Original Title: The Agentic Economy: Web2 & Web3 AI Agent Trends
Original Author: 0xJeff (@Defi0xJeff)
Translation by: Asher (@Asher0210_)
Y Combinator (YC, one of the most renowned startup accelerators in the world, headquartered in Silicon Valley, USA, has incubated well-known companies such as Airbnb, Stripe, Dropbox, Reddit, Coinbase, OpenAI, etc., with a high success rate and influence) has released its "Request for Startups" for Spring 2025, listing ideas they hope to see more founders explore. Many of these ideas indicate that the application of AI agents in the Web2 space is becoming an emerging trend, aimed at solving real pain points.
I believe the areas that will shape the trends of Web3 AI agents are: AI commercial open-source software, development tools for AI agents, vertical AI agents, AI personal assistants, AI app stores, and B2A.
AI Commercial Open Source Software
Web3 AI is closely related to open-source AI, making it a natural fit in this field. The ai16z DAO is leading one of the largest open-source AI movements, with its ElizaOS framework currently having 14,000 stars and 4,227 code forks on GitHub. Despite market fluctuations, the adoption rate continues to rise.
This movement has inspired Web3 developers to open-source their technologies, encouraging teams to build AI technologies and frameworks that allow other developers to use and collaborate more easily than ever before. In addition to ElizaOS, we have also witnessed the rise of frameworks such as arc, GAME BY VIRTUALS, SendAI, pippin, and Freysa, collectively driving the development of an open-source innovation ecosystem.
As AI agents continue to evolve, OpenAI has launched o3, DeepSeek has released new models, and tech giants are accelerating their layout of AI agents, the demand for open-source AI and Web3 AI is rapidly growing. Crypto x AI may ultimately occupy a significant share in the AI market.
Devtools for AI Agents
Building AI agents is not just about creating intelligent models; it is more crucial to provide developers with the right tools and infrastructure to efficiently implement these agents. As the complexity of AI agents continues to increase, the demand for developer-friendly tools, frameworks, and platforms is surging to support their construction, deployment, and management.
In the Web2 era, a plethora of development tools enhancing AI capabilities have emerged, and Web3 is further accelerating this process. By introducing decentralization, trustless mechanisms, and open-source collaboration, Web3 breaks the limitations of traditional closed ecosystems, allowing the development and deployment of AI agents to no longer rely on systems controlled by a few tech giants.
This trend has driven the rise of AI-focused development platforms, agent ecosystems, and no-code/low-code building tools, significantly lowering the barriers to creating AI agents, enabling more developers to easily participate and accelerating the innovation and popularization of AI technology.
In the Web3 space, an increasing number of platforms are beginning to offer AI agent development toolkits, allowing developers to create and monetize AI-driven applications more easily. Some noteworthy examples include:
ai16zDAO: ElizaOS, with the most plugins and integration support;
SendAI (Solana Agent Kit) and Coinbase Developer Platform (CDP Agent Kit): These toolkits provide developers with the basic components to build on-chain AI agents;
Pearl in the Olas ecosystem: An AI agent app store focused on practical functionalities, covering prediction markets, DeFi automation, and autonomous execution agents;
Allora: Provides machine learning infrastructure to help AI agents make more accurate predictions in real-time;
Cookie DAO: Focused on data analysis driven by AI agents, helping AI agents extract social sentiment insights from on-chain and off-chain data;
Masa: Provides real-time data stream solutions, offering AI agents the latest intelligent information.
Some no-code AI platforms focused on Web3 include:
Virtuals Protocol: A leading no-code/low-code AI agent building platform and launchpad, helping developers turn AI agents from concept to usable products with minimal investment;
Holoworld AI: A no-code building tool focused on 3D audiovisual AI agents, helping users design AI-driven virtual characters;
Cod3x: A no-code platform specifically for building autonomous trading agents, helping traders automate trading strategies using AI;
Almanak: A building platform for institutional-level quantitative agents, focusing on advanced financial application scenarios;
Elite Agents: Focused on plugin-enhanced AI agents, integrating with ElizaOS, G.A.M.E, and other AI ecosystems.
The ecosystem of development tools for Web3 AI is still in its early stages, but the infrastructure is rapidly being built and improved. With continuous technological advancements, a fully decentralized AI development ecosystem is expected to emerge in the coming years. In this ecosystem, AI agents will not only become easier to build but will also possess fully autonomous, scalable, and monetizable capabilities. One of the key factors driving this transformation will be the tools that support developers, which will become the most valuable infrastructure in the Web3 AI economy.
