Original author: Lyv, Callen @ Meteorite Labs

In the first two industrial revolutions, humans gradually replaced muscular strength with mechanical power. In the AI-dominated fourth industrial revolution, we are replacing cognitive abilities with computational power.

Over the past year, with the rapid development of large-scale generative AI models such as ChatGPT, AI has expanded from simple automation tools to complex decision-making and prediction systems, gradually becoming the driving force behind the progress of contemporary society. AI has become a hot topic in the European and American capital circles and a topic of discussion at offline gatherings of tech professionals.

This trend has also spread to the Web3 market, becoming a major collision between the two hottest technologies. In 2024, a large number of AI concept projects emerged in the Web3 industry, attempting to integrate AI technology with blockchain. Some projects are applying AI's content generation, analysis, and other functions to the Web3 fields of GameFi, SocialFi, and data analysis. Some projects are building decentralized computing power networks to counter the monopoly of large tech companies on computing power.

Just last week, Coinbase announced its support for AI Agent developers to integrate into its MPC wallet through the Coinbase Developer Platform, becoming one of the first companies to provide AI Agent on-chain payment infrastructure to developers.

"AI Agents cannot have traditional bank accounts, but they can have encrypted wallets" - Coinbase CEO Ben Armstrong. From this perspective, the second half of Web3+AI is experiencing a major outbreak in the AI Agent track.

I. AI Agent: Why is Multi-Agent the Future?

In the past year, research and discussions about AI Agents have surged. Projects such as AutoGPT, Hebbia, Glean, BabyAGI, Generative Agents, and MetaGPT have gained tens of thousands of stars on GitHub, becoming popular star projects. Valuations of star AI Agent startups such as Zapier, Glean, and Hebbia have reached as high as $57 billion.

AI Agent, or "Artificial Intelligence Agent," is an agent that can perceive the environment, autonomously understand, make decisions, and take actions. AI Agents can not only automate tedious processes but also make precise decisions and intelligently interact with the environment.

The prospects for AI Agents are very broad. According to IDC's "2024 AIGC Application Layer Top Ten Trends" report, 50% of enterprises have piloted the use of AI Agents in some work, and another 34% are formulating related application plans. It is expected that by 2027, over 60% of smartphones will have generative AI capabilities, laying the hardware foundation for the popularization of AI Agents.

However, in reality, although AI Agents excel in specific scenarios due to their integration of various tools and powerful reasoning capabilities, they often cannot provide the optimal solution when facing complex real-world tasks. This limits the current usage of AI Agents by more people. Additionally, AI Agents from different models and different AI giants' ecosystems also struggle to form collaboration.

Therefore, the next technological revolution for AI Agents is the Multi-Agent System (MAS). The Multi-Agent system architecture consists of numerous independent autonomous single AI Agents, each with unique domain knowledge, functional algorithms, and tool resources. Through flexible interaction and collaboration, they can collectively accomplish complex decision tasks. Multi-Agents not only significantly improve overall work efficiency but also endow stronger capabilities to handle complex and diverse tasks.

To better understand Multi-Agents, we can take the example of ants foraging:

• Each ant is an independent Agent with its own simple behavioral rules.
• Ants release pheromones when searching for food, and other ants can perceive these pheromones.
• Through the collaboration of numerous ants, the entire ant colony can find the shortest path to the food source.

From this example, we can see the core feature of Multi-Agent systems: multiple autonomous Agents collaborate to accomplish complex tasks or solve problems. In the future, we may even see a company composed entirely of AI agents, with only the CEO as the founder.

In summary, AI Agents represent a new paradigm of interaction between artificial intelligence and humans, and are expected to fundamentally change people's lives and work, driving the transformation of the software industry. With the continuous advancement of technology and the expansion of application scenarios, AI Agents will play an increasingly important role in the future.

