Source: OKX Ventures

This article is the "next" of this report, focusing on the analysis of AI segmented tracks and typical projects.

To better achieve value capture, we will conduct project evaluations based on the following frameworks, covering whether it is open source, key differentiating factors with existing AI protocols, long-term revenue channels, and Multiple evaluation items such as agency transaction volume in the ecosystem.

Project Evaluation Framework

Evaluation Item

Definition

Evaluation Points

Importance

< p>Open Source

Whether the project discloses its source code, allowing community review, contribution and secondary development.

- Source code accessibility (such as disclosure on platforms such as GitHub)- Community contribution activity- Types of open source licenses and their impact on project development

Open source projects usually have higher transparency and security, which can attract more developers and users to participate and promote the long-term development of the project.

Key Differentiators (Key Differentiators)

The unique advantages of the project in technology, functionality or market positioning compared to existing AI protocols.

- Technological innovations (such as unique algorithms, architectural design)- Improvement of functional integration and user experience- Differentiation of market positioning and target user group

Differential factors determine Can the project stand out in a highly competitive market and attract the attention of users and developers.

Types of Agents in Ecosystem will be generated in the ecosystem

The different types of AI agents and their application scenarios will be born in the project ecosystem.

- Functions and uses of agents (such as wallet management, token trading, NFT minting, etc.)- Customization and scalability of agents- Collaborative work capabilities between agents

Rich A variety of agent types can meet the needs of different users and enhance the vitality and attractiveness of the ecosystem.

Long-term Revenue Channels and Agentic Transaction Volumes

The long-term profit model of the project and the transaction volume generated by agents within the ecosystem .

- Token Economic Model and Its Incentive Mechanism-Main Source of Income (such as transaction fees, subscription services, value-added services, etc.)-Growth Potential of Agent Trading Volume and Its Impact on Income

< p>Stable and diversified revenue channels are the key to the sustainable development of projects, and high transaction volume can enhance the value of tokens and project influence.

GPU configuration andLifecycle (GPU Configuration and Lifecycle)

The hardware resource configuration required by the project in the operation of the AI ​​agent and its long-term sustainability.

- Current and future GPU requirements and configurations- Scalability and cost-effectiveness of hardware resources- The degree of dependence of the project's technical architecture on hardware resources

Efficient hardware configuration and rationality Resource planning can ensure the technical stability and expansion capabilities of the project and support its long-term development.

Ability to Attract Mindshare and Team's Understanding of AI Agent Attention Mechanisms

Projects attract in markets and communities The ability to focus, and the team's understanding and application of AI agents in user attention management.

- Project marketing strategy and brand building - Team members’ professional background and experience in the fields of AI and blockchain - Team’s insight into user needs and behaviors

Strong Brands and efficient marketing can improve project visibility and user base. At the same time, the team's understanding of AI agent attention mechanism can optimize user experience and improve user stickiness.

Developer Share Consideration

Whether the project provides incentives and support for developers to promote the continuous improvement and innovation of the feature set.

- Developer incentive mechanism (such as token rewards, contribution recognition, etc.)- The activity and participation of the developer community - Project support for developer tools and resources

Development The author is the key force in project innovation and function expansion. A good developer incentive mechanism can attract more outstanding developers to participate and promote the continuous progress of the project.

1. DeFAI

DeFAI combines the advantages of DeFi and AI, aiming to simplify the complex operations of DeFi and enable ordinary users to easily use these financial tools. Through the introduction of AI technology, DeFAI can automate complex financial decision-making and transaction processes, lower the technical threshold for users, and improve operational efficiency and intelligence level. Although the current market size of DeFAI is less than US$1 billion, far lower than the US$110 billion in the DeFi market, this also means that DeFAI has huge growth potential.

