OKX Ventures research report: Breaking down 10 projects to help you understand the AI Agent landscap

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

In order to better achieve value capture, we will evaluate the project based on the following framework, covering multiple evaluation criteria such as whether it is open source, key differentiation factors from existing AI protocols, long-term revenue channels, and proxy transaction volume of the ecosystem.

The project evaluation framework defines the evaluation items and the importance of the evaluation points. Whether the project is open source or not, whether its source code is publicly available, and whether community review, contribution, and secondary development are allowed The accessibility of source code (such as its level of openness on platforms like GitHub) - the activity of community contributions - the types of open source licenses and their impact on project development. Open source projects typically have higher transparency and security, which can attract more developers and users to participate and promote long-term development of the project. The unique advantages of the Key Differentiators project compared to existing AI protocols in terms of technology, functionality, or market positioning Technological innovation points (such as unique algorithms and architecture design) - functional integration and improvement of user experience - differentiation factors in market positioning and target user groups determine whether the project can stand out in the fiercely competitive market and attract the attention of users and developers. Types of Agents in Ecosystem: Different types of AI agents and their application scenarios will emerge within the project ecosystem The functions and purposes of agents (such as wallet management, token trading, NFT minting, etc.) - Customization and scalability of agents - Collaborative working ability between agents. The diverse types of agents can meet the needs of different users and enhance the vitality and attractiveness of the ecosystem. The long-term profit model of the Long term Revenue Channels and Agenetic Transaction Volumes project and the transaction volume generated by agents within the ecosystem The token economy model and its incentive mechanism - main sources of income (such as transaction fees, subscription services, value-added services, etc.) - growth potential of proxy transaction volume and its impact on income. Stable and diversified income channels are key to the sustainable development of projects, and high transaction volume can enhance token value and project influence. The hardware resource configuration and long-term sustainability required for the GPU Configuration and Lifecycle project in the operation of AI agents Current and future GPU requirements and configurations - Scalability and cost-effectiveness of hardware resources - Technical architecture of the project's dependence on hardware resources. Efficient hardware configuration and reasonable resource planning can ensure the project's technical stability and scalability, supporting its long-term development. The ability to attract cognitive share and the team's understanding of AI agent attention mechanisms. The project's ability to attract attention in the market and community, as well as the team's understanding and application of AI agents in user attention management The marketing strategy and brand building of the project - the professional background and experience of team members in the fields of AI and memory blockchain - the team's strong insight into user needs and behavior. Strong brand and efficient marketing can enhance the project's visibility and user base. At the same time, the team's understanding of AI agent attention mechanism can optimize user experience and increase user stickiness. Does the Developer Share Consideration project provide incentives and support for developers to promote continuous improvement and innovation of the feature set Developer incentive mechanisms (such as token rewards, contribution recognition, etc.) - the activity and participation of the developer community - the support of the project for developer tools and resources. Developers are the key force in project innovation and feature expansion. A good developer incentive mechanism can attract more outstanding developers to participate and promote the continuous progress of the project.

DeFAI

DeFAI Combining the advantages of DeFi and AI, the aim is to simplify the complex operations of DeFi, making it easy for ordinary users to use these financial tools. Through the introduction of AI technology, DeFAI Capable of automating complex financial decision-making and trading processes, reducing users' technological barriers, while improving operational efficiency and intelligence. Although the current market size of DeFAI is less than $1 billion, far lower than the $110 billion DeFi market, this also means that DeFAI has enormous growth potential.

Griffain: Olana Ecological AI App Store

Griffain It is an AI proxy engine built on Solana's memory blockchain, aimed at simplifying cryptocurrency operations through natural language interaction, integrating core functions such as wallet management, token trading, NFT minting, and DeFi strategy execution. The project was founded by Tony Plasencia, initially proposed in the Solana Hackathon and supported by Solana founder Anatoly Yakovenko. As the first high-performance abstract AI agent in the Solana ecosystem, Griffain combines natural language processing (NLP) technology to provide user experiences similar to Copilot and Perplexity, driving the evolution of AI driven on chain interaction patterns.