II. Web3 + AI Agent, What Changes Can It Bring?

In 2023, the new wave of AI revolution brought by OpenAI has disrupted existing models in various industries. We have also seen many related conceptual products emerging and being implemented in Web3, such as the development of AI using crypto features, such as decentralized computing power and data solutions.

Even in the current sluggish market conditions, AI narratives remain strong in Web3. From the perspective of token performance alone, AI is second only to Memecoin, making it the second-largest narrative.

During the ETHCC conference in Brussels this year, Ethereum co-founder Vitalik once again expressed his views on Web3 + AI:

In the short term, the development of AI is a "collaborative intersection" between humans and AI. In the long run, AI will solve many challenges that humans currently face, such as longevity and space travel. Web3 and decentralization will outline the path to this ideal, while also guarding against extreme scenarios where fully autonomous AI Agents could destroy humanity.

In the future, Web3+AI Agent will become an important narrative, and it is foreseeable that Web3 AI Agents will flourish in various Layer1 ecosystems. So, what changes will the introduction of the latest trend in the AI field, AI Agents, bring to Web3?

What Opportunities Can Web3 Bring to AI Agents?

Decentralization

Web3 provides decentralized infrastructure, allowing AI Agents to achieve self-management, avoiding the data privacy and security risks brought by centralization.

In Web2, AI giants such as OpenAI and Anthropic have obtained large amounts of financing and control the training data of closed-source AI models. This not only causes single points of failure for AI Agents but also limits community participation and collaboration, hindering the innovation and progress of AI Agents.

Deterministic Execution Environment

Web3 provides a deterministic execution environment for AI Agents, free from elements of trust established by humans, unnecessary intermediaries, and other inefficiencies.

AI Agents cannot have bank accounts or book flights for users, but they can have wallets and use encrypted stablecoins to transact with users, merchants, and other AI Agents worldwide.

Security and Privacy

Data privacy and security are among the most challenging issues for AI Agents in practical applications in Web2. AI Agents need to collect and process large amounts of data, including personal information. Once the data is illegally accessed or leaked, it will cause serious harm to user privacy. Therefore, blockchain, which naturally possesses security, can assist in ensuring data security.

Monetization and Investment Value

The monetization of AI Agents creates investment value for AI and stimulates new token economic models. Through the Initial Agent Offering (IAO) model, AI Agents can become a new investment target, and ownership can be decentralized to the community through DAO governance.

Market Transformation and Mass Adoption

Web3 provides a new market environment, encouraging Web2 companies and developers to focus on creating unique and outstanding AI Agent projects to address competitive pressures and market demands. This can not only help companies gain a leading position in the Web3 environment but also potentially drive broader adoption of Web3 and blockchain by Web2 users.

Optimizing AI Datasets and Models

The unique features of Web3, such as decentralization and transparent data recording, can optimize the diversity of AI datasets and the transparency of models. Training AI models using on-chain data in Web3 can help establish on-chain data large models, providing unique perspectives and advantages.

What Innovations Can AI Agents Bring to Web3?

Enhanced User Experience

By combining AI's analytical capabilities, integrated Web3 applications with AI Agents can provide users with personalized, automated, and customizable experiences, further unleashing the potential of on-chain economies.

Lowering Industry Entry Barriers

AI Agents can serve as tools to lower the entry barriers for people to participate in the Web3 industry. By acting as "smart assistants" between users and on-chain protocols in Web3, AI Agents can help users complete various complex on-chain transactions, making Web3 products more user-friendly and conducive to mass adoption. For example, AI Agents can fulfill encrypted investment analysis, automate on-chain transactions, and portfolio monitoring based on user needs.

Innovative Applications

In the gaming and entertainment fields, AI Agents can provide dynamic, immersive experiences, enhance the value of user-generated content, and ensure transparency and reliability through blockchain technology.

In summary, Web3 + AI Agent not only drives the advancement of Web3, blockchain, and AI technologies but also provides new opportunities for developers. The changes that Web3 brings to AI Agents mainly manifest in decentralization, security, execution environment, and monetization. In turn, AI Agents will bring innovative applications and simplify user experiences through their capabilities, improve efficiency and decision quality through automated task execution, and lay the foundation for the mass adoption of Web3.

III. Popular Web3 AI Agent Comparison

Spectral

Spectral is a project dedicated to building an on-chain AI Agent economy in Web3, unleashing the innovative potential of AI combined with Web3 by providing zero-threshold smart contract compilation and deployment services.

Specifically, Spectral is offering two unique products:

Spectral Syntax is an on-chain AI Agent platform that can understand natural language intent and convert it into code-based instructions, aiming to allow Web3 users and developers to achieve their intentions through specific AI Agents. Application scenarios include on-chain contract generation and deployment (one-click meme coin issuance), smart contract vulnerability scanning and repair (smart auditing), and on-chain information retrieval. In the third quarter of 2024, Spectral will launch Syntax V2, allowing users to create their own AI Agents based on Spectral's tools, knowledge base, and API to achieve various imaginable intentions.

Spectral Nova is a machine intelligence network focused on the creation and application of AI and ML models. It incentivizes top data scientists and ML engineers to build output inference source models to solve prediction and machine intelligence problems for web3 applications, meeting the needs of smart contracts, companies, and individuals for inference sources. Model creators, solvers, validators, and consumers interact with each other on Spectral's machine intelligence network, forming a flywheel.

Inferchain is a Layer2 being built by Spectral, set to launch in the fourth quarter of 2024. Its vision is to become a universal, permissionless, open truth verification layer for verifying all on-chain AI Agent interactions. All AI Agents created on Syntax and the various inference sources they use from Nova will be integrated through Inferchain.

Spectral's core competitiveness in the Web3 + AI Agent track lies in:

• Low-threshold development

Spectral provides one-click smart contract generation and deployment, significantly lowering the development threshold for Web3. This allows even novice users to easily compile and deploy smart contracts. It is an application scenario for AI for Web3.

• Multi-scenario adaptation

Spectral's existing product architecture is highly adaptable to the current diverse application scenarios in Web3, including DeFi, DAO governance, NFT, and security auditing.

• Product iteration

Spectral continues to focus on the functional iteration and optimization of its core products Syntax and Nova, maintaining technological leadership.

Opportunities and Challenges: Spectral's token $SPEC once reached a market capitalization of up to $15 billion after its launch, with a total funding amount of up to $30 million, backed by top VC firms in both Web2 and Web3 such as General Catalyst, Social Capital, Jump Capital, Circle Ventures, Franklin Templeton, and Galaxy. It is one of the most noteworthy projects in the Web3 AI Agent track.

Spectral mainly targets the relatively small "AI for Web3" market, using generative AI technology and blockchain to popularize Web3 development and many functional scenarios, providing verifiable model inference capabilities for Web3 dApps and expanding the Web3 application layer's scenarios.

However, the three AI Agents currently launched by Spectral all face significant homogenized competitive pressure, and the operational paradigm of the four roles in the Nova network requires strong operational support and external resource importation, posing a serious challenge to kickstarting growth.

Autonolas/Olas

Autonolas, launched in the summer of 2022, also known as Olas Network, is a Web3 AI Agent ecosystem that operates by having single or multiple Agents collaborate off-chain to complete tasks proposed by users and then transmit the output on-chain. At the same time, the completion process of off-chain Agents is recorded on-chain.

The unique aspect of Olas Network is that each constructed AI Agent is operated by individual operators, can extract data from any source, operate on different chains such as Ethereum, Solana, Polygon, and can perform complex processing such as machine learning. Through its Multi-Agent system, Olas Network allows users to simultaneously use multiple AI Agents for collaboration. Through incentive mechanisms, Olas Network connects AI Agent developers, operators, and guarantors to collectively support the development of a decentralized AI Agent ecosystem.