1. Griffain: The AI ​​application store of Solana ecosystem

Griffain is an AI proxy engine built on the Solana blockchain, aiming to simplify cryptocurrency operations through natural language interaction and integrate wallets. Management, token trading, NFT minting and DeFi policy execution and other core functions. The project was founded by Tony Plasencia and was initially proposed in the Solana Hackathon and supported by Solana founder Anatoly Yakovenko. As the first high-performance abstract AI proxy in the Solana ecosystem, Griffain combines natural language processing (NLP) technology to provide a user experience similar to Copilot and Perplexity, promoting the evolution of AI-driven on-chain interaction mode.

Griffain uses Shamir Secret Sharing (SSS) technology to split wallet keys to ensure the security of user assets. Core functions include natural language trading instructions (support DCA, limit orders, etc.), AI agent collaborative tasks execution, market analysis (data analysis of position distribution and other data), as well as token issuance and NFT minting that integrates the pumpfun platform. At the same time, the platform provides personalized AI agents, where users can adjust instructions according to their own needs and perform on-chain tasks; special AI agents are optimized for specific tasks such as airdrop, transaction sniper, and arbitrage. Griffain enhances the operability and user experience of the Solana ecosystem through these diversified features.

At present, Griffain is in the invitation-based access stage, and only users who hold Griffain Early Access Pass or Saga Genesis Token are allowed to participate, and adopt the SOL billing model, covering transaction fees, agency service fees, etc. The platform's AI agent can provide value-added services such as market analysis, trading signals, automatic trading strategies, etc. Users holding Griffain tokens can unlock more advanced features. As a pioneer of Solana's ecological AI agents, Griffain aims to promote the "Agentic App SZN" wave and will continue to deepen the application of AI technology in the fields of on-chain transactions, market analysis and DeFi in the future, providing users with a smarter and more efficient encryption experience.

2. AI Influencer

AiDOL is a typical representative of the trend of AI Influencer. AiDOL combines AI-generated content (AIGC), virtual image modeling and interactive live broadcast technology to create an influential AI idol ecosystem. Among them, Luna is the most popular AI agent, attracting a large number of fans with its highly intelligent interactive and personalized content; Iona and Olyn also attracted a large number of users with their unique style and innovation. AiDOL takes TikTok live broadcast as its main stage, and relies on high-quality short videos and real-time interactive live broadcasts generated by AI, in a short time672,100 subscribers have accumulated and nearly 10 million likes, becoming a major player in the AI ​​impact economy.

2. Aixbt: Automated AI influencer

Aixbt is an AI-powered crypto market agent launched in November through Virtuals and led by Alex, a developer with the pseudonym @0rxbt. . Alex has focused on analytical tools development since 2017 and has explored AI Agents-related applications since 2021. AIXBT is the only tokenized project attributable to developers, 14% tokens are held by Alex and locked for 6 months, and will be used for team expansion and project development in the future. The team has hired UI/UX engineers to optimize terminal functionality and introduced AI researchers to enhance agent intelligence. AIXBT relies on the meta-llama/Llama-3-70b-chat-hf model to realize dialogue-based AI, situational awareness, emotion analysis and retrieval enhancement generation (RAG) capabilities to ensure efficient and accurate information processing.

AIXBT aims to create a fully automated AI influencer that monitors Crypto Twitter and market trends in real time through intelligent analytics tools, providing users with data-driven market insights and investment advice. Its core functions include KOL monitoring (covering 400+ key opinion leaders), blockchain data analysis, market trend forecasting, and automation technology analysis and strategic recommendations. In addition, AIXBT publicly shares some of the analytical content through Twitter, while in-depth reports are only accessible by coin holders. Users can also directly interact with AI through exclusive terminals to obtain personalized investment advice and risk assessment reports. Daily, AIXBT publishes market insights at a fixed frequency and automatically responds to more than 2,000 mentions to efficiently interpret market sentiment and narrative trends.

AIXBT provides two main ways of use: one is that users can ask questions on X (Twitter). If you query token adaptability or project indicators, AI will analyze and feedback immediately; the other is Aixbt Terminal Advanced Terminal, positioned as a "market intelligence platform driven by narrative analysis", provides more in-depth data analysis and strategic advice. At present, this terminal is only open to users who hold $AIXBT tokens above 600K, and will expand its coverage in the future to meet market demand.

