Original Title: DeFAI is the New DeFi
Author: Defi0xJeff, Crypto KOL
Translator: zhouzhou, BlockBeats
In this article, Jeff discusses how DeFAI (Decentralized Finance + Artificial Intelligence) simplifies, optimizes, and enhances the DeFi experience through abstraction layers, autonomous trading agents, and AI-driven dApps. He introduces several developing DeFAI projects, such as Almanak, Cod3x, and Mode, emphasizing the role of AI in improving trading strategies and managing portfolios.
The following is the original content (reorganized for better readability):
DeFi has always been a pillar of Web3. It makes blockchain practical, providing tools for instant global fund transfers, on-chain asset investments, intermediary-free lending, and stacking strategies across DeFi protocols. This is the financial freedom within reach.
More importantly, DeFi addresses real-world problems. It allows unbanked individuals to access financial services, removes intermediaries, and operates around the clock, creating a truly global and inclusive financial system.
However, when we face reality, we realize that DeFi is complex. Setting up wallets, managing transaction fees, avoiding scams and rug pulls—this is not suitable for the average person. The ever-expanding L1, L2, and cross-chain ecosystems only complicate matters further. For most people, the entry barrier is simply too high.
This complexity limits the growth of DeFi, but with the emergence of DeFAI, this situation is beginning to change.
What is DeFAI?
DeFAI (DeFi + AI) makes DeFi more accessible. By leveraging AI technology, it simplifies complex interfaces and removes barriers for ordinary people to participate. Imagine a world where managing your DeFi portfolio is as simple as chatting with ChatGPT.
The first wave of DeFAI projects has begun to emerge, primarily focusing on three areas:
Abstraction Layers
Autonomous Trading Agents
AI-driven dApps
1. Abstraction Layers
The goal of abstraction layers is to hide the complexity of DeFi through intuitive interfaces. They allow users to interact with DeFi protocols using natural language commands, without the need for complex dashboards.
Before AI, abstraction layers like intent-based architectures simplified trade execution. Platforms like CoWSwap and symm.io allow users to achieve optimal pricing in decentralized liquidity pools, addressing the issue of liquidity fragmentation, but they did not solve the core problem: DeFi still feels difficult.
Now, AI-driven solutions are filling this gap:
Griffain is the first project to launch a token and is currently in early access, requiring an invitation to use.
Griffain is more versatile, allowing users to perform a range of operations from simple to complex, such as task automation (DCA), launching memecoins, and conducting airdrops.
Orbit / Grift is the second project to launch a token, designed for on-chain DeFi experiences. Orbit emphasizes cross-chain functionality, having integrated over 117 chains and 200 protocols, making it the most integrated among the three protocols.
Neur is the third project to launch a token, but due to its open-source nature, it quickly surpassed Orbit in valuation. Neur positions itself as a co-pilot for Solana, designed specifically for the Solana ecosystem. Neur is powered by the Solana Agent Kit from sendaifun.
I personally use Slate CEO, which is still in its early stages and has not yet launched a token, but I really like their automation features. I mainly use it to set conditional trades, such as selling 25% of my position if xxxx reaches a market cap of $5 million, or buying $5,000 worth of tokens if xxx reaches xxxx price.
AIWayfinder is another interesting project worth watching. It is a behemoth created by the PRIME / ParallelTCG team and is highly anticipated.
2. Autonomous Trading Agents
Why spend hours digging for Alpha, manually executing trades, and trying to optimize your portfolio when you can have an agent do it for you? Autonomous trading agents take trading bots to a new level, transforming them into dynamic partners that can adapt, learn, and make smarter decisions over time.
It is important to clarify that trading bots are not new. They have existed for years, executing predefined actions based on static programming. But agents are fundamentally different:
- They extract information from unstructured and constantly changing environments.
- They reason about data in the context of their objectives.
- They discover patterns and learn to leverage these patterns over time.
- They can perform actions that their owners have not explicitly programmed.
This subfield is rapidly evolving; initially, agents may have been used for entertainment purposes—such as hyping up some junk coins for fun—but it has now shifted to more practical, profit-driven tools that help users trade more effectively. However, there remains a significant challenge: how do you verify that an "agent" is not just a bot or even a person operating behind the scenes?
This is where DeAI infrastructure plays a crucial role.
The Role of DeAI in Verifying Agents
Key infrastructures like Trusted Execution Environments (TEE) ensure that agents can operate securely and without tampering.
For example:
TEE: Promoted by PhalaNetwork, TEE provides a secure isolation zone where data can be processed confidentially. Phala's experiments—such as Unruggable ICO and Sporedotfun—demonstrate how agents can execute tasks while maintaining data integrity.
Transparent execution/verification frameworks: Innovations like zkML (zero-knowledge machine learning) or opML provide verifiability for reasoning and computation. Hyperbolic Labs' Proof-of-Sampling (PoSP) is a prominent example. This mechanism combines game theory and sampling techniques to ensure that computations are both accurate and efficient in a decentralized environment.
Why is this important?
As autonomous agents begin to handle significant TVL (assuming $100 million or more), users will demand assurances. They need to understand how agents manage risk, verify the frameworks they operate within, and ensure their funds are not randomly thrown at some junk coins.