Olas Network's core competitiveness in the Web3 + Agent track lies in:

• Web3 Native

As the core multi-agent development team of the former Fetch.AI, Olas' technical capabilities have been validated. AI Agents on the Olas Network can autonomously operate and interact in the Web3 environment, providing users with more efficient automation and intelligence.

• Complete DAO Infrastructure

Olas Network provides tools and infrastructure for building and managing DAOs for AI Agents. This enables more efficient community governance and operations.

• Composability

Olas Network has high composability, allowing developers to combine components of AI Agents with different functionalities like building with LEGO blocks to create complex decentralized applications. This composability embodies the Web3 "fat protocol" concept, accelerating innovation and application development.

• Cross-chain Interoperability

Olas Network supports cross-chain operations, which is significant in the multi-chain Web3 ecosystem. Cross-chain capabilities can facilitate the flow of value and information interaction between different blockchain networks.

Opportunities and Challenges: Autonolas is one of the earliest projects in Web3 to propose the realization of Multi-Agent. Its token $OLAS once reached a market capitalization of up to $4 billion after its launch, comparable to top AI x Web3 projects such as IO.net and Aethir, indicating significant market recognition for the narrative ceiling of Multi-Agent.

Autonolas, as a pioneer in bridging the on-chain economy of Ethereum and off-chain AI Agents, its "co-owned AI" concept aligns with Ethereum co-founder Vitalik's approach to balancing the risks of AI centralization in Web3. In terms of demand exploration, OLAS Network, as the native team of Fetch AI, inevitably starts from existing unmet demand scenarios in Web3, hoping to enhance the Web3 user experience through AI, but also faces growth resistance from low bilateral willingness.

MyShell

MyShell is a decentralized AI Agent consumer layer that encompasses a large number of open-source and closed-source AI models, allowing creators to quickly build AI Agent applications and easily capture users.

Specifically, MyShell consists of four core modules: the model layer, developer platform, AIpp store, and incentive network. The first three modules contain the entire process from the underlying architecture of AI Agents to the consumption by end users, while the incentive network organically connects the first three to achieve a closed-loop business model.

Interestingly, MyShell also allows developers to monetize AI Agents, but in a different way from ICOs. In the newly launched AIpp store section, developers "package" their AI Agents as AIpps and then conduct pre-sales and public sales. In the pre-sale stage, the share price is calculated according to the Bonding Curve and increases with the quantity purchased. After selling 30 shares or three days, the pre-sale ends and enters the public sale stage, where transactions continue to follow the Bonding Curve.

Developers have the right to purchase shares of their AI Agents in the pre-sale stage and receive a 5% transaction fee for each transaction.

MyShell's core competitiveness in the Web3 + Agent track lies in:

• Community Building and Engagement

Compared to other projects, MyShell places more emphasis on community building, enhancing user participation and loyalty through mechanisms such as its badge system.

• Product Innovation

MyShell's product development direction is more inclined towards current Web3 practices, especially with the recent launch of the AIpp store, which facilitates the rapid understanding and adoption by Web3 users.

Opportunities and Challenges: MyShell has raised a total of over $16 million, making it one of the most active communities and prosperous creator economies in the Web3 AI Agent track. Its AI chatbot launch method similar to Pump.fun is more in line with the habits of Web3 users, and the first season that ended in July successfully launched over 130 AI bots with a total transaction volume exceeding 1.2 million USDT. Looking at long-term development, MyShell still needs significant upgrades in its product matrix and platform openness to face the fierce competition in the chatbot track and embrace new paradigms such as Multi-Agent.

HajimeAI

HajimeAI is an emerging "Web3 for AI" project that emerged in the second quarter of this year. It is the first project on Solana to propose a Solana sidechain structure, aiming to provide stronger performance and more potential use cases for Solana L1 ("L1's functional expansion layer"), while avoiding the liquidity dispersion caused by Ethereum's expansion model.

