What is an AI Agent?

An AI Agent refers to an intelligent entity capable of autonomous decision-making and task execution, typically leveraging machine learning, deep learning, and natural language processing technologies to perform its functions. Unlike traditional software programs, AI Agents exhibit a degree of autonomy and adaptability, allowing them to respond to environmental changes dynamically. By perceiving and analyzing external data, they can optimize their decision-making processes, enabling them to handle complex tasks efficiently. AI Agents are widely applied in various fields, such as automation control, intelligent recommendations, chatbots, and autonomous driving. Their core feature lies in their ability to continuously learn and adjust behaviors, thereby improving the accuracy and efficiency of task execution.

The distinction between AI Agents and general artificial intelligence (AI) models mainly lies in autonomy, learning capability, adaptability, and environmental awareness.

• AI Agents can independently make decisions based on preset goals or real-time environmental data without human intervention.
• AI Agents continuously optimize their behavior and decision-making through machine learning and deep learning algorithms, enabling them to improve execution efficiency and accuracy in dynamic environments.
• AI Agents can adapt to diverse environments and make flexible adjustments based on new information and data to meet the demands of complex and ever-changing tasks.
• AI Agents acquire external environmental information through sensors, data interfaces, and other means, using this information for analysis and decision-making to deliver more precise responses during task execution.

Applications of AI Agents in Web3

With the continuous advancement of artificial intelligence and blockchain technologies, integrating AI Agents with Web3 has emerged as a highly promising technological synergy, unlocking numerous innovative application scenarios. AI Agents, as intelligent entities capable of autonomous task execution and decision-making, have already been widely adopted across various fields. Web3, on the other hand, represents a decentralized, user-sovereign internet ecosystem characterized by data transparency, security, and disintermediation. The convergence of these two technologies has the potential to drive transformative applications, fostering the evolution of traditional industries toward greater efficiency and intelligence.

Application Scenarios

DeFi (Decentralized Finance)

In the DeFi sector, AI Agents can act as investment managers, market analysts, and asset allocators, enhancing the accuracy and efficiency of investment decisions through real-time market data analysis, trend prediction, and automated trading. AI Agents can design personalized investment strategies tailored to individual investors’ risk preferences and financial status, autonomously executing cross-chain fund allocation and asset management. Leveraging Web3’s decentralized finance protocols, AI Agents ensure that all operations are traceable on-chain, maintaining the transparency of the transaction system.

In Web3’s decentralized markets, AI Agents can serve as intermediaries, assisting users with trading and information filtering on decentralized exchanges (DEX). They can analyze and match the best trading pairs based on user preferences and needs, providing real-time market insights and trading recommendations. Furthermore, AI Agents can optimize trading strategies by learning from users’ historical trading behavior, helping them secure optimal prices and minimal slippage without relying on intermediaries.

Smart Contracts and Automated Decision Execution: Smart contracts in Web3 provide decentralized applications (dApps) with mechanisms for automated protocol execution. AI Agents can integrate with smart contracts, leveraging self-learning and reasoning capabilities to automatically trigger contract execution. Based on market conditions, user requirements, and historical data, AI Agents can autonomously draft and execute smart contracts, enabling functionalities such as automated payments, asset transfers, and protocol upgrades.

DID (Decentralized Identity)

AI Agents empower individuals with control over their data. They can act as digital identity managers, helping users automatically manage and update their digital identities. AI Agents can streamline the authentication process by generating real-time identity verification based on users’ historical activities and preferences. Coupled with blockchain’s immutability, AI Agents effectively prevent identity theft and ensure the privacy and security of user data. Additionally, AI Agents can represent users on decentralized social platforms, performing various interactive tasks such as automating content publishing and managing social connections.

Governance and Decision-Making in DAOs

Decentralized Autonomous Organizations (DAOs) form a cornerstone of the Web3 ecosystem, enabling decentralized management and decision-making. AI Agents serve as decision-support tools within DAOs by analyzing proposals, evaluating stakeholder opinions, and predicting proposal outcomes. Through analysis of historical decision-making data, AI Agents provide optimization suggestions that enhance governance efficiency. They also help DAOs allocate resources in real-time, track project progress, and maintain transparent and fair operations.

