An in-depth analysis of the narrative evolution of AI+Crypto: An introductory guide to the AI ​​Agent track

AI is developing too fast. The future must be the world of AI. If we add another core element, it must be the world of AI+Crypto.

Today, AI has evolved to a new stage: AI Agent.

AI Agent is worth looking forward to both in imaginary space and in real-life scenarios.

The train of the times is roaring by, and we need to get on board quickly.

I have been learning AI Agent recently. This article records my learning path, hoping to help everyone get started in the AI ​​Agent track.

This article is the first introductory guide to the AI ​​Agent track. It also helps everyone establish an overall cognition and framework understanding. Later, we will continue to delve into the track, continue to improve, and seize the AI ​​wave.

01 What exactly is AI Agent?

Let’s put aside various complex concepts and directly compare the differences between AI Agent and existing large models (such as ChatGPT).

The current large model is more like a powerful "natural language search engine" that can answer questions and provide suggestions, but cannot truly actively make decisions and execute them.

The capabilities of AI Agent go beyond the scope of existing large models and are no longer limited to "data processing", but can complete a complete closed loop from "perception" to "action".

Let’s use an intuitive example: Now if you ask ChatGPT how to invest in Crypto, ChatGPT will give you a bunch of suggestions, but AI Agent can help you track global market information in real time and dynamically adjust your investment portfolio to maximize returns.

From this, we can abstract the concept of AI Agent: AI Agent (artificial intelligence agent) is a software entity based on artificial intelligence technology that can autonomously or semi-autonomously perform tasks, make decisions, and interact with humans or other systems. interactive.

The core difference here is: autonomous action.

How does AI Agent achieve autonomous action?

Through AI, complex logic can be converted into precise conditions (returning True or False according to the context), and then it can be seamlessly integrated into the business scenario.

The first is intent analysis: AI will understand what the user wants to do by analyzing the user's prompt words and context. It not only looks at what the user said, but also considers the user's previous usage records and specific circumstances, and then converts these needs into specific program instructions.

The second is to assist in judgment: AI is like a smart assistant that can analyze some complex problems that are not easy for humans to handle and turn them into simple yes or no answers, or a few fixed options. This not only makes decision-making more accurate and efficient, but also works well with existing business systems.

According to the degree of autonomous action, AI Agent can be divided into two types:

One is that AI Agent is equivalent to a personal assistant and can assist users in handling some business.

The other goes a step further. The AI ​​Agent itself is an independent individual, has its own identity or brand, and provides services to many users.

In short, AI Agent can be said to be the next development stage of large-scale models and a new product form. AI Agent has a lot of room for imagination.

02 What is the relationship between AI Agent and Crypto?

AI and Crypto are not distinct, they can be integrated.

More importantly, the AI ​​Agent of Web2 is different from the AI ​​Agent of Web3.

Web3's AI Agent is a higher-level and more complete AI Agent. It may be called another name: Crypto AI Agent.

With the help of Crypto’s capabilities, AI Agent has more features:

(1) Decentralization

After combining Crypto, the operation, data storage and decision-making process of AI Agent are more transparent and not controlled by a single entity.

Web2 AI Agent These agents are usually controlled by a centralized company or platform, and the data and decision-making process are concentrated in the hands of one or a few entities.

Once an AI Agent provides services to the outside world, there will be trust issues, so the AI ​​Agent needs the running or verification environment provided by the blockchain.

AI Agent also requires barrier-free usage, open and transparent data, interconnection and decentralization.

(2) Incentive mechanism

This is Crypto's strongest empowerment. Through the token economic model, it provides a mechanism to directly encourage developers and users to participate and contribute.

Web2 AI Agent relies primarily on traditional business models such as advertising revenue or subscription services to maintain operations.

Web2 entrepreneurial teams or companies cannot make a profit for a long time, and it is difficult to raise funds; but with Web3, through the issuance of coins, you can directly obtain cash flow to support project development. For example, the use of AI Agent requires Crypto payment.

A free market economy can generate more innovation.

(3) True eternal life

With smart contracts, AI Agents truly achieve “eternal life”.

As long as the smart contract is deployed on the blockchain, the AI ​​Agent can operate automatically according to its rules and can theoretically run indefinitely.

Smart contracts can ensure that the AI ​​Agent's code and decision-making mechanism exist permanently on the blockchain unless there is clear logic to stop or change its behavior.

