"DeFAI" As summer approaches, how will AI reshape the future of DeFi?

Original Title: DeFAI is the New DeFi
Author: Defi0xJeff, Crypto KOL
Compiled by: 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 readability):

DeFi has always been a pillar of Web3. It makes blockchain practical, providing tools to instantly transfer funds globally, invest in assets on-chain, lend without intermediaries, and stack 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 eliminates 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:

1. Abstraction Layers

2. Autonomous Trading Agents

3. 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 instead of 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 of 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 Sendaifun's Solana Agent Kit.

I personally use Slate CEO, which is still in early stages and has not launched a token yet, 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 hits xxxx price.

AIWayfinder is another interesting project worth watching. This is a behemoth created by the PRIME / ParallelTCG team, and it 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 operations that their owners have not explicitly programmed.

This subfield is rapidly evolving; initial agents may have been for entertainment purposes—such as hyping up some junk coins for fun—but have now shifted towards 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 merely a bot and not a person operating behind the scenes?

This is where DeAI infrastructure plays a critical 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 isolated area 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 verifiability for reasoning and computation. Hyperbolic Labs' Proof-of-Sampling (PoSP) is a notable example. This mechanism combines game theory and sampling techniques to ensure computations are 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 in, 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 evolves, 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 by forking EVM chains, 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 a 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 designed to simplify 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 agents handle complex multi-step crypto strategies. Gekko integrates autonomous driving features. I am waiting to see how Gekko executes 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 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 space, 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 automated rebalancing.

At the core of this ecosystem is MODE, the native token. Holders can stake MODE to receive veMODE, granting 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 for DeFi interfaces
• DeFi agents for autonomous trading execution
• Research and communication agents for acquiring, filtering, and interpreting relevant data

The market has responded 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 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 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 would be more accurate to say that 2025 will be the summer of DeFAI.