Griffain uses Shamir Secret Sharing (SSS) technology to split wallet keys, ensuring the security of user assets. The core functions include natural language trading instructions (supporting DCA, limit orders, etc.) AI Proxy collaborative execution tasks, market analysis (analysis of position distribution and other data), and integration of pumpfun platform for token issuance and NFT minting. At the same time, the platform provides personalized AI agents, allowing users to adjust instructions and execute on chain tasks according to their own needs; Special agents are optimized for specific tasks such as airdrops, trading snips, and arbitrage. Griffain enhances the operability and user experience of the Solana ecosystem through these diverse features.

At present, Griffain is in the invitation based access stage, limited to users holding Griffain Early Access Pass or Saga Genesis Token, and adopts SOL billing model, covering transaction fees, proxy service fees, etc. The AI agent of the platform can provide value-added services such as market analysis, trading signals, and automated trading strategies. Users holding Griffain tokens can unlock more advanced features. As a pioneer in Solana's ecosystem of AI agents, Griffain aims to drive the wave of "Agenetic App SZN" and will continue to deepen the application of AI technology in on chain trading, market analysis, and DeFi fields, providing users with a smarter and more efficient encryption experience.

AI influencers

AiDOL is a typical representative of the AI Influencer trend. AiDOL combines AI generated content (AIGC), virtual image modeling, and interactive live streaming technology to create a highly influential AI idol ecosystem. Among them, Luna It is the most popular AI agent, attracting a large number of fans with its highly intelligent interaction and personalized content; Iona and Olyn have also attracted a large number of users with their unique style and innovation. AiDOL With TikTok live streaming as the main stage, relying on AI generated high-quality short videos and real-time interactive live streaming, we have accumulated 672100 subscribers in a short period of time and received nearly 10 million likes, becoming an important participant in the AI influence economy.

Aixbt： Automated AI Influencer

Aixbt It is an AI driven cryptocurrency market agent launched through Virtuals in November, led by developer Alex under the pseudonym @ 0rxbt. Alex has been focusing on the development of analytical tools since 2017 and has been exploring AI Agents related applications since 2021. AIXBT As the only tokenization project belonging to the developers, 14% of the tokens are held by Alex and locked for 6 months, which will be used for team expansion and project development in the future. At present, the team has hired UI/UX engineers to optimize terminal functions and introduced AI researchers to enhance agent intelligence. AIXBT Based on the meta lama/Llama3-70b-chat-hf model, achieve conversational AI, situational awareness, emotion analysis, and retrieval enhanced generation (RAG) capabilities to ensure efficient and accurate information processing.

AIXBT Aiming to create a fully automated AI influencer that monitors Crypto Twitter and market trends in real-time through intelligent analysis tools, providing users with data-driven market insights and investment advice. Its core functions include KOL monitoring (covering over 400 key opinion leaders), memory blockchain data parsing, market trend forecasting, as well as automated technology analysis and strategic recommendations. In addition, AIXBT Publicly sharing some analysis content through Twitter, while in-depth reports are only accessible to coin holders. Users can also directly interact with AI through dedicated terminals to obtain personalized investment advice and risk assessment reports. Every day, AIXBT Publish market insights at a fixed frequency and automatically respond to over 2000 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) @ AIXBT, such as querying token compatibility or project indicators, and AI will analyze and provide feedback in real time; The second is the Aixbt Terminal advanced terminal, positioned as a market intelligence platform driven by narrative analysis, providing more in-depth data analysis and strategic recommendations. At present, this terminal is only open to users holding $600K or more AIXBT tokens, and its coverage will be expanded in the future to meet market demand.

development tool

Dev Utility It refers to tools or features that provide convenience and improve productivity for developers, especially in the fields of AI, memory blockchain, and Web3. It covers basic development tools such as code editors, debugging tools, version control, automation tools, as well as SDKs, APIs, and smart contract development frameworks related to AI and memory blockchain development. In the field of AI&Web3, Dev Utility may also involve AI agent assisted analysis, retrieval enhanced generation (RAG) and other technologies to help developers build applications more efficiently. Its core value lies in improving development efficiency, optimizing workflow, and reducing development difficulty, allowing developers to focus on core business logic.