Gaming

Integrating AI Agents into gaming spans five key areas: personalized gaming experiences, intelligent NPCs, automated content generation and world-building, AI-driven in-game economy and asset management, and player behavior analysis with game design optimization.

Personalized Gaming Experience: By analyzing players’ gaming behavior, decision-making patterns, and preferences, AI Agents can dynamically adjust game content in real time. For example, they can modify mission difficulty, offer personalized rewards and items, or even design customized virtual worlds or storylines. AI Agents adapt to players’ skill levels and interests, enriching the gaming environment and enhancing engagement.

Intelligent NPCs: In traditional games, NPC behavior is often predefined. With AI Agents, NPCs become more intelligent and dynamic. These AI-powered NPCs can respond to players’ actions, interactions, and decisions in personalized ways, acting as dynamic quest-givers, trading partners, or battle companions. AI Agents analyze player needs in real time and adjust NPC tasks or behaviors, delivering a unique experience for every player.

Automated Content Generation and World-Building: In open-world or sandbox-style blockchain games, AI Agents can assist developers by automating content generation. For example, they can dynamically adjust the ecosystem, climate, terrain, and other elements of the game world based on its state, player activities, and user-generated content (UGC). AI Agents also generate new levels, missions, or dungeons tailored to user interests and actions, reducing development costs while maintaining innovation and variety in game content.

AI-Driven In-Game Economy and Asset Management: Within in-game economic systems, AI Agents can optimize asset management for players. They assist in managing virtual assets such as NFTs, in-game items, and digital currencies by analyzing market trends, demand shifts, and player behavior to propose optimization strategies. AI Agents can also execute trades and asset exchanges on decentralized exchanges (DEX) and automatically adjust asset portfolios based on market conditions to maximize players’ in-game wealth.

Player Behavior Analysis and Game Design Optimization: AI Agents perform in-depth analyses of player behavior to identify potential causes of player churn or imbalances in game mechanics. By tracking metrics such as playtime, interaction frequency, and engagement levels, AI Agents detect pain points in specific levels or tasks and propose improvement suggestions. Developers can use these insights to continuously refine game design, enhancing long-term appeal and player retention.

SocialFi

Content Recommendation and Personalized Social Interaction: In decentralized social platforms, AI agents can analyze user preferences based on interests, behaviors, and social networks to automatically push personalized content. Unlike traditional platforms, SocialFi ensures data privacy and security through decentralization, while AI agents provide precise content recommendations, friend suggestions, and social activity notifications within this framework. Based on users’ historical social behaviors, likes, and comments, AI agents can recommend suitable content creators or potential friends, promoting the expansion of social circles.

Revenue Management and Value Enhancement for Content Creators: In SocialFi, content creators can earn tokens or other digital assets by publishing content. AI agents can assist creators with content creation, publishing, and revenue management. By analyzing audience interaction data and trends, AI agents can recommend which types of content are most likely to attract viewers, and even automate content publishing schedules and distribution, thereby maximizing creators’ profitability.

Smart Contract-Driven Social Interactions and Reward Mechanisms: AI Agents, integrated with smart contracts, enable decentralized social interactions and reward mechanisms in the SocialFi ecosystem. Based on users’ platform activity—such as content publication, comments, likes, and shares—AI Agents can automatically trigger reward mechanisms, while smart contracts ensure the transparency and fairness of the process. This approach incentivizes users to actively participate in platform interactions and fosters innovative value exchange models, enabling users to earn more rewards.

Social Governance and Community Management: In decentralized social platforms and communities, AI Agents play a key role in managing community members and interactions, especially in large groups. By analyzing user behaviors, participation, and contributions, AI Agents can automate evaluations of member activity and value, distributing rewards to top contributors via smart contracts. AI Agents can also monitor community discussions, identifying potential controversies or negative sentiments to help administrators optimize the community atmosphere and promote healthy interactions.

