Author: 0xJeff, Head of Steak Studio; Translation: Jinse Finance Xiaozou
DeFi has always been a pillar of Web3. It is DeFi that showcases the utility of blockchain, providing us with the necessary tools for instant remittances globally, on-chain asset investments, intermediary-free lending, and cross-DeFi protocol strategies. These are all pathways to financial freedom within reach.
More importantly, DeFi solves real-world problems. It enables those without traditional bank accounts to access financial services, eliminates intermediaries, and operates around the clock, creating a truly globally inclusive financial system.
But let's face an obvious question: DeFi is really complex.
Setting up a wallet, managing gas fees, and learning to avoid scams in an environment rife with fraud is not very user-friendly. The growing number of L1, L2, and cross-chain ecosystems only complicates matters further. The entry barrier is too high for most people.
It is this complexity that hinders the growth of DeFi, but DeFAI is beginning to change that.
What is DeFAI?
DeFAI (DeFi + AI) makes DeFi accessible. DeFAI leverages artificial intelligence to simplify complex interfaces, removing the barriers that hinder ordinary people from participating. Imagine a world where managing your DeFi portfolio is as simple as chatting with ChatGPT.
The first wave of DeFAI projects has now emerged, mainly focusing on three areas:
Abstraction Layer
Autonomous Trading Agents
AI-driven dApp
1. Abstraction Layers
The purpose of abstraction layers is to make DeFi more accessible by hiding its complexities behind intuitive interfaces. Abstraction layers support users in interacting with DeFi protocols using natural language commands instead of complex dashboards.
Before the advent of artificial intelligence, abstraction layers like intent-based architectures simplified trade execution. Platforms like CoWSwap and SYMMIO enable users to obtain the best pricing in decentralized liquidity pools, addressing the issue of liquidity fragmentation, but they do not tackle the core issue: DeFi remains daunting.
Currently, AI solutions are filling this gap:
Griffain is the first solution to launch a token, and it is still in the early access phase, where users need to be invited to access it. Griffain is more versatile, allowing users to execute various basic or complex operations such as task automation (DCA), releasing meme coins, and airdropping meme coins by standard.
Orbit / Grift is the second solution to release a token, targeted at on-chain DeFi experiences. Orbit emphasizes cross-chain functionality and integrates over 200 protocols across more than 117 chains, making it the most integrated of the three solutions.
Neur is the third solution to be released, but its open-source nature quickly led to a valuation exceeding that of Orbit. Neur positions itself as a Solana co-pilot designed specifically for the Solana ecosystem. Neur is powered by the SendAI Solana Agent Kit.
I personally use Slate, which is still in its early stages and has not released a token, but I love its automation features. I mainly use it to set conditional trades, like selling 25% of my position if [xxx] reaches a market cap of $5 million, or buying $5,000 worth of tokens if [xxx] hits [xxxx].
Wayfinder Foundation is another interesting application worth watching. It is a behemoth that the PRIME/Parallel team is building.
2. Autonomous Trading Agents
Why spend hours digging for alpha, manually executing trades, and trying to optimize your portfolio when you can let agents do it? Autonomous trading agents are elevating the concept of trading bots to a new level, transforming them into dynamic partners that can adapt, learn, and make wiser decisions over time.
It is worth noting that trading bots are not a new phenomenon. They execute predefined actions based on static programming and have been around for many years. But agents are fundamentally different:
They extract information from an unstructured and ever-changing environment.
They reason about data in the context of their objectives.
They will discover patterns over time and learn to leverage those patterns.
They can perform actions that their creators never explicitly programmed.
This emerging sub-industry is growing rapidly. Initially for entertainment purposes, it has now shifted to practical, profit-driven tools that help users trade more effectively. However, an important challenge remains: how do you verify that an 'agent' is not just a robot or even someone manipulating everything behind the scenes?
This is where the DeAI infrastructure comes into play.
The role of DeAI in verifying agents
Key infrastructures like Trusted Execution Environments (TEEs) ensure that agents operate securely and without tampering.
For example:
TEE: Promoted by Phala Network, TEE provides secure enclaves, and all data is processed confidentially. Phala's experiments—such as Unruggable ICO and Sporedotfun—demonstrate how agents can perform tasks while maintaining data integrity.
Transparent execution/verification framework: Innovative technologies like zkML (zero-knowledge machine learning) or opML provide verifiability for reasoning and computation. Hyperbolic's Sampling Proof (PoSP) is a prominent example. This mechanism combines game theory and sampling to ensure computational accuracy and efficiency in decentralized environments.
Why is this important?
