Exploring in depth: Analysis of various types of AI agents and potential projects

Original author: Biconomy

Original translation: DeepPool TechFlow

When we hear about the integration of AI and the cryptocurrency market, the projects that receive the most attention are those networks that address data collection, GPU computing, or data inference problems in the field of AI. These protocols include Akash Network, Ritual net, etc. They stand out in the large AI industry by leveraging the advantages of decentralization, incentives, censorship resistance, and privacy provided by web3.

While these projects create engaging applications, their impact on the average web3 user is still limited and they are not effective in bringing 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 difficult to cope with such complexity. As a result, there is a growing demand for creating AI agents, intelligent assistants designed to simplify the use of crypto applications. AI agents sit at the intersection of cryptocurrency and artificial intelligence, aiming to address the complex user experience issues in crypto. Imagine in the future, you only need to tell the AI agent what task you want to accomplish on-chain, and it will automatically write and execute the necessary transactions for you.

AI agents will help us build an intelligent layer on the existing DeFi infrastructure, which will be equivalent to bankers, investors, traders, and fund managers in traditional finance in web3. They will use underlying technology to trade on-chain.

DeFi and AI integration 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, allowing users to have assistants and pets to help them better experience the game.

Based on the use case types and value-added brought by the protocol, the continuously evolving AI agent field can be roughly divided into the following categories:

Classification of AI Agents

Game AI Agent:

Teams like Parallel Colony are developing game AI agents to enhance the gaming experience for users. 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 in the game. These agents can also interact with other agents and trade assets.

Some web2 and web3 games are also actively using AI to design dynamic non-playable characters (NPCs) in the game. But this article only focuses on AI agents that can represent users for trading and actions.

Autonomous Investment Portfolio Agent:

These AI agents can manage asset pools from different users. The goal of AI agents is to allocate assets to various DeFi strategies by utilizing off-chain AI data streams, in order to maximize returns. This is actually a kind of investment portfolio management service that utilizes AI capabilities. To minimize trust in the protocol, some projects also enable on-chain AI inference proofs through protocols such as Modulus using zero-knowledge proofs (ZK).

AI Agent Based on Clues:

Imagine a future where you only need to tell the AI agent what goals you want to achieve on-chain, and it will automatically write and execute the necessary transactions for you.

This is the goal of most AI agent projects, and we can imagine that in the future, prompts may become the preferred way for ordinary users to interact with the Block 01928374656574839201.

Projects like Wayfinder, Brian Knows, Aperture Finance, etc. are developing interfaces similar to ChatGPT, allowing users to directly conduct intelligent transactions on-chain by chatting with AI agents. These protocols utilize Large Language Models (LLMs) to translate user prompts and intentions into executable transactions.

Let's discuss some AI agent protocols in detail:

Autonolas Agent

Autonolas is a platform that supports the creation and management of autonomous proxy services. These services, known as proxy services, operate independently off-chain as a Multi-Agent System (MAS), collaborating to achieve common goals. Autonolas enables developers to build and deploy autonomous proxies that seamlessly collaborate off-chain while leveraging blockchain technology to enhance on-chain functionality. BabyDegen is an example of such a proxy. (A directory of other proxies built on the Olas Network)

AutoTX developed 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 using crowdsourced insights, on-chain and off-chain data sources, task planning, and batch transactions. Current agents include payment, market research and trading, social content planning, prediction, and public product financing. Polywrap's future plans include expanding the scope of professional agents, decentralizing their execution, and developing the system through community-driven governance. AutoTx is such an AI agent.

AutoTx can convert high-level user goals into a series of blockchain transactions. This means 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 let it handle the rest.

Parallel Colony

Parallel Studios has taken 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 their environment. Players must guide these avatars with different skills and abilities and cooperate with them to survive in competitive colonies on future Earth.

Colony stands out by integrating continuous learning into its gameplay. AI avatars develop unique personalities and worldviews by learning from their own experiences, identities, and goals. In addition, these avatars can autonomously manage digital assets through dedicated Web3 wallets, allowing them to trade with other in-game avatars. (Reference: White Paper)

Wayfinder

Wayfinder is creating a "map" for AI agents to handle tasks and simplify users' on-chain activities. By open-source development and incentivizing builders with $ tokens, Wayfinder will expand the network of navigation instructions. Wayfinder's paths will continuously enhance the capabilities of AI agents, making them smarter over time. It aims to connect blockchain and off-chain data sources, allowing users to easily execute tasks through a command prompt. Their innovation aims to make blockchain interactions more efficient and accessible, improving users' lives by reducing complexity and pressure. You will like this analogy and explanation by @tiggity_tc on Wayfinder. (Reference video of Pathfinder Agent in operation & White Paper reference)

Noya

NOYA is a decentralized finance (DeFi) protocol that enables AI agents to manage the liquidity of multiple blockchains securely and accurately. It uses a composable system built from scratch, including a private guardian network, an AI-compatible oracle machine, and a competitive environment for AI and strategic managers. Noya has multiple treasuries, each tailored to different user intent profiles. The protocol has its own designed AI oracle to read various DeFi markets and communicate the information to AI agents.

NOYA's infrastructure utilizes advanced technologies such as Zero-Knowledge Machine Learning (ZKML) to support various functions including liquidity provisioning, leverage management, and optimization of borrowing interest rates. It aims to set new standards for end-to-end liquidity management and financial strategy. The team is rolling out access to the protocol.

Brian Knows

Brian provides developers with an API that can be integrated into their applications, allowing users to generate web3 transactions through prompts, such as "Can you exchange 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 then integrates the execution of these transactions through their preferred protocol and resolver.

The team has also developed a Brian application where you can explore the feature set. The team aims to expand their services by offering features such as regular and automatic payment settings to users.

Aperture Finance

Aperture Finance provides liquidity management services through user-friendly protocols, completely changing DeFi. It aims to enhance the DeFi user experience through an intuitive chat box interface inspired by GPT, allowing users to express their goals in natural language. Third-party participants (referred to as solvers) optimize the process to handle requests, ensuring efficient and cost-effective execution.

Fungi Agent

Fungi uses the powerful capabilities of intelligent accounts and account abstractions to provide a self-hosted AI agent experience. Fungi allows users to instruct command prompts through its interface, process real-time blockchain data, and autonomously execute operations based on user instructions.

Users can chat with Fungi to deepen their understanding of cryptocurrency, get 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 - a financial superintelligence that anyone can use. Here's how the Fungi Agent works.

Fyde Protocol

Fyde allows users to increase their cryptocurrency holdings more quickly by depositing into a diversified AI-managed vault, which locks in returns based on market performance and reduced volatility, and reallocates assets.

Users can deposit various tokens into these vaults and receive $TRSY, which is a token representing their share of assets in the vault. Pyro aims to maintain the liquidity of $TRSY under various market conditions, enabling users to trade easily.

The demand for smart agents on the 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 to find the best returns. However, these AI agents face two main challenges:

• They cannot achieve true autonomy: Currently, AI agents can recommend on-chain operations and prepare transactions for users, but still require users to sign or approve.
• If you choose automation, they will lose security: Protocols tend to explore alternative solutions for automation, such as approvals, centralized treasuries, shared private key pairs, etc., which make the protocol the custodian of your assets and bring significant risks.

We need to provide a fence for AI in the form of user-defined permissions—strictly defining the operations that 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 only within specific permissions and rules.

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