This field is still in its early stages, but we are already seeing some promising projects exploring these verifiability tools. As DeFAI develops, this is a direction worth watching.
For more trends on DeAI infrastructure, check out this article:
Top Autonomous Trading Agents I’m Watching
Almanak
Almanak offers users institutional-grade quantitative AI agents that address complexity, fragmentation, and execution challenges in DeFi. The platform executes Monte Carlo simulations in real environments through a forked EVM chain, taking into account unique complexities like MEV, transaction fees, and transaction order.
It employs TEE (Trusted Execution Environment) to ensure the privacy of strategy execution, protecting Alpha information, and allows for non-custodial fund management through Almanak Wallets, enabling precise permission delegation to agents.
Almanak's infrastructure supports the ideation, creation, evaluation, optimization, deployment, and monitoring of financial strategies. The ultimate goal is for these agents to learn and adapt over time.
Almanak raised $1 million on legiondotcc, with subscriptions oversubscribed. The next steps include the release of the beta version and the deployment of initial strategies/agents for testing with beta testers. It will be very interesting to observe the performance of these quantitative agents.
Cod3xOrg / BigTonyXBT
Cod3x, created by the Byte Mason team (known for their work in Fantom and SonicLabs), is a DeFAI ecosystem aimed at simplifying the creation of trading agents. The platform provides a no-code building tool that allows users to create agents by specifying trading strategies, personalities, or even tweet styles.
Users can access any dataset and develop financial strategies in minutes, leveraging a rich API and strategy library. Cod3x integrates with AlloraNetwork, using its advanced ML price prediction model to enhance trading strategies.
Big Tony is the flagship agent based on the Allora model, predicting entries and exits for mainstream coins. Cod3x is working to create a thriving ecosystem of autonomous trading agents.
A notable feature of Cod3x is its liquidity strategy. Unlike the common alt:alt LP structure promoted by virtuals.io, Cod3x uses a stablecoin:alt LP supported by cdxUSD, which is Cod3x's own CDP (Collateralized Debt Position). This structure provides more stability and confidence for liquidity providers compared to the volatility of alt:alt trading pairs.
Cod3x also has its own DeFi primitives, such as liquidity AMOs (Automated Market Operations) and mini pools, which enhance liquidity and add more functionality/DeFi Lego components to agents in its ecosystem.
Other Notable Projects
getaxal / Gekko Agent—Axal's autonomous driving product, where the agent handles complex multi-step crypto strategies. Gekko integrates autonomous driving features. I am waiting to see how Gekko performs data-driven trading in autonomous mode.
ASYM41b07—Often referred to as the "cheat code for memecoin trading," the ASYM agent can analyze vast amounts of data from blockchains and social media to predict memecoin trends. ASYM has consistently outperformed the market and demonstrated 3-4 times returns through backtesting. It will be interesting to see how it performs in live trading.
ProjectPlutus—I just love this name PPCOI
3. AI-driven Decentralized Applications (dApps)
AI-driven dApps are a promising but still nascent area within the DeFAI space. These are fully decentralized applications that integrate AI or AI agents to enhance functionality, automation, and user experience. While this field is still in its early stages, some ecosystems and projects have begun to stand out.
In this area, modenetwork is a very active ecosystem, a Layer 2 network aimed at attracting high-tech AI x DeFi developers. Mode serves as a base for multiple teams working on cutting-edge AI-driven applications:
·ARMA: Autonomous stablecoin mining tailored to user preferences, developed by gizatechxyz.
·Modius: Autonomous agents supported by autonolas for mining Balancer LP.
·Amplifi Lending Agents: Developed by Amplifi Fi, these agents integrate with IroncladFinance to automatically swap assets, lend on Ironclad, and maximize returns through automatic rebalancing.
At the core of this ecosystem is MODE, the native token. Holders can stake MODE to receive veMODE, which grants access to AI agent airdrops, whitelist access to projects, and more ecosystem benefits. Mode is positioning itself as a hub for AI x DeFi innovation, with its influence expected to grow significantly by 2025.
Additionally, danielesesta has garnered widespread attention with the DeFAI theory of HeyAnonai. He announced that HeyAnon is developing the following:
- An abstraction layer as a DeFi interface
- DeFi agents for autonomous trade execution
- Research and communication agents for acquiring, filtering, and interpreting relevant data
The market reacted enthusiastically, with the market cap of the ANON token skyrocketing from $10 million to $130 million. Daniele seems to be bringing back the excitement of TIME Wonderland, but this time with a stronger foundation and a clearer vision.
In addition to these two ecosystems, many teams are building their own AI-driven decentralized applications. Once major ecosystems form around them, I will share more information in the future.
Final Thoughts
DeFAI is transforming DeFi by making it smarter, simpler, and more accessible. As abstraction layers simplify user interactions, autonomous trading agents manage portfolios, and AI-driven dApps optimize use cases, we are witnessing the dawn of a new era.
Rather than calling it the DeFi summer of 2020, it is more accurate to say that 2025 will be the summer of DeFAI.
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