When we hear about the integration of AI and the crypto market, the projects that receive the most attention are those that address data collection, GPU computing, or data inference problems in the field of AI. These protocols include Akash Network, Ritual net, and others. They stand out in the large AI industry by leveraging the decentralized, incentivized, censorship-resistant, and privacy advantages provided by web3.
While these projects create engaging applications, their impact on ordinary web3 users is still limited, and they have not effectively brought new users into the web3 space.
The Rise of AI Agents
With the rapid development of Web3, new crypto protocols, tokens, and applications are emerging constantly. Even the most experienced users find it challenging to cope with this complexity. Therefore, there is a growing need for creating AI agents, intelligent assistants designed to simplify the use of crypto applications. AI agents sit at the intersection of cryptocurrencies and artificial intelligence, aiming to solve the complex user experience issues in the crypto space. Imagine a future where you only need to tell an AI agent what task you want to accomplish on the blockchain, and it will automatically write and execute the necessary transactions for you.
AI agents will help us build an intelligent layer on top of the existing DeFi infrastructure, acting as bankers, investors, traders, and fund managers in the web3 world. They will leverage underlying technologies to conduct transactions on the blockchain.
The integration of DeFi and AI is expected to bring advanced applications such as AI-driven lending, smart liquidity mining strategies, automated market making, and AI-assisted portfolio management. The applications of AI agents are not limited to this; they can also be used in the gaming industry to provide users with assistants and pets to enhance their gaming experience.
Based on the types of use cases and value addition brought by the protocols, the evolving AI agent space can be broadly categorized as follows:
1. Gaming AI Agents:
Teams like Parallel Colony are developing gaming AI agents to enhance the user gaming experience. These AI agents run in a Web3 environment and interact with players and game elements through on-chain smart contracts. AI agents can act on behalf of users or serve as pets/assistants within the game. These agents can also interact with other agents and trade assets.
While some web2 and web3 games are actively using AI to design dynamic non-playable characters (NPCs) in the game, this article focuses only on AI agents that can trade and act on behalf of users.
2. Autonomous Portfolio Agents:
These AI agents can manage asset pools from different users. The goal of AI agents is to maximize returns by allocating assets to various DeFi strategies, leveraging off-chain AI data streams. This is essentially an investment portfolio management service that utilizes the power of AI. To ensure minimal trust in the protocol, some projects enable on-chain AI inference proofs through protocols like Modulus.
3. Prompt-based AI Agents:
Imagine a future where you only need to tell an AI agent what goal you want to achieve on the blockchain, and it will automatically write and execute the necessary transactions.
This is the goal of most AI agent projects, and we can envision prompts becoming the preferred way for regular users to interact with the blockchain.
Projects like Wayfinder, Brian Knows, and Aperture Finance are developing interfaces similar to ChatGPT, where users can directly perform intelligent transactions on the blockchain by chatting with AI agents. These protocols leverage large language models (LLMs) to convert user prompts and intentions into executable transactions.
Now let’s discuss some of the AI agent protocols in detail:
1. Autonolas Agent:
Autonolas is a platform that supports the creation and management of autonomous agent services. These services, called proxy services, run off-chain as a multi-agent system (MAS) that collaboratively achieves common goals. Autonolas enables developers to build and deploy autonomous agents that seamlessly collaborate off-chain while leveraging blockchain technology to enhance on-chain functionality.
2. BabyDegen:
This is an example of such an agent. (Catalog of other agents built on Olas Network)
3. AutoTX by Polywrap:
Polywrap is building a network of professional AI agents to perform complex tasks for web3 users and protocols. These agents efficiently solve problems and make decisions by leveraging crowdsourced insights, on-chain and off-chain data sources, task planning, and batch transactions. The current agents include payment, market research and trading, social content curation, prediction, and public product funding. Polywrap’s future plans include expanding the scope of professional agents, decentralizing their execution, and developing the system through community-driven governance. AutoTx is an example of such an AI agent.
AutoTx can translate advanced user goals into a series of blockchain transactions. This means that you no longer need to be an expert in each protocol or spend hours learning how to manually write different types of transactions. Just tell AutoTx what you want to achieve, and it will take care of the rest.
4. Parallel Colony:
Parallel Studios takes a fresh approach to AI agents through Colony, a new AI-driven web3 survival game. In Colony, highly autonomous AI agents or “avatars” continuously learn from the environment. Players must guide these avatars with different skills and abilities and collaborate with them to survive in competing colonies on a future Earth.