Vertical AI Agents
AI agents are gradually evolving from simple task execution tools into highly specialized intelligent agents tailored for specific industries, capable of handling complex and detailed business operations. These agents leverage domain expertise, surpassing basic automation functions, becoming intelligent entities with decision-making capabilities that can perform tasks typically requiring deep human expertise.
With this development, a wave of AI-driven industry verticalization is rising, covering fields such as finance, law, and research. The capabilities of AI agents are continuously enhancing, enabling them not only to analyze and recommend solutions but also to execute decisions and operations on behalf of users, driving profound transformations across various industries.
Some notable examples of vertical AI agents include:
Tax agents: Capable of calculating, optimizing, and executing tax-saving strategies;
Legal agents: Able to review contracts, detect unfavorable terms, and propose more favorable alternatives (even representing you in legal disputes);
Financial agents: Capable of analyzing financial statements, interpreting macroeconomic trends, and generating investment insights.
The difference in the application of vertical AI agents in Web3 compared to Web2 mainly lies in the emphasis on autonomy, decentralization, and on-chain integration. Unlike traditional AI services that rely on centralized data silos, Web3 native AI agents possess on-chain verifiability, thus providing higher transparency and trust.
Moreover, in the Web3 space, community interaction and individuality are crucial, which also influences the development direction of Web3 AI agents. Unlike the typically impersonal, purely functional AI agents in Web2, Web3 AI agents are gradually developing unique personalities and interaction patterns to better fit the culture of decentralized communities. Here are some typical examples:
AI influencers, such as aixbt, share insights and investment information by analyzing crypto-related content on the X platform;
Token analysis agents, such as Rei, kwantxbt, 3σ, Moby AI, and Agent Scarlett;
Research agents, such as Deep Value Memetics and s4mmy, provide actionable intelligence through Orbit;
DeFAI agents manage LP provision, yield farming, and trading strategies, developed by teams like Cod3x, Giza, and Olas.
As AI model platforms like Nous Research, Bagel, and Pond continue to enhance the personalities of agents, the application scenarios for Web3 native AI are rapidly evolving. DeFAI agents simplify the complexities of DeFi and guide the next wave of billions of users, potentially becoming the next major wave of AI adoption.
AI Personal Staff
AI personal assistants are revolutionizing the way people handle daily tasks, bringing unprecedented convenience and automation. The functions of these assistants will no longer be limited to simple reminders and scheduling; in the future, they will proactively make decisions for users, optimizing the use of time and resources.
For example, an AI can not only book travel but also recommend the best restaurants based on user preferences, check traffic conditions, and even reschedule meetings if the user is running late. It can summarize all meetings, suggest follow-up actions, and even book transportation when needed. At the same time, the AI will automatically organize photos, tag locations and events, and create convenient memory albums for users to access at any time.
In the Web3 ecosystem, the applications of AI personal assistants will further expand:
Airdrop agents: Scan user wallets to determine eligibility for upcoming airdrops;
Yield farming and LP management agents: Automatically track and rebalance DeFi positions, claim rewards, and compound under optimal strategies;
GitHub repository analysis agents: Such as SOLENG, assess whether a project's development team is strong or if the project might be a scam;
Automated trading agents: Such as Cod3x and Almanak, automatically enter and exit the market based on preset trading conditions, optimizing profits and adjusting according to market changes.
The next development of AI personal assistants will be fully autonomous intelligent agents that are not just assistants but partners capable of taking proactive actions. As the reasoning and decision-making capabilities of AI models continue to improve, these agents will shift from passive responses to actively predicting user needs and executing complex multi-step tasks with minimal human intervention.
Web3 plays a crucial role in this transition: decentralized AI agents possess trust, transparency, and censorship resistance, ensuring that users have complete control over their AI-driven workflows. By outsourcing AI's automatic decision-making and task execution, especially in financial and operational decisions, the existing ways of working will be significantly transformed.
AI App Store
The AI app store is one of the most exciting and inevitable advancements in the AI field. Just as mobile applications have their own app stores, AI agents also need a dedicated marketplace where users can discover, purchase, and seamlessly integrate AI-driven applications.
In Web3, this concept is evolving into a combination of Multi-Agent Orchestration Networks (MAO) and agent distribution networks:
Agent distribution networks drive market construction by attracting builders, investors, and users into the ecosystem. Virtuals Protocol is a typical representative of this model, building an agent society where different AI agents can live and interact;
MAO networks ensure that AI applications can accurately match user needs, coordinating agents to efficiently deliver value. