The Era of "Intelligent Automation": The Integration and Innovation of Intent Trading and AI Smart Agents

In today's rapidly evolving blockchain technology, intent trading and AI intelligent agents are becoming the focal point of industry attention. Many industry experts, including the founder of Ethereum and the Paradigm team, believe that intent trading will become one of the important directions for the future development of blockchain applications. This article will explore the concept of intent trading and its potential, analyzing how this model simplifies user experience, enhances trading security, and brings more innovative opportunities for decentralized applications. At the same time, we will also discuss the role of AI intelligent agents, exploring how they can be combined with intent trading to further promote the automation and intelligence of smart contracts, providing users with a smarter and more personalized blockchain interaction experience.

The Nature of Intentional Trading

Intent trading is a blockchain operation execution method that is user goal-oriented. In this model, users only need to express their final objectives, such as conditions like time and transaction price, without worrying about the specific execution steps. Users sign a contract, outsourcing the trade creation to a third party. As long as the final result falls within the range set by the user, the solver can freely achieve the result, typically matching other corresponding intents in the community and exchanges to meet the needs of multiple users. Users need to pay a certain fee to the solver to complete the transaction.

The two core features of intent-based trading are:

1. Adopt a "declarative programming approach" that directly declares the expected outcomes of transactions without specifically detailing the execution steps.
2. Delegate the construction process of actual transactions to third-party solvers, who will generate the traditional blockchain transactions needed to achieve the expected results.

This trading method is particularly suitable for handling virtual currencies with the "same" attribute, such as Bitcoin, because they are essentially identical, with consistency and interchangeability.

Advantages and Applications of Intent Trading

The most significant advantage of intention trading is that it simplifies the trading process and enhances user experience. It can:

• Reduce trading details and simplify the operation process in the dApp.
• Supports repeat transactions to avoid the inconvenience of users having to perform manual operations regularly.
• Implement time-related or condition-based transactions, such as automatic balance top-ups.
• Eliminate the hassle of regularly purchasing tokens with simple commands.

This approach helps beginners to use cryptocurrencies more easily without dealing with cumbersome steps. Since the intention of the trade focuses on the output result, orders do not need to be executed immediately; the system can execute the orders when the market is most favorable, reducing slippage. The solver will look for the best path and may sometimes aggregate orders for larger trades to further reduce slippage.

Potential applications of intent-based trading include:

• Set limit orders to buy tokens at target price
• Set the acceptable slippage range
• Regularly scheduled token purchases
• Automatic transfer when balance is insufficient
• Buy or sell tokens in a timely manner based on significant events reported by the oracle.

Intent Trading Case: UniswapX

UniswapX is an innovative decentralized trading protocol that employs a permissionless, open-source auction mechanism, allowing users to trade across different AMMs and other liquidity sources. Its core is intent-based trading, where users only need to express their trading intentions without worrying about the specific execution process.

UniswapX offers three different reactors: Limit Order Reactor, Dutch Order Reactor, and Exclusive Dutch Order Reactor, which handle different types of orders. After placing an order, users sign a contract with Permit2, allowing token transfers. Once the order is published, anyone can take the order and complete it.

"Fillers" can complete transactions using various methods and benefit from multiple liquidity pools, including decentralized exchanges, centralized exchanges, cross-chain liquidity networks, etc., to ensure optimal pricing. Fillers are motivated to complete transactions quickly to achieve higher prices and higher fees per transaction. Reactors verify contracts to ensure that the output of tokens meets expectations.

UniswapX provides users with a more efficient, transparent, and user-friendly trading environment through its innovative auction mechanism and intent-based trading concept, while addressing the issues faced by traditional AMMs, such as trading costs, MEV attacks, and slippage losses.

The Concept and Application of AI Smart Agents

AI intelligent agents are computer programs that can autonomously make decisions and execute tasks based on the environment, input, and predefined goals. Their core components include:

• Large Language Models (LLM) as "brains"
• Observation and Perception Mechanism
• Reasoning process
• Action Execution
• Memory and Retrieval

AI intelligent agents can be reactive, proactive, learning, or collaborative, typically operating independently to perform complex tasks. Common examples of AI intelligent agents include ChatGPT, Tesla's autonomous driving engine, and Netflix's recommendation engine.

On a mature AI smart agent platform, users only need to issue instructions, and the LLM will intelligently call various tools to meet the users' needs. The application scenarios of AI smart agents are very broad, covering multiple fields such as e-commerce, education, real estate, tourism, finance, healthcare, and transportation.

The Integration of AI Smart Agents and Intent Trading

In intent-based trading, AI intelligent agents can serve as smart personal assistants, helping users complete various tasks by understanding natural language input. LLMs can be integrated into intent-based architectures, allowing users to express their needs without having to consider implementation details.

The integration of AI intelligent agents can enhance the efficiency and intelligence level of intent-based trading. For example, AI intelligent agents can utilize their capabilities, such as perception, planning, memory, and tool usage, to interact with solvers, automatically execute trading strategies, and optimize the price and timing of trade execution.

Some companies have started to explore the combination of these two concepts. For example, the TXT2TXN prototype created by Circle allows users to exchange and transfer funds on EVM chains. After the user inputs their intention, the LLM identifies the type of intention and fills in the corresponding architecture to create an order or transaction payload.

Future Prospects and Challenges

In the future, we look forward to AI smart agents being able to perform more functions, such as purchasing NFTs or tokens through dApps. This will greatly increase their practicality, allowing users to perform more tasks without relying on programmers to constantly update the interface.

However, we also need to pay attention to some potential challenges:

1. Ensure that the AI smart agent correctly understands the user's intent to avoid issues caused by misunderstandings.
2. Address the privacy and market manipulation risks that may arise from the solver collecting user intent information.
3. The balancing solver utilizes data permissions to maintain trust in the decentralized financial ecosystem.

With the continuous development of technology, the combination of intention trading and AI intelligent agents will bring more innovations and opportunities to the blockchain field, promoting the automation and intelligence of smart contracts, and providing users with a more convenient, secure, and personalized blockchain interaction experience.