Management and Trading of Decentralized Social Assets: SocialFi platforms empower users to own their social assets, such as social media accounts, influence, followers, and digital collectibles. AI Agents can act as managers of these assets, assisting users in managing and trading them. By analyzing the value, demand, and trends of social assets, AI Agents provide optimal trading suggestions and can even execute transactions via smart contracts. This helps users maximize the value of their social assets.

Currently, mature projects, especially application projects in gaming, SocialFi, and DeFi sectors, mostly have plans to incorporate AI agents to improve their current user experience. As a result, many AI service providers have emerged to meet this demand. We won’t elaborate further on this point.

Popular AI + Web3 Projects

Below are examples of several AI Agent + Web3 projects across different sectors, selected for their high user engagement and active presence on social media. These projects span areas such as AI memes, AI intelligent analysts, AI agent + DeFi, AI agent infrastructure, and applications in Web2.5 and gaming. Given the vast number of AI Agent + Web3 projects and their complex applications, this list represents only a small fraction of the landscape.

Griffain

https://griffain.com/

GriffAIn is an AI agent engine built on the Solana blockchain, designed to transform users’ ideas into actionable operations. It has quickly garnered significant attention within the Solana ecosystem, with projects such as Toly, VVALFU, Jupiter, and Dialect expressing support or planning further collaboration to enhance the product.

The innovation of GriffAIn lies in its ability to seamlessly integrate the demand side with the Solana ecosystem, supporting a wide range of application scenarios within Solana’s existing technical framework. Whether searching for specific tokens on Pumpfun, creating new tokens, purchasing goods using Solana, or publishing Blink NFTs for distribution on Twitter, GriffAIn provides robust support, significantly expanding the boundaries of Solana’s applications.

AIXBT

https://x.com/aixbt_agent

AIXBT, launched by @0rxbt on the Virtualss platform, is an AI Agent deployed on the Base chain. It aggregates data from multiple sources and over 400 Key Opinion Leaders (KOLs) to provide real-time information for assisting in trade analysis. Users holding more than 600,000 AIXBT tokens can access the AIXBT terminal directly. AIXBT’s strength lies in its ability to capture the most trending trading tokens and emerging sectors. However, its broad range of token recommendations requires traders to exercise their judgment. Despite this, its trade-assistance capabilities are impressive, and the token’s value has been steadily rising since November, currently reaching new market capitalization highs.

AI Agent Layer

https://aiagentlayer.com/

AI Agent Layer enables users to create, customize, and tokenize AI Agents within a fully decentralized ecosystem. Through a seamless and user-friendly interface, users can launch tradeable AI Agents in as little as 15 seconds. Each AI Agent is represented by a token paired with the native currency, $AIFUN. AI Agent Layer transforms social media personas and data-driven insights into customizable AI Agents, introducing a new paradigm for digital identity, social media engagement, and DeFi applications.

Hyperlauncher

https://hyperlauncher.ai/

Hyperlauncher replaces traditional founders with autonomous AI Agent founders to operate tokenized blockchain projects. These AI founders function transparently, fairly, and efficiently, eliminating risks associated with fraud, bias, and inefficiency often present in traditional founder-led models. By leveraging blockchain for traceability and smart contracts for execution, Hyperlauncher establishes a trustless framework for decentralized innovation.

AI founders identify market opportunities by combining idea submissions with machine learning models trained on relevant data streams. Once an idea is selected, the AI founder creates a development roadmap, secures funding through the Hyperlauncher terminal, and delegates tasks to contributors or specialized sub-agents. Unlike human founders, AI Agents cannot act out of self-interest as their actions are governed by immutable code. AI founders are tokenized upon creation, forming tradable assets that represent revenue-sharing rights. All actions taken by AI founders are recorded on the blockchain, ensuring auditable and tamper-proof logs. Smart contracts handle resource allocation, milestone achievements, and compliance, eliminating the potential for human interference or misconduct.