3. Dev Utility

Dev Utility refers to tools or functions that provide developers with convenient and productivity improvements, especially in the fields of AI, blockchain and Web3. It covers basic development tools such as code editor, debugging tools, version control, automation tools, etc., and also includes AI SDK, API and smart contract development framework related to blockchain development. In the field of AI & Web3, Dev Utility may also involve technologies such as AI agent-assisted analysis, retrieval enhancement generation (RAG), to help developers build applications more efficiently. Its core value lies in improving development efficiency, optimizing workflows, and reducing development difficulties, so that developers can focus on core business logic.

3. SOLENG: Code "review"

SOLENG ( @soleng_agent) serves as a solution engineering and developer relationship agent to bridge the technology team and the broader project needs. The gap. Its core function is to automatically review the code submitted by participating projects in Hackathon and provide preliminary review opinions. Although robot audits cannot completely replace human labor, SOLENG, as a "jury", can effectively filter obvious errors and improve review efficiency.

The project has been publicly reviewed on GitHub (link), demonstrating the role of SOLENG in the Hackathon review process. In addition to basic pros and cons analysis, SOLENG also checks for code spelling errors and provides correction suggestions to make reviews more practical. This model meets the needs of Hacksone and provides developers with immediate feedback.

The developer behind SOLENG is Lost Girl Dev, whose identity echoes the virtual female image of the project. Her technical abilities have been followed by ai16z official account and have a record of interaction with Shaw on the X platform, further enhancing SOLENG's industry influence.

4. Investment DAO: Intelligent Investment Research

Investment DAO provides users with more refined investment analysis services through the "Investment Research" AI agent. Its core functions include automatic interpretation of K-line charts, assisting technical analysis, evaluating whether the project has Rug risks, and generating a summary of information similar to research reports. This AI-driven intelligent investment research model lowers the analysis threshold for users, allowing investors to gain market insights more efficiently and provide strong support for decision-making.

4. VaderAI: AI Agent Invest in DAO

VaderAI aims to become the "Black Rock" in the Agentic economy, attract and promote it through its autonomously traded AI Agent tokens. To its followers. The platform builds a versatile AI Agent investment ecosystem by making profits by investing and airdropping profits to holders and followers. Its core goal is to build itself into a leading AI Agent investment DAO management platform to promote industry innovation and scalability.

VaderAI promotes the integration of technology and capital through multi-agent systems, and is committed to building aInvestment DAO eco-network managed by AI Agent. In this network, agents can not only raise funds and manage capital, but also hire other agents to optimize investment strategies and improve the efficiency and flexibility of the system. Through decentralized computing, agents can also reinvest in R&D to promote the sustainable development of the platform.

In addition, VaderAI adopts an innovative token incentive mechanism to provide investors with B2B tool optimization and enhance the platform's commercial application value. The platform also further consolidates investors' sense of participation and interest sharing mechanism by sharing GP/carry profits with holders, making VaderAI not only an investment platform, but also a win-win ecosystem for agents and investors.

5. Content & Creator

Whether it is writing, editing, or visual design, AI can provide personalized creative output according to user needs, helping creators save time, improve productivity, and in intense Stand out of the market competition. The goal of this platform is to provide content creators with an intelligent and convenient creative assistant to promote the innovation and development of the content industry.

5. ZEREBRO: AI Art Creation and Content Generation

ZEREBRO is a blockchain-based cross-chain natural intelligence autonomously operated AI agent, focusing on In artistic creation and content generation. Its innovation combines multiple fields such as decentralized verification, meme generation, NFT casting, DeFi applications, etc., showing strong versatility and execution. ZEREBRO has successfully run the Ethereum mainnet verification node and sells artwork on Polygon, accumulating important assets for its economic base.

ZEREBRO is also committed to building a decentralized computing network and implementing MEV optimization strategies to ensure economic and technological sustainability. It is not only a technical tool, but also explores the in-depth participation of proxy technology in blockchain operations, economic models and governance. ZEREBRO promotes its value manifestation in a decentralized ecosystem through multiple dimensions.