When autonomous agents start handling significant amounts of TVL—imagine $100 million or more TVL—users will have very high assurance demands. They need to understand how agents manage risk, verify the frameworks under which they operate, and ensure their funds do not end up going to just any meme coin.
This field is still in its early stages, but we see some promising projects exploring these verifiable tools. This is something to keep in mind as DeFAI evolves.
Top autonomous trading agent projects I am closely monitoring
As follows:
(1) Almanak
Almanak provides users with institutional-level quantitative AI agents that address the complexities, fragmentation, and execution challenges of DeFi.
The platform forks the EVM chain and executes Monte Carlo simulations in real-world environments, considering unique complexities such as MEV, gas costs, and transaction ordering. It uses TEE (Trusted Execution Environment) to ensure the privacy of strategy execution and the security of alpha insights, and supports non-custodial fund handling through the Almanak wallet, allowing precise permission authorization for agents.
The Almanak 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 LEGION, receiving significant oversubscription. The next steps include a beta release and agent deployment/initial strategies for beta testers. It will be interesting to observe the performance of these quantitative agents.
(2) Cod3x / Big Tony
Cod3x, developed by the Byte Mason team (known for their work on Fantom/SonicLabs), is a DeFAI ecosystem aimed at simplifying the creation of trading agents. The platform provides a no-code development tool that allows users to create agents by specifying trading strategies, personalities, or even tweet styles.
Users can access any dataset and devise financial strategies in minutes using APIs and strategy libraries. Cod3x integrates the Allora network, utilizing its advanced ML price prediction models to enhance trading strategies.
Big Tony is the flagship agent trading based on the Allora model, entering and exiting according to its predictions. Cod3x is working to create a thriving ecosystem of autonomous trading agents.
Notably, Cod3x's liquidity approach. Unlike the common alt:alt LP structures promoted by Virtuals, Cod3x uses a stablecoin driven by Cod3x's own CDP (Collateralized Debt Position) cdxUSD:alt LP structure.
This adds more stability and confidence for LPs (liquidity providers) when providing liquidity compared to the volatility of alt:alt trading pairs.
Cod3x also has its own DeFi primitives, such as liquidity AMOs and Mini Pools, which deepen liquidity and add more functionality/DeFi building blocks for agents in its ecosystem.
Note:
- Axal / Gekko AI—Axal's auto-tuning product, handled by agents, executes complex multi-step crypto strategies. Gekko integrates auto-tuning capabilities. I am eager to see how Gekko performs with the integration of auto-tuning for data-driven trading.
- ASYM—The ASYM agent has been described by many as a 'cheat code' for meme coin trading, capable of analyzing large datasets from blockchain and social media to predict meme coin trends. ASYM has consistently outperformed the market, demonstrating a 3-4x return rate through backtesting. I look forward to seeing its performance in live trading.
- Project Plutus—I really like the name PPCOIN.
3. AI-driven dApp
AI-driven dApps are a promising emerging field in the DeFAI domain. They are fully mature decentralized applications that integrate AI or AI agents to enhance functionality, automation, and user experience. Although this field is still in its early stages, some ecosystems and projects have begun to stand out.
One of the most active ecosystems in this field is the Mode network, designed to attract high-tech AI x DeFi developers. Several teams dedicated to cutting-edge AI use cases are already on Mode:
ARMA: Developed by Giza, it customizes autonomous stablecoin farming strategies based on user preferences.
Modius: An autonomous agent farming Balancer LP, supported by Olas.
Amplifi Lending Agent: Developed by Amplifi, these agents integrate with Ironclad to automatically trade assets, loan on Ironclad, and maximize returns through automatic rebalancing.
At the core of the ecosystem is the native token MODE. Token holders can stake their MODE tokens to receive veMODE, which provides airdrops from AI agents, access to project whitelists, and additional ecosystem benefits. Mode positions itself as an innovation hub for AI x DeFi, expecting its influence to grow significantly by 2025.
Additionally, Daniele stirred excitement by publishing the DeFAI theory through HeyAnon.
He announced that HeyAnon is working on the following:
As an abstraction layer for DeFi interfaces
DeFi agents for autonomous trading execution
Research and communication agents for acquiring, filtering, and interpreting relevant data
Market reaction has been enthusiastic, with the market capitalization of the ANON token soaring from $10 million to $130 million. Daniele seems to have brought back the excitement of TIME Wonderland, but this time with a stronger foundation and clearer vision (hopefully).
In addition to these two ecosystems, many teams are building their own AI dApps. Once the primary ecosystems around these dApps form, I will share more in the future.
Conclusion
DeFAI is transforming DeFi, 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.
It's not a repeat of the DeFAI Summer of 2020, but the DeFAI Summer of 2025!