But the data it relies on may require ongoing updating or maintenance. Without continuous input of data or interaction with the outside world, the AI ​​Agent's "immortality" may be limited to its program logic and is not dynamic.

In short, AI Agent needs Crypto more than Crypto needs AI Agent.

03 Narrative evolution of AI+Crypto

There are two stages from AI to large model to AI Agent. The combination of AI and Crypto can also be divided into two stages:

3.1 Large model stage: infrastructure

AI projects mainly have three evaluation dimensions, computing power, algorithm and data.

In fact, the role of Web3 is to add an incentive system to AI and tokenize computing power, algorithms and data.

Therefore, the combination of AI and Web3 can also be discussed from the three dimensions of computing power, algorithm, and data:

(1) Computational Power:

Distributed computing network: Blockchain is naturally distributed. AI can use Web3's distributed network to obtain more computing resources. By distributing AI computing tasks to various nodes in the Web3 network, more powerful parallel computing capabilities can be achieved, which is especially useful for training large AI models.

Incentive mechanism: Web3 introduces an economic incentive mechanism, such as the token economy, which can motivate participants in the network to contribute their computing resources. Such a mechanism can be used to create a market where AI developers can purchase computing power to perform machine learning tasks, and providers are rewarded with tokens.

(2) Algorithms:

Smart contracts: Smart contracts in Web3 can automatically execute AI algorithms. AI can design algorithms to run as smart contracts on the blockchain, which not only increases transparency and trust, but also enables automated decision-making processes, such as automated market predictions or content moderation.

Decentralized algorithm execution: In the Web3 environment, AI algorithms can not rely on a single central server, but can be verified and executed through multiple nodes. This increases the interference resistance and security of the algorithm and prevents single points of failure.

(3) Data:

Data privacy and ownership: Web3 emphasizes the decentralization of data and user ownership of data. AI combined with Web3 can use blockchain technology to manage data permissions and ensure data privacy. At the same time, users can selectively share data in exchange for rewards, which provides AI with a richer but controlled data source.

Data verification and quality: Blockchain technology can be used for data verification to ensure the authenticity and integrity of the data, which is very critical for the training of AI models. Through Web3, data can be verified before being used, improving the output quality and credibility of AI algorithms.

Data market: Web3 can promote the development of the data market, and users can directly sell or share data to the AI ​​systems in need. This not only provides AI with diverse data sets, but also ensures the liquidity and value of data through market mechanisms.

Through these combination points, AI and Web3 can develop together:

• AI can obtain distributed computing power and high-quality data through Web3, while using smart contracts to improve the execution efficiency and transparency of algorithms;
• Web3 can use AI to enhance the intelligence of its system, such as intelligent resource management, automated contract execution, etc.

Focusing on these three dimensions, many well-known projects have appeared on the market:

Computational Power projects:

• Render Network: Although it mainly focuses on rendering, it can also provide AI computing power.
• Akash Network: Provides decentralized cloud computing resources that can be used for AI needs.
• Aethir: Focus on decentralized cloud computing, which may involve the provision of AI computing power.
• ionet: A decentralized computing platform that supports AI reasoning and training.

Algorithms projects:

• Cortex: A decentralized world computer capable of running AI and AI-driven DApps on the blockchain, focusing on integrating AI into smart contracts.
• Fetchai: A blockchain-based machine learning platform, it launched the code-free management service Agentverse to simplify the deployment of AI agents for Web3 projects.
• iExec RLC: Provides a blockchain-based AI model market that supports confidential computing and decentralized oracles.

Data type projects:

• Vana: Vana is building a DAO for personal genetic data, a data market that allows users to control and potentially benefit from it.
• RSS3: Launched an open source AI architecture that enables any large-scale language model to become a Web3 AI agent, involving data utilization and management.

Comprehensive projects:

• Myshell: A decentralized AI consumption layer designed to connect consumers, creators and open source researchers. It opens a platform where anyone can create, share and monetize their AI-native applications.

Generally speaking, in the large model stage, the combination of Crypto and AI is mainly at the infrastructure level, laying the foundation for the long-term development of AI.

3.2 AI Agent stage: application implementation

The emergence of AI Agent marks the implementation stage of AI at the application layer.

AI Agent can also be subdivided into three development stages: Meme coin stage, single AI application stage and AI Agent framework standard stage.

1. AI Agent Meme Coin

The AI ​​Agent Meme coin is a very special existence, and the Meme coin itself is the product of community sentiment.

AI is developing too fast, and this technology seems to be very profound, making ordinary people very anxious. AI Meme coins give ordinary people the opportunity to participate.