ZEREBRO tokens have two main uses: one is to serve as a content interactive reward, and token holders can earn by participating in decentralized content on social platforms; the other is to serve as a community development tool, Reward users who actively participate in the ecosystem, including content creation, pledge and governance, and further enhance their community activity and sense of participation.

VI. Gaming & Agentic Metaverse

Gaming & Agentic Metaverse is exploring AI-powered gaming and meta-universe experiences, committed to creating a virtual world where humans and agents interact through reinforcement learning. This newXingtian combines artificial intelligence and immersive gaming environments, allowing players to dynamically interact with smart agents and experience more personalized and intelligent gameplay.

6. ARC: AI solution provider

ARC solves player mobility problems in independent games and Web3 games through AI technology. The project has been upgraded from a single gaming studio (AI Arena) to an integrated AI solution provider, launching ARC B2B and ARC Reinforcement Learning (ARC RL). ARC B2B is an AI-powered game development toolkit (SDK) that can be seamlessly integrated into various games to provide developers with an intelligent gaming experience. ARC RL uses crowdsourcing game data to train "super smart" game agents through reinforcement learning to improve the playability and sustainability of the game. ARC's business model is deeply bound to integrated game studios, with revenue sources including token allocation in Web3 games and royalty payments based on game performance, while establishing generalized AI data reserves across game types to promote the training of generalized AI models and Evolution.

ARC's technical applications cover multiple core modules. AI Arena is a cartoon-style AI competitive game where players train AI warriors to fight. Each character is NFT, enhancing the strategic and economic value of the game. The ARC SDK enables developers to easily integrate AI agents and deploy models with just one line of code. ARC is responsible for back-end data processing, training, and deployment. ARC RL improves AI training efficiency through offline reinforcement learning, allowing agents to learn from human players' data, thus providing more natural and challenging game opponents. ARC's AI model architecture covers feedforward neural networks, table agents, hierarchical neural networks, etc. to adapt to the interactive needs of different types of games, and at the same time optimizes the state space and action space to ensure the smoothness and intelligence of the game experience.

ARC's market covers two major areas: independent games and Web3 games, helping developers solve early player liquidity problems and enhance the long-term attractiveness of the game. The core members of the team have rich experience in machine learning and investment management. In 2021, they received a seed round of financing of US$5 million led by Paradigm, and in 2024, they received another US$6 million in follow-up financing. ARC's native token NRN has experienced a transformation from a single game economy (AI Arena) to a platform economy, adding demand drivers such as integration revenue, Trainer Marketplace fees and ARC RL participation in staking, ensuring the sustainability and value growth of the token. Through the crowdsourcing data contribution mechanism, ARC RL realizes multi-player collaborative training, promotes the intelligent evolution of AI agents, and further strengthens the vitality and competitiveness of the gaming ecosystem.

7. Framework & Hubs

When developing AI Agents in the field of encryption, many frameworks are suitable forBasic projects or toy-level applications, but in real product development, there are often problems of insufficient customization and overly abstract and complexity, which makes developers not only need to spend a lot of extra effort on debugging, but also find it difficult to expand and apply flexibly. The core pain points that an excellent Agent framework needs to solve include: comprehensive support for on-chain operations, and APIs that can efficiently integrate on-chain data, DeFi automation, NFT and other key application scenarios; multi-platform compatibility, supporting major blockchain and social platforms. , realize the integration of user operations; modularity and flexibility, abstract basic functions, such as vector storage and LLM model switching, allowing developers to flexibly adapt to different needs and avoid repeated development; memory and communication capabilities, although some frameworks are invested A large number of resources improve this capability, but excessive intelligence may not be practical at the current stage, but instead increase complexity.

