analogy: the user experience of translating LLM to DSL is akin to a customer placing an order over the phone at a pizza shop. The customer might order in very colloquial language: "Give me your largest all-meat pizza." The operator on the other end might respond: "You want our meat lovers pizza, in large size?" The user easily understands this transformation and agrees: "Yes, I don't know its name, but that's what I want."

On-chain, this interaction will occur in a similar manner. The user might first state their ultimate goal—

"Can you rebalance my ETH-GMX LPs to concentrate 80% of funds in the best-performing pools across all my EVM chains, while evenly distributing the remaining 20% LP funds into the other pools?"

The parsing of the DSL might feedback to the user—

● Qualified assets: ETH-GMX trading pairs on Mainnet, Arbitrum, and Avalanche;

● Allowed operations: bridging, removing liquidity, trading ETH or GMX, adding liquidity;

● Final Goal 1: Rebalance liquidity positions to concentrate 80% of qualified asset capital in the positions with the highest spot APY according to APY Vision data;

● Final Goal 2: Rebalance liquidity positions to concentrate 20% of qualified asset capital in existing pools not used in Final Goal 1;

● Sign intent statement (if correct).

The conversion LLM will standardize the colloquial language into DSL terminology, which solvers will utilize in a predictable and replicable manner.

Underlying Infrastructure

The intent infrastructure can be broken down into several components:

● Intent Clearinghouse (Memory Pool): Acts as a preliminary holding area for user intents. It is designed to efficiently organize these intents for processing, using priority algorithms based on various criteria such as urgency and resource requirements. The clearinghouse ensures that intents are managed securely and orderly before they are submitted to the blockchain.

● ZK Simulation for Data Validity: This is the resource required to verify certain intents and their corresponding solutions, which will rely on off-chain data. Zero-knowledge proofs can be used to validate the validity of this data. By utilizing advanced cryptographic tools like Brevis or Axiom, Aperture can generate ZKPs for historically on-chain data that is part of the solutions proposed. This approach allows for rigorous validation of the outputs of solutions, ensuring their accuracy, completeness, and compliance with specified constraints and intents, while preserving the confidentiality of transaction data.

● Verification Smart Contracts: Each intent use case will require a smart contract to simulate, verify, and oversee the proposed solutions.

● Ranking and Execution Engine: Each group of validated intents will need to be ranked based on outcomes and solver scores, and then executed subsequently. A key aspect of this execution engine is its accountability enforcement capability. If any malicious activity occurs, such as revoked transactions or other malicious events, the execution engine is designed to punish accountable solvers through reduced rewards or other means. This not only protects the integrity of transactions but also deters potential malicious behavior from solvers.

Application Layer: Solver DAO

The Solver DAO network is a unique application layer built on the intent infrastructure. Aperture's intent infrastructure enables Solver DAO to focus on enabling and solving use cases based on unique intents without worrying about underlying execution demands.

Solver DAO gains access to user intents in the Aperture clearinghouse by staking the necessary amount of $APTR and $ETH. Solver DAO can be associated with a large professional solver with proprietary solutions or a network composed of smaller solvers.

New intent solutions can come from Aperture or third-party Solver DAOs. Solver DAOs add value by enabling new intent use cases. This requires submitting the necessary business logic to fit Aperture's modular design. Once built, this use case can now be "declared" from the Aperture intent interface or a third-party interface created by the solver DAO.

Aperture DAO will provide $APTR funding to Solver DAO to enable new intent use cases.

How Solvers Will Compete, What Types of Solvers May Exist?

On-Chain vs. Off-Chain

In the competitive Aperture intent ecosystem, solvers stand out by the methods they use to publish solutions. While not mandatory, smart contracts are preferred due to their scalability and speed. However, off-chain scripts are equally adept at quickly publishing solutions, providing an alternative route. Some declared intents may even have characteristics that allow solvers to manually submit solutions. (For example, a seller wishes to arrange a large OTC trade and sets a 3-day bidding window.)

Maintaining Alpha

For solvers with genuine "alpha" or proprietary solution generation methods, they can avoid using smart contracts to generate solutions and instead rely on Aperture's zero-knowledge verification process to establish trust in their off-chain script-enabled solutions. This will enhance the positive feedback loop of attracting solvers (sustainable business solutions attract more revenue, attracting more solvers).

Solver Library

Although not explicitly required in a given ecosystem, solvers can also choose to raise collateral through crowdfunding, via a vault mechanism, with a portion of solver earnings as a return. Each Solver DAO can open-source a reward-sharing vault contract for its solvers to implement (if they wish to receive initial funding support).

Example: Intent Airdrop

To facilitate understanding, let's take the "airdrop claim intent" proposed in Aperture's first blog post as an example. How does a user declare intent? How can a dedicated Solver DAO leverage Aperture's Solver DAO marketplace?

The user first declares in natural language:

"Claim all eligible airdrops on my behalf, don't forget the gas fees associated with the claim, in exchange, pay 1% or less."

The chatbot may ask clarifying questions to further refine the user's declaration.

Once this clarification is complete, the intent will be translated from natural language into encoded intent DSL and sent back to the user in a readable format for verification. Next, the intent expression will be published to the intent clearinghouse, where any qualified solver can view the user's declaration.

Now, solvers can view the user's address and cross-reference it with claimable airdrops or rewards. Permissioned functions supported by account abstraction wallets allow solvers to claim airdrops on behalf of users. Solvers will compete on "finder's fees" and their overall understanding of the airdrop. The difference in intent now is that if Solver A covers a Dymension airdrop while Solver B covers a Celestia airdrop, both solvers can earn finder's fees from our user.

Proposed solutions will be simulated by Aperture's smart contracts to verify the proposed outcomes, and then all validated solutions will be ranked. Subsequently, Aperture will execute on behalf of the user, returning all airdrops.