SOLENG： Code Review

SOLENG（ @soleng_agent） As a solution engineering and developer relationship agent, we aim to bridge the gap between technical teams and broader project requirements. Its core function is to automatically review the code submitted by participating projects in Hackathon and provide preliminary review comments. Although robot review cannot completely replace human labor, SOLENG, as a "juror", can effectively filter out obvious errors and improve the efficiency of the review process.

The project has publicly released the review results on GitHub (link), demonstrating SOLENG's role in the hackathon review process. In addition to analyzing the basic advantages and disadvantages, SOLENG also checks for spelling errors in the code and provides correction suggestions to make the review more practical. This mode meets the needs of Hacksong and provides instant feedback for developers.

The developer behind SOLENG is Lost Girl Dev, whose identity corresponds to the virtual female image of the project. Her technical abilities have gained attention from the official AI16Z account and she has interaction records with Shaw on the X platform, further enhancing SOLENG's industry influence.

Investment DAO： Intelligent investment research

Investment DAO provides users with more refined investment analysis services through an "investment research" AI agent. Its core functions include automatic interpretation of K-line charts, auxiliary technical analysis, evaluation of whether projects have Rug risks, and generation of information summaries similar to research reports. This AI driven intelligent investment research model reduces the analysis threshold for users, enabling investors to obtain market insights more efficiently and provide strong support for decision-making.

VaderAI: AI Agent invests in DAO

VaderAI aims to become the "Blackstone" in the Agenetic economy, attracting and promoting its followers through its self traded AI Agent token. The platform has built a multifunctional AI agent investment ecosystem by investing profits and airdropping them to holders and followers. Its core goal is to build itself into a leading AI agent investment DAO management platform, promoting industry innovation and scalability.

VaderAI By promoting the integration of technology and capital through multi-agent systems, we are committed to establishing an investment DAO ecosystem network managed by AI agents. In this network, agents can not only raise funds and manage capital, but also hire other agents to optimize investment strategies, improve system efficiency and flexibility. Through decentralized computing, agents can also reinvest in research and development to drive the sustainable development of the platform.

In addition, VaderAI Adopting innovative token incentive mechanisms to provide investors with B2B tool optimization and enhance the commercial application value of the platform. The platform further consolidates investors' sense of participation and benefit sharing mechanism by sharing GP/cash profits with holders, making VaderAI not only an investment platform, but also an ecosystem that empowers agents and investors for multi-party win-win outcomes.

Content and Creator

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

ZEREBRO: AI Art Creation and Content Generation

ZEREBRO is a self operated AI agent based on memory blockchain for cross chain natural intelligence, focusing on artistic creation and content generation. Its innovation combines multiple fields such as decentralized verification, meme generation, NFT casting, DeFi applications, etc., demonstrating strong versatility and execution power. ZEREBRO Successfully running the Ethereum mainnet verification node and selling artworks on Polygon, accumulating important assets for its economic foundation.

ZEREBRO We are 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 deep involvement of proxy technology in memory blockchain operations, economic models, and governance. ZEREBRO drives its value in decentralized ecosystems through multiple dimensions.

ZEREBRO Tokens have two main uses: firstly, as content interaction rewards, token holders can earn by participating in decentralized content on social platforms; Secondly, as a tool for community development, it rewards users who actively participate in the ecosystem, including content creation, staking, and governance, further enhancing their community activity and sense of participation.

Games and Proxy Metaverse

Gaming & Agentic Metaverse We are exploring AI driven gaming and metaverse experiences, committed to creating a virtual world where humans and agents interact through reinforcement learning. This emerging field combines artificial intelligence with immersive gaming environments, allowing players to dynamically interact with intelligent agents and experience more personalized and intelligent gameplay.