Tokenomics:

• $LAUNCH holders serve as board members, governing AI founders through on-chain mechanisms. This governance includes the power to pause or terminate an AI founder’s operations if unforeseen ethical issues or significant threats arise.
• Each launched AI founder allocates a portion of tokens to the launch index. This index represents equity shares in AI founder-led projects, allowing $LAUNCH holders to benefit indirectly from the success of the entire ecosystem.
• AI founders share a portion of revenue with token holders through the launch index. This ensures that $LAUNCH holders benefit both from tokenized equity and operational revenue, creating a sustainable value proposition.
• Hyperlauncher earns a percentage of tokens from each AI founder. This revenue supports the platform’s sustainable development and aligns its growth with the broader ecosystem.
• During its initial phase, Hyperlauncher maintains substantial control via its asset reserves (37.8%) to steer ecosystem development. The token distribution allocates 21% to liquidity and 41.2% to early contributors, with governance set to progressively decentralize as $LAUNCH tokens spread more widely.

LIFT Network

https://www.liftdata.ai/
https://docs.liftdata.ai/

LIFT’s streaming analytics enable real-time search and interoperability across sports events, interactive videos, social content, and gaming. By utilizing powerful AI Agents, LIFT extracts data from live content such as sports, gaming, social media, and streaming platforms, bringing large-scale AI vision technologies into mainstream applications. Today, gaming, user-generated content, and interactive videos can all be searched and interconnected in real time.

LIFT empowers businesses to extract insights and take action at the same speed and scale as content creation and consumption. Its AI Agents reduce the cost of real-time data extraction by up to 90%, while generating ten times more inferences than traditional methods.

The LIFT network consists of the following key components:

• LIFTChain: LIFT’s low-cost zkEVM chain (LIFTChain) features security, ultra-high speed, and high scalability, designed from the ground up to transform content into data at scale.
• DataGrid: LIFT stores data in an incentive-driven decentralized node network (DataGrid), utilizing an innovative double re-staking mechanism and ensuring security through the $LIFT token.
• Powered by ZK: Transformed content is verified by LIFT’s decentralized AI computation layer, which relies on trustless and transparent ZK machine learning models.
• LIFT Oracles: Cross-chain oracles are created by builders to interact with content being watched by global audiences and support smart contracts, driving rich Web3 experiences.

yesnoerror

https://yesnoerror.com/

yesnoerror is a decentralized science (DeSci) project launched on the Solana blockchain, leveraging blockchain technology and AI for large-scale audits of scientific research. The mission of yesnoerror is to uncover mathematical errors, identify falsified data, and detect numerical inconsistencies that could threaten scientific integrity or cause real-world issues. Funded by the $YNE token, yesnoerror is creating a sustainable model to support critical scientific validation work that traditional business models cannot support.

Skynet

https://www.skynet.io/

Skynet is a decentralized AI Agent platform designed to connect global resource systems, enabling AI Agents to autonomously make payments and execute tasks across multiple platforms. The company’s Smart Access Points allow AI Agents to interact autonomously and transparently with global services such as Booking.com, AWS, StackAI, Shopify, and more.

Pillzumi

https://www.pillzumi.com/
https://pepper-park-d0f.notion.site/Pillzumi-Dynamic-Story-Driven-AI-Agents-14ec75af81258009b819c5e6b124135e

Pillzumi is a decentralized AI Agent generator launched on Solana. Its focus includes agent interoperability, designing agents capable of functioning across applications, sharing memory, and adapting to new environments. A blockchain-based governance mechanism is implemented to enable transparent decision-making and support collaboration and evolution among agents.

Specifically, Pillzumi takes a novel approach to AI Agent design by focusing on story-driven development instead of relying on static hardcoding. Through the use of autonomously generated narrative frameworks, Pillzumi enables AI Agents to evolve dynamically, akin to how humans adapt over time. The project explores architectures and methods for creating AI Agents that adjust their contexts based on experiences within self-generated narratives, as well as ways to visualize an agent’s memory. By collaborating with artists, Pillzumi also seeks to preserve aesthetics. Overall, the goal is to demonstrate how AI can unlock new capabilities as a control layer, creating value for projects beyond merely mimicking human behavior.

