The Evolution Path of DeFi Intelligence: From Automation Tools to Intelligent Agent Networks

In the current cryptocurrency industry, stablecoin payments and Decentralized Finance applications are among the few verified sectors with genuine demand and long-term value. At the same time, the flourishing Agents are gradually becoming the practical interface of the AI industry for users, serving as the key intermediary layer that connects AI capabilities with user needs.

In the field of the integration of Crypto and AI, especially in the direction of AI technology feeding back to Crypto applications, the current exploration mainly focuses on three typical scenarios:

1. Conversational Interactive Agents: Primarily focused on chat, companionship, and assistant types. Although most are still wrappers of general large models, the low development threshold and natural interactions, combined with token incentives, have made them one of the earliest forms pushed to the market to gain user attention.

2. Information Integration Agent: Focuses on the intelligent integration of online and on-chain information. Kaito, AIXBT, and others have achieved success in the field of online but off-chain information search integration, while the integration of on-chain data is still in the exploratory stage with no明显 leading projects.

3. Strategy Execution Agent: Focused on stablecoin payments and the execution of Decentralized Finance strategies, this type of Agent extends into two main directions: Agent Payment and DeFAI. Such Agents are more deeply embedded in on-chain trading and asset management logic, with the potential to break through speculation bottlenecks and form an intelligent execution infrastructure characterized by financial efficiency and sustainable returns.

This article will focus on the evolutionary path of the integration of Decentralized Finance and AI, outlining its development stages from automation to intelligence, and analyzing the infrastructure, scenario space, and key challenges of strategy execution agents.

The Three Stages of DeFi Intelligence: Automation, Copilot, and the Leap to AgentFi

In the evolution of intelligent DeFi, we can divide the system capabilities into three stages: Automation, Intent-Centric Copilot, and AgentFi.

• Automation is more like a Rule Trigger: it executes fixed tasks based on preset conditions, such as arbitrage, rebalancing, taking profits, and stop-losses, and cannot generate strategies or operate independently.
• Copilot introduces intent recognition and semantic parsing capabilities, allowing users to input natural language. The system understands, decomposes, and suggests execution paths, but ultimately still requires user confirmation, and the execution chain is not closed.
• AgentFi represents a complete "Perception → Reasoning/Strategy Generation → On-Chain Execution → Evolution" intelligent closed loop, which is an intelligent agent (Agent) capable of on-chain autonomous execution and continuous evolution.

To determine whether a project truly belongs to AgentFi, it needs to meet at least three of the following five core criteria:

1. Autonomous perception of on-chain states/market signals (not static inputs, but real-time monitoring)
2. Possess the ability to generate and combine strategies (not preset strategies, but the ability to formulate action plans based on context)
3. Can autonomously execute operations on the chain (no user interaction required, can perform complex operations such as swap/lend/stake)
4. Has persistent state and evolutionary capability (Agents have a lifecycle, can run for a long time and self-adjust based on feedback)
5. Equipped with Agent-Native architecture (such as dedicated Agent SDK, managed execution environment, Agent middleware, etc.)

In other words, automated trading ≠ Copilot, and even more ≠ AgentFi: automated trading is just a "rule trigger"; Copilot can understand user intent and provide operational suggestions, but still relies on human participation; while the real AgentFi is an "intelligent agent with perception, reasoning, and on-chain autonomous execution capabilities" that can complete strategy loops and continuous evolution without human intervention.

Analysis of Intelligent Adaptability in DeFi Scenarios

In the DeFi (Decentralized Finance) system, the core application scenarios can be roughly divided into asset circulation and exchange types and yield-generating finance types. We believe that there are significant differences in the adaptability of these two types of scenarios on the path to intelligence:

1. Asset circulation and exchange scenarios

Asset circulation and exchange scenarios are primarily based on atomic interactions, including swap trading, cross-chain bridges, and fiat deposits and withdrawals. The essential characteristic is "intention-driven + single atomic interaction." The trading process does not involve yield strategies, state maintenance, or evolutionary logic, and is mostly suitable for the lightweight execution path of Intent-Centric Copilot, which does not fall under AgentFi.