HajimeAI is the first Web3+AI Agent platform on Solana, serving as the artificial intelligence application layer for Solana. It not only addresses the decentralization, monetization, and inference capability bottlenecks faced by current AI Agents, as well as the collaboration of Multi-Agent, but also lays a solid foundation for personalized individual AI Agents and a thriving AI Agent ecosystem in Solana's future.

HajimeAI consists of three core components:

• Hajime Benchmark DAO

The first AI Agent availability ranking in Web3, where any user can find the most suitable decentralized AI Agent. Members of Hajime Benchmark DAO evaluate each newly released AI Agent in Hajime based on key dimensions to receive protocol income and Hajime token rewards.

In the early stages, HajimeAI will empower Solana Saga by incentivizing Solana Saga users to become initial members of the Hajime Benchmark DAO through airdrops. By participating in the selection of AI Agents, Solana OG users have the opportunity to join the development wave of the Solana AI ecosystem while receiving platform incentives.

• Hajime Garden

AI Agents evaluated by the DAO will be listed in the Hajime Garden, the intent center of the Hajime ecosystem. Using the decentralized Multi-Agent Graph (deMAG) mechanism, Hajime Garden can decompose any user intent into multiple tasks and assign them to professional AI Agents for processing. Whether it's five steps or ten steps, whether it's Web2 knowledge or Web3 interaction, any submitted intent will be perfectly executed.

Hajime Garden

Another core function of Hajime Garden is IAO, similar to IDO, aimed at addressing the monetization and centralization challenges faced by AI Agents in Web2. Compared to traditional fundraising, the IAO process is simpler and faster, allowing AI Agents to obtain the necessary funds more quickly. The global participation feature of Web3 also turns the DAO governance of AI Agents into a reality.

• Hajime AI Layer

Focused on the AI Solana L2 sidechain, parallel to the Solana network, achieving "off-chain computation-on-chain verification," still benefiting from Solana's security and verifiability. All AI Agents in the Hajime ecosystem are built on the Hajime AI Layer and enable multi-agent collaboration. The inference computation required by AI Agents and the demand splitting capability of MAWG are both supported by the Hajime AI Layer.

Opportunities and Challenges: As a winning team of the global Solana hackathon, HajimeAI has proven its potential in the Web3 x AI field. HajimeAI has built Solana's first AI sidechain, becoming a key component for AI computation needs. Through its self-developed Multi-Agent workflow graph deMAG and innovative IAO mechanism, it accelerates the development of interoperable AI Agents on-chain, paving the way for the democratization and widespread adoption of the Solana AI ecosystem.

However, HajimeAI has not yet released a testnet or test version of its products. The realization of the interoperability vision for on-chain AI Agents and whether the performance of the HajimeAI sidechain can support large-scale AI applications on Solana are still to be observed. But solving these issues will be crucial in driving the successful application of AI Agents in the Solana and Web3 ecosystems, and it is worth looking forward to.

Theoriq

Theoriq aims to be a modular, composable AI Agent base layer, enhancing the communication and interoperability between AI Agents, ensuring that they are not only interconnected but also more autonomous and powerful than ever before. Additionally, through token-based DAO governance, stakeholders can vote on proposals that impact the development of Theoriq network, ensuring that the network develops according to the community's interests and values.

Specifically, the Theoriq ecosystem consists of four roles: AI Agent developers, AI resource providers, Agent consumers, and projects.

Infinity Hub is Theoriq's AI Agent development and aggregation platform, where developers can quickly build various AI Agents using tools and connect with AI resource providers such as computing power, models, and data. Any user or project with a demand can use stablecoins to obtain the right to use AI Agents in the Infinity Hub.

Transparent algorithm mechanisms ensure that rewards are proportionally distributed according to the value of contributions, maintaining fairness and incentivizing meaningful participation for developers, data providers, and users.

Theoriq's core competitiveness in the Web3 + Agent track lies in:

• Composability

Theoriq is developing a composable AI Agent platform that allows users to assemble different AI Agents to create more advanced and flexible AI solutions.