The following is a detailed comparison of the mainstream encryption AI Agent framework in various dimensions:

7. Eliza ($AI16Z): AI Agent framework

Eliza ( $AI16Z) takes the lead in the AI ​​agent market, attracting a large number of developers with approximately 60% market share and a strong TypeScript ecosystem. Its GitHub project has accumulated more than 6,000 Stars and 1.8K Forks, fully demonstrating the high level of community participation. Eliza is known for its multi-agent system and cross-platform integration, and supports mainstream social platforms such as Discord, X (Twitter), Telegram, making it an important participant in the fields of social AI and community AI. With a broad ecological foundation, Eliza has excellent adaptability in areas such as social interaction, marketing and AI agent development.

In terms of technical architecture, Eliza has the capability of multi-agent system, allowing different AI roles to share the runtime environment and implement more complex interaction modes. Its search-enhanced generation (RAG) technology empowers AI with long-term context memory, allowing it to maintain consistency in continuous conversations. In addition, the plug-in system supports extended functions such as voice, text, and multimedia analysis, further enhancing the flexibility of application scenarios. Eliza is also compatible with multiple LLM vendors such as OpenAI and Anthropic, and can provide efficient AI computing power whether it is cloud or on-premises deployment. With the launch of the V2 message bus, Eliza's scalability will be further optimized and is suitable for medium and large social AI applications.

Eliza has faced certain challenges despite her outstanding performance in the market. Its multi-agent architecture may cause complexity problems in high concurrency scenarios and increase system resource overhead. In addition, the current version is still in the early stages of development, and stability and optimization are still being improved. For developers, the learning curve of multi-agent systemsFor steepness, it requires a certain amount of technical accumulation to make full use of its advantages. In the future, with the continued contribution of the community and the release of V2 versions, Eliza is expected to achieve further breakthroughs in scalability and stability.

8. GAME ($VIRTUAL): AI Agent framework

GAME ($VIRTUAL) takes games and metaverse as the core track, and GAME is a large scale with low-code/no-code integration Lower the developer threshold, allowing it to quickly build and deploy smart agents. At the same time, relying on the $VIRTUAL ecosystem, GAME has formed a strong developer community, accelerating product iteration and ecological expansion. Its core advantage lies in providing efficient gaming AI solutions, making it easier to implement functions such as programmatic content generation, dynamic NPC behavior adjustment and on-chain governance.

In terms of technical architecture, GAME adopts the API + SDK model to provide convenient integration methods for game studios and metaverse developers. Its proxy prompt interface optimizes the interaction between user input and AI agents, making intelligent behavior in the game more natural. The strategic planning engine divides the logic of AI agents into high-level goal planning and underlying strategy execution, making them more adaptable in complex gaming environments. In addition, GAME also supports blockchain integration, which can realize decentralized proxy governance and on-chain wallet operations, giving it a unique advantage in the Web3 gaming field.

GAME has performed performance optimization for highly concurrent gaming scenarios and performs well in handling game engine constraints. However, its overall performance is still affected by proxy logic complexity and blockchain transaction overhead, which may challenge real-time interactivity. Meanwhile, as an AI proxy framework focused on gaming and the metaverse, GAME has limited versatility in other fields. In addition, the complexity of blockchain integration still needs to be optimized to reduce development costs and further attract a wider group of developers.

9. Rig ($ARC): AI Agent Framework

Rig ($ARC) accounts for 15% of the market share of the enterprise-level AI agent market, and is based on the high performance of the Rust language. and modular architecture, making it perform excellently in high throughput and low latency scenarios, especially suitable for high-performance blockchain ecosystems such as Solana. With strong system stability and efficient resource management, Rig has become an ideal choice for on-chain financial applications, large-scale data analysis and distributed computing tasks. Its architectural design emphasizes scalability, allowing enterprise users to flexibly deploy AI agents in complex data environments and improve computing efficiency.

In terms of technical architecture, Rig adopts the Rust workspace structure to ensure the modularity and readability of the code while improving the scalability of the system. Its provider abstraction layer supports multiple mainstream LLM providers such as OpenAI and Anthropic) seamless integration allows developers to switch models freely. Rig also supports vector storage and is compatible with backend databases such as MongoDB and Neo4j, improving the efficiency of context retrieval. In addition, Rig's built-in proxy system, combined with RAG model and tool optimization capabilities, enables it to automate complex tasks, and is suitable for high-performance computing and intelligent data processing scenarios.