Due to its lower engineering threshold and simple interaction, most DeFAI projects on the market are currently at this stage, which does not constitute a closed-loop intelligent agent for AgentFi; however, a few advanced complex Swap strategies (such as cross-asset arbitrage, perpetual hedging LP, leverage rebalancing, etc.) actually require the capability of AI Agents for integration, and are still in the early exploration stage.

2. Asset Yield Financial Scenarios

Asset income financial scenarios have clear income targets, complex strategy combination spaces, and dynamic state management needs, naturally aligning with AgentFi's "strategy closed loop + autonomous execution" model. Its core features are as follows:

• Quantifiable yield targets (APR / APY) make it easier for Agents to establish optimization functions;
• The strategy portfolio space is vast, covering multiple assets, multiple timeframes, multiple platforms, and multiple interaction processes;
• Operations require frequent management and real-time adjustments, suitable for execution and maintenance by on-chain agents.

Due to multiple factors such as the constraints of yield duration, volatility frequency, complexity of on-chain data, difficulty of cross-protocol integration, and compliance restrictions, the adaptability and engineering feasibility of different yield scenarios in the AgentFi dimension vary significantly, with the following priority recommendations:

High priority business landing direction:

• Lending / Borrowing: Interest rate fluctuations are easy to track with standardized execution logic, suitable for lightweight agents.
• Yield Farming: The pools are dynamic and frequent, with a large strategy combination space and high yield fluctuations. AgentFi can significantly optimize annualized returns and interaction efficiency, but the engineering implementation poses certain challenges;

Long-term layout directions to explore:

• Pendle yield rights trading: The time dimension and yield curve are clear, suitable for Agent management of expiry rotation and inter-pool arbitrage;
• Funding Rate arbitrage: Theoretical returns are considerable, but challenges in cross-market execution and off-chain interactions need to be addressed, and the engineering difficulty is high.
• LRT Dynamic Combination Structure: Static staking is not suitable, you can try strategies such as LRT + LP + Lending for automatic adjustment.
• RWA multi-asset portfolio management: difficult to implement in the short term, Agent can provide assistance in portfolio optimization and maturity strategies;

Introduction to Intelligent Projects in Decentralized Finance Scenarios

1. Automation Tools ( Automation Infra ): Rule Triggering and Condition Execution

Gelato is one of the earliest infrastructures for DeFi automation, having previously provided conditional task execution support for protocols like Aave and Reflexer, but it has now transformed into a Rollup as a Service provider. Currently, the main battleground for on-chain automation has also shifted to DeFi asset management platforms (DeFi Saver, Instadapp). These platforms integrate standardized automated execution modules including Limit Order setting, liquidation protection, automatic rebalancing, DCA, and grid strategies. In addition, we see some more complex DeFi automation tool platform projects:

Mimic.fi

Mimic.fi is an on-chain automation platform that serves DeFi developers and projects, supporting the creation of programmable automation tasks on chains such as Arbitrum, Base, and Optimism. Its core functionality is realized through "if-then" rule triggers that enable automatic execution of cross-protocol operations, and the architecture is divided into three layers: Planning (task and trigger definition), Execution (intent broadcasting and execution bidding), and Security (triple verification and security control). Currently, it uses an SDK integration method and the product is still in the early deployment stage.

AFI Protocol

AFI Protocol is an algorithm-driven Agent execution network that supports 24/7 unmanaged automation operations, focusing on solving issues of execution decentralization, strategy thresholds, and risk response in Decentralized Finance. Its design is aimed at institutions and advanced users, providing orchestrable strategies, permission management, and SDK tools, and has launched the yield-bearing stablecoin afiUSD as its native asset. It is currently in the internal testing phase at Sonic Labs and has not yet been publicly launched or opened for retail users.

