Original Title: DeFAI is the New DeFi
Author: Defi0xJeff, Crypto Kol
Translation: zhouzhou, BlockBeats
In this article, Jeff discusses how DeFAI (Decentralized Finance + Artificial Intelligence) simplifies, optimizes, and enhances the DeFi experience through abstraction layers, automated trading agents, and AI-driven dApps, introducing several developing DeFAI projects such as Almanak, Cod3x, and Mode, emphasizing the role of AI in enhancing trading strategies and managing portfolios.
The following is the original content (for readability, the original content has been reorganized):
DeFi has always been a pillar of Web3. It makes blockchain practical, providing tools for instant global fund transfers, on-chain asset investments, peer-to-peer lending, and stacking strategies between DeFi protocols. This is financial freedom within reach.
More importantly, DeFi addresses real-world problems. It provides access to financial services for the unbanked, removes intermediaries, and operates around the clock, creating a truly global and inclusive financial system.
But 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 ordinary people. The constantly expanding L1, L2, and cross-chain ecosystems only complicate matters further. For most people, the entry barrier is simply too high.
This complexity has limited the development of DeFi, but with the advent of DeFAI, this situation is beginning to change.
What is DeFAI?
DeFAI (DeFi + AI) makes DeFi much 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, mainly focused on three areas:
1. Abstraction Layer
2. Autonomous Trading Agents
3. AI-driven dApp
1. Abstraction Layer
The goal of the abstraction layer is to hide the complexity of DeFi through an intuitive interface. They allow users to interact with DeFi protocols through natural language commands, without the need for complex dashboards.
Before AI, abstraction layers like intent-based architecture simplified trade execution. Platforms like CoWSwap and symm io allow users to obtain the best pricing in decentralized liquidity pools, addressing liquidity fragmentation, but they did not resolve the core issue: DeFi still feels difficult.
Now, AI-driven solutions are filling this gap:
Griffain is the first project to launch a token and is currently still in early access, requiring an invitation to use.
Griffain is more versatile, allowing users to perform a variety of operations ranging from simple to complex, such as task automation (DCA), issuing memecoins, and conducting airdrops.
Orbit / Grift is the second project to launch a token, aimed at on-chain DeFi experiences. Orbit emphasizes cross-chain functionality, having integrated more than 117 chains and 200 protocols, making it the most integrated among the three protocols.
Neur is the third project to launch a token but has quickly surpassed Orbit in valuation due to its open-source nature. 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 launched a token yet, but I really like their automation features. I mainly use it to set conditional trades, like 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 worth looking forward to.
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 elevate 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 data within the context of their goals.
They discover patterns and learn to leverage those patterns over time.
They are capable of performing actions that their owners have not explicitly programmed.
This subfield is rapidly evolving; initially, agents might have been used for entertainment purposes—such as potentially hyping some junk coins for fun—but it has now shifted towards more practical, profit-driven tools that help users trade more effectively. However, there remains an important challenge: how do you verify that an 'agent' is merely a bot or even a person operating behind the scenes?
This is where the DeAI infrastructure plays a key role.
The role of DeAI in verifying agents
Key infrastructure like Trusted Execution Environments (TEE) ensures that agents can operate securely and tamper-proof.
For example:
·TEE: Promoted by PhalaNetwork, TEE provides a secure enclave where data can be processed confidentially. Phala's experiments—such as Unruggable ICO and Sporedotfun—demonstrate how agents can perform tasks while maintaining data integrity.
·Transparent execution/verification frameworks: Innovations like zkML (zero-knowledge machine learning) or opML provide reasoning and computational verifiability. Hyperbolic Labs' Proof-of-Sampling (PoSP) is a prominent example. This mechanism combines game theory and sampling techniques to ensure computations are accurate and efficient in a decentralized environment.
Why is this important?
When autonomous agents start handling significant TVL (assuming $100 million or more), users will demand assurances. They need to understand how the agents manage risk, the frameworks they operate under, and ensure their funds are not randomly thrown at some junk coin.
This field is still in its early stages, but we have already seen some promising projects exploring these verification tools. As DeFAI develops, this is a direction worth paying attention to.
For more trends on DeAI infrastructure, please check out this article:
Top autonomous trading agents I am watching
Almanak
Almanak offers users institutional-level quantitative AI agents to address the complexities, fragmentation, and execution challenges in DeFi. The platform executes Monte Carlo simulations in real environments by forking EVM chains, accounting for unique complexities like MEV, transaction fees, and transaction ordering.
It employs TEE (Trusted Execution Environment) to ensure the privacy of strategy execution, protect Alpha information, and achieve non-custodial fund management through Almanak Wallets, allowing 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, and the subscription was oversubscribed. The next steps include releasing the beta version and deploying initial strategies/agents, 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 build agents by specifying trading strategies, personalities, or even tweet styles.
Users can access any dataset, develop financial strategies in minutes, utilizing rich APIs and strategy libraries. 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 liquidity providers with more stability and confidence compared to the volatility of alt:alt trading pairs.
Cod3x also has its own DeFi primitives, such as liquidity AMO (Automated Market Operations) and mini-pools, which enhance liquidity and add more features/DeFi Lego components for agents in its ecosystem.
Other notable projects
getaxal / Gekko Agent—An autonomous product from Axal where agents handle complex multi-step crypto strategies. Gekko integrates autonomous driving features. I am waiting to see how Gekko performs data-driven trades in autonomous mode.
ASYM41b07—often referred to as the 'cheat code for memecoin trading,' ASYM agents can analyze vast amounts of data from blockchains and social media to predict memecoin trends. ASYM has consistently outperformed the market and demonstrated 3-4x 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 yet 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 started to stand out.
In this space, modenetwork is a very active ecosystem, designed to attract high-tech AI x DeFi developers as a Layer 2 network. Mode serves as a base for multiple teams working to develop cutting-edge AI-driven applications:
·ARMA: Autonomous stablecoin mining tailored to user preferences, developed by gizatechxyz.
·Modius: Autonomous agent powered by autonolas, 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 automated rebalancing.
At the core of this ecosystem is MODE, the native token. Holders can stake MODE to earn veMODE, which provides access to airdrops from AI agents, whitelist access to projects, and additional ecosystem benefits. Mode is positioning itself as the center of AI x DeFi innovation, with its influence expected to grow significantly by 2025.
Additionally, danielesesta has garnered significant attention with his DeFAI theory via HeyAnonai. He announced that HeyAnon is developing the following:
·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 has reacted enthusiastically, with the market capitalization of ANON tokens soaring 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 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 changing DeFi by making it smarter, simpler, and more accessible. As the abstraction layer simplifies 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 saying the summer of 2020 was DeFi's summer, it would be more accurate to say that 2025 will be the summer of DeFAI.