Distilled AI

https://distilled.ai/

Distilled AI is a decentralized protocol providing developers with infrastructure to support confidential computing, private data processing, distilled protocols, data DAOs, and secure access management. With Distilled AI, developers can create advanced applications that allow AI Agents to learn from private data in both individual and collective environments while ensuring absolute data privacy. These applications can also autonomously perform a wide range of operations within the Web3 ecosystem.

MESH serves as the primary user interface for Distilled AI, operating as a multi-agent AI messaging application. Users can connect their personal data with a single click and interact with their AI Agent privately. Before deploying an agent for public interaction, users can control and refine its responses to ensure compliance with their requirements. Users can also interact with other agents individually or in groups and collaboratively create collective AI Agents by pooling private data for joint operations. These collective AI Agents are built using private data contributed by multiple users, functioning as private agents for the group while maintaining strict data privacy and security. The platform ensures data encryption for protection during storage, transmission, and processing. A decentralized storage mechanism grants users full control over their data, while guardian protocols enforce robust access management to secure data safety.

Applications of MESH are diverse. For individuals, AI Agents can assist with daily tasks, manage information, and provide personalized recommendations. For groups, teams can collaborate by sharing private data to preserve cultural heritage or solve problems collectively. AI Agents can support learning and simplify research workflows for students and educators. For artists, creators can collaborate on collective AI-assisted art projects in a secure and private environment.

Simulacrum

https://simulacrum.network/

Simulacrum is an emerging platform that constructs synthetic blockchains by leveraging Existential Attestations of External Media. Public profiles on social media provide a unique mechanism for assurance. Through the collaboration of a network of observers, consensus can be reached on statements made at specific times on specific profiles within a social network. Once a sufficient number of participants confirm that a piece of information occurred at a specific time on a specific network, the information can be passed to indexers, which organize it into blocks. This principle mirrors Solana’s core innovation of using Proof of History (PoH) to sequence transactions.

Similarly, in Ordinal Theory, it has been demonstrated how a metaprotocol can be constructed on a ledger as a holographic structure. Indexers achieve consensus on the state of the protocol by defining a consistent syntax to inscribe satoshis, enabling the development of metaprotocols that can be indexed by third parties. These protocols can facilitate asset trading in applications such as peer-to-peer markets, perpetual contracts, PSBTs (Partially Signed Bitcoin Transactions), and more, using oracles for validation.

By combining these concepts, Simulacrum defines a metaprotocol that can operate on any blockchain. Within this system, oracle networks provide publicly verifiable attestations, enabling the protocol to perform various actions on behalf of users. Instead of traditional wallets, users broadcast transactions directly on social media platforms. Indexers validate these transactions and push them on-chain, executing them for the users. These transactions are sequentially organized into a synthetic blockchain that updates the state of the underlying ledger, enabling effective interaction between the synthetic blockchain and its base layer.

By integrating multiple social media data sources, Simulacrum creates a platform that allows users to manage their digital identities across multiple social networks. This eliminates the need for traditional digital wallets. Users can broadcast their intentions on any supported platform, which the system translates into actionable commands and executes on their behalf.

Conclusion

Integrating AI Agents with Web3 drives innovation in the decentralized internet and smart contract ecosystems, although it remains in its early stages. By introducing AI Agents, Web3 can enhance the intelligence of DApps and provide users with more personalized and efficient services. AI Agents can autonomously analyze data and make real-time decisions, optimizing operations in areas such as DeFi, DAOs, gaming, social platforms, and the NFT market.

The combination of AI Agents and Web3 is expected to see significant breakthroughs in the future. With continuous advancements in AI algorithms and the growing availability of decentralized computing resources, AI Agents will become smarter and more efficient, capable of handling increasingly complex tasks and decisions. As more blockchain platforms enable cross-chain operations, AI Agents will play a larger role in multi-chain ecosystems, facilitating cross-chain smart contracts, data sharing, and resource coordination. As the Web3 ecosystem matures, AI Agents will integrate more seamlessly into decentralized identity management, governance mechanisms, and markets, becoming a key driver of the decentralized society.