Rig relies on Rust's asynchronous runtime to achieve superior concurrency performance, scaling to high-throughput enterprise-level workloads. However, Rust's own learning curve is steep, which may cause certain entry barriers to some developers. In addition, Rig's developer community is relatively small and the ecological driving force needs to be strengthened. Despite this, with the growth of demand for Web3 and high-performance computing, Rig still has broad market potential and is expected to further increase market penetration by optimizing developer experience and enhancing community construction in the future.

10. ZerePy ($ZEREBRO): AI Agent framework

ZerePy ($ZEREBRO) accounts for 5% of the market share in the creative content and social media automation field, with a total market value of 300 million Dollar. Its core advantage lies in a community-driven innovation ecosystem, which allows it to accumulate a loyal user group in application scenarios such as NFT, digital art and social content automation. ZerePy lowers the development threshold for AI agents, allowing content creators and community operators to easily deploy smart agents, realize automated content creation, social interaction and community management, and enhance user engagement and content influence.

In terms of technical architecture, ZerePy is based on the Python ecosystem and provides AI/ML developers with a friendly development environment. At the same time, it uses the modular Zerebro backend to achieve proxy autonomy for social tasks. Its social platform integration function optimizes Twitter-like interaction, allowing agents to automatically complete tasks such as posting, replying, and retweeting, enhancing the automation capabilities of social media. In addition, ZerePy combines lightweight architecture design to make it more suitable for AI proxy needs of individual creators and small communities without the high computing costs.

ZerePy performs well in social interaction and creative content generation, but its scalability is mainly applicable to small-scale communities and is not very suitable for high-intensity enterprise-level tasks. At the same time, due to its relatively concentrated application scope, its applicability outside the creative field still needs further verification. For scenarios where more complex creative outputs are required, ZerePy may require additional parameter tuning and model optimization to meet a wider market demand. With the development of the creative economy, ZerePy is expected to further expand its application scenarios in the future in the direction of NFT generation and personalized social agency.

8. AI Launchpad

AI Launchpad not only provides customized growth paths for emerging projects, covering technical support, fundraising, marketing and collaboration opportunities with industry experts, but also helps projects quickly integrate into the global AI community through its extensive network of collaborations.

11. Vvaifu: The first AI Launchpad on the Solana chain

vvaifu.fun is the first AI proxy Launchpad based on the Solana chain, allowing users to create, manage and trade AI proxy. , no coding skills are required. This platform enables each AI agent to have exclusive tokens, thus forming a decentralized ecosystem. Users can not only share these agents, but also interact with AI-powered assets. The platform supports the agent's autonomous interaction on social media platforms such as Twitter, Discord and Telegram, and has on-chain wallet management functions, which greatly improves its practicality in various application scenarios.

vvaifu.fun's business model is based on its unique token economic model. The main token of the platform $VVAIFU is the first AI proxy token launched on the Dasha platform. It has deflationary characteristics. A certain amount of $VVAIFU will be burned whenever the proxy is created or function unlocked. In addition, the platform has designed a number of combustion mechanisms to ensure the stability of token value, including burning $750 for agent creation, consuming $VVAIFU and SOL fees when function unlocking, etc. Each launched agent will also allocate 0.90% of the new agent tokens to a community fund or directly into the team’s vault, thereby promoting community participation and ecological construction.

The platform's community participation mechanism enhances users' interaction and governance rights. Token holders can accumulate 0.90% of the supply initiated by a proxy through the community wallet and vote on the use of these resources. vvaifu.fun also sets a platform transaction fee of 0.009 SOL, which provides sustainable economic support for the operation of the platform. Through these mechanisms, vvaifu.fun provides a comprehensive decentralized interactive platform for creators and users of AI agents, which not only promotes the development of creative projects, but also inspires active participation from global communities.