Therefore, AI Meme coins bring an emotional value to holders to participate in the AI ​​revolution, allowing ordinary people to participate in the AI ​​wave.

The final result is: AI + MEME uses the wealth effect to accelerate the market education and dissemination of AI.

Thinking from another perspective, why does the AI ​​Agent issue coins?

On the one hand, it attracts funds and users through the wealth effect, injecting momentum into the subsequent development of the industry; on the other hand, the MEME issuance method itself is a means of community financing, providing cash flow for the development of the project itself.

We can look at the header headings:

• $GOAT: The first popular AI Agent Meme coin;
• $Fartcoin: Attract users’ attention by generating humorous content (such as “fart jokes”);
• $ACT: aims to create a digital ecosystem where users and AI interact equally;
• $WORM: Aims to combine digital biology and blockchain technology to create a unique digital asset that simulates the nervous system of a biological worm;

2. Single AI application

AI Agent is being integrated with various subdivisions of Crypto, showing a situation where a hundred flowers are blooming.

With the development of AI Agent, the tokens issued by AI Agent are no longer pure Meme coins. With the support of actual use scenarios, they gradually have the attributes of value coins.

(1) Creation Project

• ai16z: The first AI Agent to break out of the industry, and established the first framework standard Eliza.

(2)Agent Gaming

• ARC: An AI framework called RIG was developed based on the Rust language to support decentralized applications (dApp) and smart contracts.
• FARM: Focus on using AI to improve the realism and strategic depth of farming games.
• GAME: $GAME empowers the autonomous operation and intelligence of AI agents, and deeply integrates AI and games.

(3)Agent DeFi

• $NEUR: Focus on token analysis and DeFi interaction, providing intelligent financial decision support.
• $BUZZ: Provides a natural language interface to enable users to conduct DeFi transactions and management more intuitively.

(4) Code audit

• AgentAUDIT: Use AI technology to automate code audits and improve code security and quality.

(5)Agent data analysis

• REI: Conduct large-scale data analysis through AI technology to provide insight and prediction services.

(6) Autonomous AI Agent

• LMT: An AI Agent that learns and performs tasks autonomously, aiming to reduce human intervention.
• GRIFFAIN: An AI Agent that can autonomously optimize its own behavior, especially for decision-making and strategy formulation in complex environments.

3. AI Agent framework standard

The AI ​​Agent framework standards are still in a state of chaos.

What is the AI ​​Agent framework standard?

The AI ​​Agent framework standard simplifies the development and deployment process of AI Agent by providing a unified set of specifications and tools.

It allows developers to create an AI Agent that can interact with multiple clients (Twitter, Discord, Telegram, etc.), extend functionality through plug-ins, and leverage AI technology to enhance its intelligence.

These standards and basic libraries (such as memory storage, session isolation, context generation, etc.) ensure that the operation of AI Agent is efficient, safe and user-friendly

By connecting various AI platform interfaces, framework standards further enhance the capabilities of AI Agents, enabling them to utilize the latest AI technology to provide better services.

In short, the AI ​​Agent framework standard is infrastructure and platform, and it can form its own ecology. The narrative space is naturally higher than that of a single AI application.

AI Agent framework standards mainly include the following:

• ai16z: Built the Eliza framework to support multiple platforms such as Discord, Twitter, Telegram, etc., allowing AI Agents to seamlessly integrate with these platforms.
• Virtual: The GAME framework is built, specifically designed for games and virtual environments, allowing AI Agents to operate autonomously or interact with players in these environments.
• swarms: a multi-agent AI framework. Based on its framework, developers can create and manage multiple AI agents. It is suitable for scenarios that require high-complexity coordination, such as simulating social behavior, complex business process automation, or large-scale data processing. .
• ZEREBRO: Built the ZerePy framework, which is equivalent to Optimism's OP Stack, making it easier and standardized to develop and deploy single AI applications, allowing these agents to independently create and distribute content on social platforms.

Related ecologies have emerged around these frameworks. We need to focus on these ecologies when studying related projects.

04 Summary

The AI ​​Agent narrative has begun to explode.

Every year in our industry, a main narrative breaks out. Around this main narrative, many star projects will emerge, and naturally there will be many opportunities.

For example, DeFi Summer in 2020, Inscription Summer in 2023, Meme Summer in 2024, and AI Summer is emerging in 2025.

Don't waste every rare opportunity to make wealth.