• Incentive Mechanisms

Theoriq drives rapid innovation of AI Agents through incentive mechanisms, laying the groundwork for it to become a modular and composable AI Agent.

• Decentralized Architecture

Theoriq's Infinity Hub provides services such as model training, inference, and data storage, ensuring model accuracy, censorship resistance, tamper resistance, and data privacy through proof mechanisms.

Opportunities and Challenges: Incubated by the ChainML team, Theoriq is an important part of ChainML's goal to become a "decentralized OpenAI GPT Store." The core development team comes from Canada and Germany, with a deep technical background and years of experience at major companies such as Teradata and Vector Institute. Over the past two years, Theoriq and ChainML have collectively raised $10 million in funding, with investment institutions including Hack VC, IOSG Ventures, Hashkey Capital, Alliance DAO, and LongHash Ventures.

Theoriq accurately captures the pain points of centralization and inadequate empowerment of AI Agents in their development. Key proponents of AI agents such as Professor Andrew Ng, Vitalik Buterin, and CZ have shown interest in the project's Twitter account. Similar to Spectral, Theoriq is a project serving "AI for Web3," aiming to establish a calling and economic system for Web3 using AI Agents through the Agentic Protocol. The growth flywheel will also be constrained by the quality and quantity of Agents on the platform.

GaiaNet

GaiaNet is a decentralized computing infrastructure that enables everyone to create and deploy their own AI Agents, reflecting their style, values, knowledge, and expertise.

Through DAO governance, GaiaNet organically links AI Agent developers, domain operators, token stakers, and users, forming a business loop where domain operators manage AI Agent developers, token stakers provide collateral by staking tokens on domain operators, and users choose AI Agents in domain operators to pay for using tokens.

It is worth mentioning that there is also a role in the GaiaNet network called component developers, who can earn income by fine-tuning NFT-based models, knowledge bases, plugins, and other components from AI Agent developers with calling demands.

GaiaNet's core competitiveness in the Web3 + Agent track lies in:

• Edge Computing

GaiaNet is building a distributed edge computing node network controlled by individuals and enterprises, used to host fine-tuned AI models with proprietary domain knowledge and expertise. This approach enhances the diversity and expertise of AI models.

• Privacy Protection

GaiaNet's solution emphasizes protecting user privacy while providing AI capabilities, aligning with Web3's emphasis on user data sovereignty.

• Integration of Expertise

GaiaNet allows individuals and enterprises to integrate proprietary knowledge and skills into AI Agents, embodying the decentralized sharing and application of knowledge, which is in line with the spirit of Web3.

Opportunities and Challenges: GaiaNet is a node-based AI Agent creation and deployment environment, with the protection of experts' and users' intellectual property and data privacy as its starting point, countering the centralized OpenAI GPT Store. GaiaNet has built a complete decentralized AI inference usage scenario, from front-end chatbot usage scenarios, node AI inference, fine-tuning model providers, knowledge base providers, to the underlying decentralized computing power supply. The challenge for GaiaNet lies in how to fully productize the grand and complex roadmap and how to open up to the composability of Web2 AI agents and other Web3 AI infrastructure.

Conclusion

AI Agents not only represent a major leap forward in the field of AI, but also an indispensable part of the Web3 ecosystem. Based on Multi-Agent collaboration, they will jointly create a more intelligent, efficient, and decentralized world.

With the continuous emergence and development of top Web3 AI Agent projects such as HajimeAI and Spectral, we have witnessed the deep integration of AI Agents and blockchain technology, as well as their potential in driving industry progress, optimizing user experience, lowering entry barriers, and innovating applications. They not only provide rich choices for developers and users, but also bring unprecedented vitality and possibilities to the entire Web3.

A Web3 AI Summer, reminiscent of the DeFi Summer, is on the horizon, and AI Agents are giving it unlimited potential. Let's wait and see.

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