2. Intent-Centric Copilot: Intent Expression and Execution Recommendations

The DeFAI concept, which was once very popular at the end of 2024, aside from some speculation mainly involving Meme tokens, most projects essentially belong to the Intent-Centric Copilot type - that is, expressing user intentions through natural language, and the system providing trading suggestions or completing basic on-chain operations. Its core capability still remains at the "intent recognition + Copilot-style assistance execution" stage, and has not yet formed a complete strategy loop and continuous optimization mechanism. Many products have obvious shortcomings in semantic understanding, cross-protocol invocation, and feedback response, resulting in a generally poor user experience and relatively limited functional boundaries.

HeyElsa

HeyElsa is an AI Copilot positioned in the Web3 scenario, empowering users to complete various on-chain operations through natural language interaction, including trading, cross-chain bridging, NFT purchases, stop-loss settings, and token creation. As a multifunctional conversational crypto assistant, it covers users from beginners to advanced traders (including the highly active degen community), and currently supports real-time interaction across more than 10 mainstream blockchains. The platform's daily trading volume has reached $1 million, with daily active users maintained between 3,000 and 5,000. The system has integrated yield optimization strategies and automated intent execution modules, initially constructing the foundational capability framework for AgentFi applications.

Bankr

Bankr is an intent trading assistant that integrates AI, Decentralized Finance, and social scenarios, allowing users to issue commands in natural language on the X platform or exclusive terminals to perform operations such as Swap, limit orders, cross-chain bridging, token issuance, and NFT minting, supporting Base, Solana, Polygon, and the Ethereum mainnet. Bankr has built a complete Intent → Compilation → Execution link, emphasizing a minimalist trading experience and seamless operations within a social environment, and activates the ecosystem through token incentives and revenue-sharing mechanisms.

Griffain

Griffain is a multifunctional AI Agent platform deployed on Solana, supporting users to interact with Griffain Copilot through natural language for on-chain operations such as asset queries, swaps, NFT trading, and LP management. The platform is equipped with multiple agent modules and encourages community participation in agent creation and sharing. Technically built on the Anchor Framework along with components like Jupiter and Tensor, it emphasizes mobile adaptation and front-end composability. Currently, it supports over 10 core agent modules, possessing strong execution capabilities and ecological connectivity.

Symphony

Symphony is an on-chain execution infrastructure for AI Agents, building a full-stack system that covers intent modeling, intelligent path discovery, RFQ execution, and account abstraction, aiming to become the core module of the DeFi smart execution layer. The platform has launched the conversational assistant Sympson, which has market query and strategy recommendation functions, but on-chain execution is not yet open. Symphony provides the core components needed for AgentFi and can support multi-Agent collaborative execution and cross-chain operations in the future.

Hey Anon

HeyAnon is a DeFi AI platform that combines intent interaction, on-chain execution, and intelligence analysis, supporting multi-chain deployment (Ethereum, Base, Solana, etc.) and cross-chain bridging (LayerZero, deBridge). Users can perform operations such as Swap, lending, and Staking through natural language, and obtain on-chain sentiment and market dynamics analysis. Although the project has high attention due to its founder Sesta, it is currently still in the Copilot stage, and the core strategies and execution intelligence have not yet been fully implemented, so long-term development still needs to be observed.

3. AgentFi Agent: Strategy Closed Loop and Autonomous Execution

We believe that AgentFi represents a more advanced form compared to Intent Copilot on the path of intelligent leaps in Decentralized Finance. Agents have independent yield strategies and on-chain automatic execution capabilities, which can significantly enhance users' strategy execution efficiency and capital utilization. By 2025, we are delighted to see that more and more AgentFi projects have been launched or are in product planning, mainly focusing on lending and liquidity mining, with representative projects including Giza ARMA, Theoriq AlphaSwarm, Almanak, Brahma, and Olas.