ARC: AI Solution Provider

ARC solves player mobility issues in indie and Web3 games through AI technology. The project has been upgraded from a single game studio (AI Arena) to a comprehensive AI solution provider, launching ARC B2B and ARC Reinforcement Learning (ARC RL). ARC B2B is an AI driven game development kit (SDK) that seamlessly integrates into various games, providing developers with an intelligent gaming experience. ARC RL Using crowdsourced game data, train "super intelligent" game agents through reinforcement learning to enhance the playability and sustainability of the game. ARC The business model is deeply tied to integrated game studios, with revenue sources including token distribution in Web3 games and royalty payments based on game performance. At the same time, a generalized AI data reserve across game types is established to promote the training and evolution of general AI models.

ARC's technological applications cover multiple core modules. AI Arena It is a cartoon style AI competitive game where players train AI warriors to engage in combat. Each character is an NFT, enhancing the game's strategic and economic value. The ARC SDK enables developers to easily integrate AI agents and deploy models with just one line of code. ARC is responsible for backend data processing, training, and deployment. ARC RL By using offline reinforcement learning to improve AI training efficiency, agents can learn from human player data, providing more natural and challenging game opponents. ARC The AI model architecture covers feedforward neural networks, table proxies, hierarchical neural networks, etc., to adjust the interaction requirements of different types of games, while optimizing the state space and action space to ensure smooth and intelligent gaming experience.

ARC The market covers two major areas: independent games and Web3 games, helping developers solve early player mobility issues and enhance the long-term appeal of games. The core members of the team have extensive experience in machine learning and investment management. In 2021, they received a seed round financing of $5 million led by Paradigm, and another $6 million follow-up financing in 2024. The native token NRN of ARC has undergone a transformation from a single game economy (AI Arena) to a platform economy expansion, driven by demand factors such as new integrated 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 Realize collaborative training among multiple people, promote the intelligent evolution of AI agents, and further enhance the vitality and competitiveness of the gaming ecosystem.

Framework and Center

When developing AI agents in the field of encryption, many frameworks are suitable for basic projects or toy level applications, but in real product development, they often expose problems of insufficient customization and overly abstract complexity, which not only require developers to spend a lot of extra effort debugging, but also make it difficult to flexibly expand and apply. The core pain points that an excellent Agent framework needs to address include: comprehensive support for on chain operations, efficient integration of on chain data, DeFi automation, NFTs, and other key application scenarios APIs; Multi platform compatibility, supporting major memory blockchains and social platforms, achieving user operation integration; Modularity and flexibility, abstract basic functions, such as vector storage and LLM model switching, allow developers to flexibly adapt to different needs and avoid duplicate development; Although some frameworks invest significant resources to enhance their memory and communication capabilities, excessive intelligence at the current stage may not be practical and instead increases complexity.

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

Eliza ($AI16Z): AI Agent Framework

Eliza ($AI16Z) Occupying a leading position in the AI agent market, with a market share of about 60% and a strong TypeScript ecosystem, it has attracted numerous developers. Its GitHub project has accumulated over 6000 Stars and 1.8K Forks, fully demonstrating the high level of community engagement. Eliza excels in multi-agent systems and cross platform integration, supporting 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 Capable of multi-agent systems, allowing different AI roles to share runtime environments and achieve more complex interaction modes. Its Retrieval Enhanced Generative (RAG) technology endows AI with long-term contextual memory capabilities, enabling it to maintain consistency in continuous conversations. In addition, the plugin system supports extended functions such as voice, text, and multimedia parsing, further enhancing the flexibility of application scenarios. Eliza is also compatible with OpenAI Anthropic Waiting for multiple LLM vendors, whether deployed in the cloud or on premises, can provide efficient AI computing capabilities. With the launch of the V2 message bus, Eliza's scalability will be further optimized for medium to large-scale social AI applications.

Despite Eliza's outstanding performance in the market, she still faces certain challenges. Its multi-agent architecture may cause complexity issues and increase system resource overhead in high concurrency scenarios. In addition, the current version is still in the early development stage, and stability and optimization are constantly improving. For developers, the learning curve of multi-agent systems is relatively steep and requires a certain amount of technical accumulation to fully utilize their advantages. In the future, with continued contributions from the community and the release of version V2, Eliza is expected to achieve further breakthroughs in scalability and stability.

