Editor's Note: In this article, jeff discusses how DeFAI (Decentralized Finance + Artificial Intelligence) can simplify, optimize, and enhance the DeFi experience through abstraction layers, autonomous trading agents, and AI-driven dApps. He introduces several emerging DeFAI projects, such as Almanak, Cod3x, and Mode, and emphasizes the role of AI in improving trading strategies and portfolio management.
The following is the original content (edited for readability):
BlockBeats has always been a pillar of Web3. It makes blockchain practical, providing tools for instantly transferring funds globally, investing in on-chain assets, peer-to-peer lending, and stacking strategies across DeFi protocols. This is financial freedom at your fingertips.
More importantly, BlockBeats solves real-world problems. It allows the unbanked to access financial services, removes intermediaries, and operates 24/7, creating a truly globalized, inclusive financial system.
But when we face reality, we realize that BlockBeats is complex, setting up wallets, managing transaction fees, and avoiding scams and rug pulls - this is not suitable for the average person. The constantly expanding L1, L2, and cross-chain ecosystems only make things more complicated. For most people, the barrier to entry is simply too high.
This complexity has limited the growth of BlockBeats, but with the emergence of DeFAI, this is starting to change.
What is DeFAI?
DeFAI (DeFi + AI) makes BlockBeats more accessible. By leveraging AI technology, it simplifies complex interfaces and removes the barriers to mainstream participation. Imagine a world where managing your DeFi portfolio is as easy as chatting with ChatGPT.
The first wave of DeFAI projects is already emerging, focusing on three main 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 BlockBeats 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 the execution of transactions. Platforms like CoWSwap and symm io allow users to obtain the best pricing in decentralized liquidity pools, solving the problem of liquidity fragmentation, but they did not address the core issue: BlockBeats still feels difficult.
Now, AI-driven solutions are filling this gap:
Griffain is the first project to launch a token, currently in early access and invite-only.
Griffain is more versatile, allowing users to perform a range of operations from simple to complex, such as task automation (DCA), meme coin deployment, and airdrops.
Orbit / Grift is the second project to launch a token, with a product aimed at the on-chain BlockBeats experience. Orbit emphasizes cross-chain functionality, as it has already 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 has quickly surpassed Orbit in valuation. Neur positions itself as the co-pilot for Solana, designed specifically for the Solana ecosystem. Neur is supported by the Solana Agent Kit from sendaifun.
The one I personally use is slate ceo, which is still very early and has not yet launched a token, but I really like their automation features. I mainly use it to set up conditional trades, such as if xxxx reaches a $5 million market cap, I'll sell 25% of my position, or if xxx reaches xxxx price, I'll buy $5,000 worth of the token.
AIWayfinder is another interesting project worth keeping an eye on. This is a behemoth created by the PRIME / ParallelTCG team, and it's 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 let an agent do it for you? Autonomous trading agents have taken trading bots to a new level, transforming them into dynamic partners that can adapt, learn, and make smarter decisions over time.
It's 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 over data in the context of their objectives.
They discover patterns and learn to leverage them over time.
They can perform operations that their owners have not explicitly programmed.
This sub-field is rapidly evolving, with early agents potentially being used for entertainment purposes - such as shilling shit coins - but now shifting towards more practical, profit-driven tools that can help users trade more effectively. However, there is still an important challenge: how do you verify that an "agent" is not just a bot, or even a human operating in the background?
This is where the DeAI infrastructure plays a crucial role.
The Role of DeAI in Verifying Agents
Key infrastructures like Trusted Execution Environments (TEEs) ensure that agents can operate securely and without tampering.
For example:
·TEE: Promoted by PhalaNetwork, TEEs provide a secure enclave where data can be processed confidentially. Phala's experiments, such as Unruggable ICO and Sporedotfun, have demonstrated how agents can execute tasks while maintaining data integrity.
·Transparent Execution/Verification Frameworks: Innovations like zkML (Zero-Knowledge Machine Learning) or opML provide verifiability of reasoning and computation. Hyperbolic labs' Proof-of-Sampling (PoSP) is a standout 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 start to manage large TVLs (assume $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 deployed into shit coins.