Colony stands out by incorporating continuous learning into its gameplay. The AI avatars develop unique personalities and worldviews, learning from their own experiences, identities, and goals. Additionally, these avatars can autonomously manage digital assets through dedicated web3 wallets, allowing them to trade with other in-game avatars.
5. Wayfinder:
Wayfinder is creating a “map” for AI agents to handle tasks and simplify users’ on-chain activities. By incentivizing builders through open-source development and the $PROMPT token, Wayfinder aims to expand the navigation instruction network. Wayfinder’s paths will continuously enhance the capabilities of AI agents, making them more intelligent over time. It aims to connect blockchain and off-chain data sources, enabling users to easily perform tasks through command prompts. Their innovation aims to make blockchain interactions more efficient and accessible, improving users’ lives by reducing complexity and stress. You will find this analogy and explanation by @tiggity_tc on Wayfinder interesting. (Reference to a video of Wayfinder agent running, and reference to whitepaper)
6. Noya:
Noya is a decentralized finance (DeFi) protocol that enables AI agents to manage liquidity across multiple blockchains securely and accurately. It uses a composable system built from scratch, including a private gatekeeper network, an AI-compatible oracle, and a competitive environment for AI and strategic managers. Noya has multiple treasuries, each configured for different user intent profiles. The protocol has its own-designed AI oracle to read various DeFi markets and pass information to AI agents.
Noya’s infrastructure supports various functionalities, such as liquidity provisioning, leverage management, and lending rate optimization, using advanced technologies like Zero-Knowledge Machine Learning (ZKML). It aims to set new standards for holistic liquidity management and financial strategy. The team is rolling out access to the protocol.
7. Brian Knows:
Brian provides an API that developers can integrate into their applications, enabling users to generate web3 transactions through prompts, such as “Can you swap 10 USDC for ETH on Uniswap on the Ethereum mainnet?” They also offer smart contract deployment services through prompts. On the backend, the team uses LLM to convert prompts into web3 transactions and executes them through their preferred protocols and solvers.
The team has also developed a Brian application where you can explore the feature set. They aim to expand their services by offering features such as recurring and automated payment setups to users.
8. Aperture Finance:
Aperture Finance revolutionizes DeFi by providing liquidity management services through a user-friendly protocol. It aims to enhance the DeFi user experience by incorporating a GPT-inspired intuitive chatbox interface, allowing users to express their goals in natural language. Third-party participants, called solvers, handle requests by optimizing the process to ensure efficient and cost-effective execution.
9. Fungi Agent:
Fungi offers a self-custodial AI agent experience by leveraging the powerful capabilities of smart accounts and account abstraction. Fungi allows users to issue command prompts through its interface, which then processes real-time blockchain data and autonomously performs actions based on user instructions.
Users can chat with Fungi to deepen their understanding of cryptocurrencies, receive personalized guidance, execute on-chain transactions, create custom DeFi strategies (Hyphas), and even profit by sharing these Hyphas with the community. Fungi is a network of agents that interact with each other and learn from past experiences, creating a financial superintelligence available to everyone. Here’s how Fungi Agent works.
10. Fyde Protocol:
Fyde enables users to increase their cryptocurrency holdings faster by depositing into diversified AI-managed treasuries that lock in yields based on market performance and reduced volatility and reallocate assets. Users can deposit various tokens into these treasuries and receive $TRSY, a token representing their share in the treasury assets. Fyde aims to maintain the liquidity of $TRSY in various market conditions, enabling users to trade with ease.
The Need for an AI Identity Verification Layer
In all these upcoming AI and intent-related projects, the potential use cases range from handling simple tasks to authorizing AI agents to execute complex DeFi strategies for optimal returns. However, these AI agents face two main challenges:
1. They cannot achieve true autonomy: Currently, AI agents can recommend on-chain actions and prepare transactions for users but still require user signatures or approvals.
2. If they choose automation, they lose security: Protocols tend to explore alternative solutions to automation, such as approvals, centralized treasuries, shared private key pairs, etc., which make the protocol custodians of your assets and bring significant risks.
We need to provide AI with guardrails in the form of user-defined permissions – strictly defining the operations AI is allowed to sign and those it is not authorized to sign. Therefore, we need a solution that can delegate transaction authorization to AI agents but restrict them to specific permissions and rules. (Reference to an image)
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