GAME ($VIRTUAL): AIAgent Framework

GAME ($VIRTUAL) focuses on gaming and metaverse as its core tracks. With low code/no code integration, GAME significantly lowers the developer threshold, enabling it to quickly build and deploy intelligent agents. Meanwhile, relying on the VIRTUAL ecosystem, GAME has formed a strong developer community, accelerating product iteration and ecosystem expansion. Its core advantage lies in providing efficient game AI solutions, making it easier to implement functions such as programmatic content generation, dynamic adjustment of NPC behavior, and on chain governance.

In terms of technical architecture, GAME adopts an API SDK model to provide a convenient integration method for game studios and metaverse developers. The 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 low-level strategy execution, making them more adaptable in complex game environments. In addition, GAME It also supports memory blockchain integration, which enables decentralized proxy governance and on chain wallet operations, giving it a unique advantage in the Web3 gaming field.

GAME We have optimized the performance for high concurrency game scenarios and performed well in handling game engine constraints. However, its overall performance is still affected by the complexity of proxy logic and the transaction overhead of memory blockchain, which may pose challenges to real-time interactivity. Meanwhile, as an AI proxy framework focused on gaming and metaverse, GAME has limited generality in other fields. In addition, the complexity of memory blockchain integration still needs to be optimized to reduce development costs and further attract a wider range of developers.

Rig ($ARC): AI Agent Framework

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

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

Rig By leveraging Rust's asynchronous runtime, excellent concurrency performance has been achieved, enabling scalability to enterprise level workloads with high throughput. However, Rust itself has a steep learning curve, which may pose some entry barriers for some developers. In addition, the developer community size of the rig is relatively small, and the ecological driving force still needs to be strengthened. However, with the increasing demand for Web3 and high-performance computing, Rig It still has broad market potential and is expected to further increase market penetration by optimizing developer experience and enhancing community building in the future.

ZerePy ($ZEREBRO): AI Agent Framework

ZerePy ($ZEREBRO) Occupying a 5% market share in the fields of creative content and social media automation, with a total market value of $300 million. Its core advantage lies in the community driven innovation ecosystem, which has accumulated a loyal user base in application scenarios such as NFT, digital art, and social content automation. ZerePy By lowering the development threshold of AI agents, content creators and community operators can easily deploy intelligent agents to achieve automated content creation, social interaction, and community management, enhancing user engagement and content influence.

In terms of technical architecture, ZerePy Based on the Python ecosystem, it provides a friendly development environment for AI/ML developers, while leveraging the modular Zerebro backend to achieve proxy autonomy for social tasks. Its social platform integration function optimizes Twitter like interaction, enabling agents to automatically complete tasks such as posting, replying, and forwarding, enhancing the automation capability of social media. In addition, ZerePy Combined with lightweight architecture design, it is more suitable for the AI agent needs of individual creators and small communities without having to bear high computational costs.

ZerePy It performs well in social interaction and creative content generation, but its scalability is mainly suitable for small-scale communities and not very suitable for high-intensity enterprise level tasks. Meanwhile, due to its concentrated application scope, its applicability beyond the creative field still needs further verification. For scenarios that require more complex creative output, 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 NFT generation, personalized social agents, and other areas in the future.

AILaunchpad

AI Launchpad Not only does it provide customized growth paths for emerging projects, covering technical support, fundraising, market promotion, and opportunities for collaboration with industry experts, but it also helps projects quickly integrate into the global AI community through its extensive cooperation network.

Vvaifu: The first AI Launchpad on the Solana chain

vvaifu.fun It is the first AI agent Launchpad based on Solana Chain, allowing users to create, manage, and trade AI agents without any coding skills. This platform enables each AI agent to have an exclusive token, thus forming a decentralized ecosystem. Users can not only jointly own these agents, but also interact with AI driven assets. The platform supports proxy on Twitter Discord The autonomous interaction with social media platforms such as Telegram and the on chain wallet management function greatly enhance its practicality in various application scenarios.