This field is still in its early stages, but we've already seen some promising projects exploring these verifiability tools. As DeFAI evolves, this is a direction worth watching.
To learn more about the trends in DeAI infrastructure, check out this article:
Top Autonomous Trading Agents I'm Watching
Almanak
Almanak provides institutional-grade quantitative AI agents to users, solving the complexity, fragmentation, and execution challenges in BlockBeats. The platform forks EVM chains to execute Monte Carlo simulations in a live environment, considering unique complexities like MEV, transaction fees, and transaction ordering.
It uses TEEs (Trusted Execution Environments) to ensure the privacy of strategy execution, protecting Alpha information, and non-custodial fund handling through Almanak Wallets, allowing precise delegation of permissions to agents.
Almanak's infrastructure supports the ideation, creation, evaluation, optimization, deployment, and monitoring of financial strategies. The ultimate goal is to have these agents learn and adapt over time.
Almanak raised $1 million on legiondotcc, with oversubscription. Next steps include the release of a beta version and the initial deployment of strategies/agents for beta testers. Observing the performance of these quantitative agents will be very interesting.
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, allowing users to construct agents by specifying trading strategies, personalities, and even tweet styles.
Users can access any dataset, develop financial strategies in minutes, and leverage a rich API and strategy library. Cod3x integrates with AlloraNetwork, using its advanced ML price prediction model to enhance trading strategies.
Big Tony is a flagship agent based on the Allora model, trading in and out of mainstream Bits based on its predictions. Cod3x is working to create a thriving autonomous trading agent ecosystem.
A notable feature of Cod3x is its liquidity strategy. Unlike the common alt:alt LP structure promoted by virtuals io, Cod3x uses a stable coin:alt LP supported by its own cdxUSD, which is a Cod3x-native 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 for agents in its ecosystem.
Other Notable Projects
getaxal / Gekko Agent—Axal's autonomous driving product, where agents handle complex multi-step crypto strategies. Gekko has integrated autonomous driving capabilities. I'm looking forward to seeing how Gekko performs in autonomous mode for data-driven trading.
ASYM41b07—dubbed the "cheat code for memecoin trading" by many, the ASYM agent is able to analyze vast amounts of data from the Blockchain and social media to predict memecoin trends. ASYM has consistently outperformed the market and shown 3-4x returns through backtesting. It will be interesting to see how it performs in live trading.
ProjectPlutus—I just like the name PPCOI
3. AI-Driven Decentralized Applications (dApps)
AI-driven dApps are a promising but still nascent field within the DeFAI space. These are fully decentralized applications that integrate AI or AI agents to enhance functionality, automate, and improve user experience. While this field is still in its early stages, some ecosystems and projects have started to emerge.
Within this space, modenetwork is a very active ecosystem, a Layer 2 network aimed at attracting high-tech AI x DeFi developers. Mode is the home base for multiple teams working on developing cutting-edge AI-driven applications:
· ARMA: Autonomous stablecoin mining tailored to user preferences, developed by gizatechxyz.
· Modius: Autonomous agents supported by autonolas, performing Balancer LP mining.
· Amplifi Lending Agents: Developed by Amplifi Fi, these agents integrate with IroncladFinance, automatically swapping assets, lending on Ironclad, and maximizing yields through auto-rebalancing.
The core of this ecosystem is MODE, the native token. Holders can stake MODE to earn veMODE, granting them access to AI agent airdrops, project whitelists, and more ecosystem benefits. Mode is positioning itself as the center of AI x DeFi innovation, and its influence is expected to grow significantly by 2025.
Additionally, danielesesta has garnered widespread attention through his DeFAI theory via HeyAnonai. He has announced that HeyAnon is developing the following:
· An abstraction layer as a DeFi interface
· DeFi agents for autonomous trade execution
· Research and communication agents to acquire, filter, and interpret relevant data
The market has reacted enthusiastically, with the ANON token's market cap skyrocketing from $10 million to $130 million. Daniele seems to be recapturing 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. As 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 the DeFi summer of 2020, 2025 may well be the DeFAI summer.
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