12. Clanker: AI reply robot

Clanker is an AI reply robot based on Farcaster, designed for users to create and deploy memecoins and tokens. Through this platform, users can simply create their own tokens by interacting with Clanker. Users just need to tag @clancher on Farcaster to tell the robot what kind of tokens they need, and provide the name, code,Information such as images and supply. Clanker generates and provides tracking links within one minute, and eventually deploys the token on Uniswap v3. Although there is no initial liquidity, users need to manually add liquidity to price the token.

Clanker's technical architecture works through Next.js middleware in conjunction with LLM such as Anthropic's Claude or ChatGPT. When a user initiates a request on Farcaster, the message is forwarded to the LLM, which will execute the decision logic based on the provided context to determine the deployment operation of the token. This process reflects how Clanker uses AI technology to simplify the process of user generation and deployment of tokens, fully combining social platforms and blockchain technology to provide users with a convenient token creation experience.

As a platform, Clanker not only simplifies the creation process, but also deeply integrates with Uniswap v3, allowing users to deploy new tokens directly to decentralized exchanges. This process increases the speed of memecoins and token issuance, and also supports providing strategic value to the ecosystem through components such as Telegram robots, DEXs, aggregators, etc., which in turn drives the growth of on-chain transaction volume. As the number of tokens increases, Clanker has participated in a significant increase in transaction volume, helping users take advantage of the advantages of low transaction fees and quick confirmation time, promoting the circulation of on-chain assets such as Solana and Base.

Key Conclusion

Technology drivers and infrastructure form the core of the AI ​​agent project, ensuring efficient operation and supporting scale expansion through advanced programming languages ​​and innovative algorithms. At the same time, the high-performance blockchain platform provides excellent transaction processing capabilities and multi-chain compatibility, allowing AI agents to interact seamlessly on different chains, promoting the continuous optimization and upgrading of the technical foundation.

Payment and transaction infrastructure are key pillars of the development of the AI ​​agent ecosystem. The stablecoin payment system ensures transaction stability and liquidity, and improves the interaction efficiency between AI agents and users. The decentralized autonomous trading system achieves more efficient and secure automated trading by eliminating human intermediaries. In addition, innovative reward and governance mechanisms, such as "Proof of Contribution" and "Proof of Cooperation", promote AI agent collaboration and resource sharing, and ensure long-term and healthy development of the ecosystem through a sound governance system.

Outlook and Challenge

The necessity of AI Agent tokens is often questioned, mainly because it does not directly enhance the functions of the agent or brings obvious advantages. Many people believe that the AI ​​Agent token is similar to the tokens in Web3 games, and the latter may not necessarily be of substantial help to the core functions of the project. Therefore, some investors may ignore the actual value of these tokens by blindly following the AI ​​boom, which brings high risks and may even cause fraud. For this type ofIn the purpose, some believe that they attract investors who are unscientific by pretending to be legitimacy, especially when compared to meme coins, these tokens may have promised too many unimplemented features.

If the project uses tokens as the primary driver, it may lead to the sacrifice of core functions and experiences, especially in games and services of non-gambling nature. Tokens should be used as additional elements, not as dominant factors. Many successful projects have proved that truly effective applications should focus on user experience and create high-quality products instead of relying solely on the economic incentive mechanism of tokens to attract users.

The convergence of AI and DeFi will be an important trend in the future. It is expected that 80% of DeFi transactions will be completed by AI Agent, and promoters such as Modenetwork and Gizatech are also actively promoting this development. At the same time, the role of AI Agent in protocol governance will be further expanded, and may even trigger AI-driven governance attacks. In addition, security AI Agents are expected to play an important role in protecting protocols from attacks, similar to the protection features provided by HypernativeLabs and FortaNetwork. As infrastructure continues to expand, the development of Trusted Execution Environment (TEE) and the core position of decentralized computing will enhance the resilience of AI Agents. In addition, the explosion of the AI ​​data market will also drive the growth of data payments between AI, and projects such as Nevermined.io have laid the foundation for this.

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