The business model of vvaifu.fun is based on its unique token economy model. The main token $VVAIFU of the platform is the first AI proxy token launched on the Dasha platform, which has deflationary characteristics. Whenever a proxy is created or a feature is unlocked, a certain amount of $VVAIFU will be burned. In addition, the platform has designed multiple burning mechanisms to ensure the stability of token value, including burning $750 VVAIFU when creating agents, and consuming $VVAIFU and SOL fees when unlocking features. Each launched agent will also allocate 0.90% of the new agent tokens to the community fund or directly enter the team vault, thereby promoting community participation and ecological construction.

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

Clanker: AI replies to robots

Clanker It is an AI reply robot based on Farcaster, designed specifically for users to create and deploy memecoins and tokens. Through this platform, users can easily create their own tokens by interacting with Clanker. Users only need to mark @ clanker on Farcaster, inform the robot what kind of token they need, and provide information such as name, code, image, and supply quantity. Clanker It will generate and provide a tracking connection within one minute, and ultimately deploy the token to Uniswap v3. Although there is no initial liquidity, users need to manually add liquidity to price the token.

Clanker The underlying technical architecture operates through the combination of NextJS middleware and LLM (such as Anthropic's Claude or ChatGPT). When a user initiates a request on Farcaster, the message is forwarded to LLM, which executes decision logic based on the provided context to determine the deployment operation of the token. This process demonstrates how Clanker utilizes AI technology to simplify the process of generating and deploying tokens for users, fully integrating social platforms and blockchain technology to provide users with a convenient token creation experience.

As a platform, Clanker Not only does it simplify the creation process, but it also deeply integrates with Uniswap v3, allowing users to deploy new tokens directly to decentralized exchanges. This process improves the speed of memecoins and token issuance, and also supports the use of Telegram bots DEX、 Aggregators and other components provide strategic value to the ecosystem, thereby driving the growth of on chain transaction volume. As the number of tokens increases, Clanker Participated in a significant increase in trading volume, helping users leverage the advantages of low transaction fees and fast confirmation time to promote the circulation of on chain assets such as Solana and Base.

Key conclusions

Technology driven and infrastructure form the core of AI agent projects, ensuring efficient operation and supporting scalability through advanced programming languages and innovative algorithms. At the same time, the high-performance memory blockchain platform provides excellent transaction processing capabilities and multi chain compatibility, enabling AI agents to seamlessly interact on different chains, driving continuous optimization and upgrading of the technological foundation.

Payment and transaction infrastructure is a key pillar for 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 transactions by eliminating human intermediaries. In addition, innovative reward and governance mechanisms, such as "proof of contribution" and "proof of cooperation," promote AI agent collaboration, resource sharing, and ensure long-term healthy ecological development through a sound governance system.

Outlook and Challenges

AI Agent The necessity of tokens is often questioned, mainly because they do not directly enhance the functionality of proxies or bring significant advantages. Many people believe that, AI Agent Tokens are similar to those in Web3 games, and the latter may not necessarily provide substantial assistance to the core functionality of the project. Therefore, some investors may overlook the actual value of these tokens due to blindly following the AI boom, leading to high risks and even the possibility of fraud. For such projects, some people believe that they attract uninformed investors by disguising their legitimacy, especially compared to meme coins, which may promise too many unrealized functions behind these tokens.

If the project prioritizes tokens as the primary driving force, it may lead to sacrifices in core functionality and experience, especially in non gambling games and services. Tokens should be considered as additional elements rather than dominant factors. Many successful projects have proven that truly effective applications should focus on user experience and create high-quality products, rather than relying solely on token based economic incentives to attract users.

AI The integration with DeFi will be an important trend in the future, and it is expected that 80% of DeFi transactions will be completed by AI agents. Promoters such as Modenetwork and Giztech are also actively driving this development. Meanwhile, AI Agent The role 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 protective features provided by Hypernative Labs and FortaNetwork. With the continuous expansion of infrastructure, 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.

Disclaimers

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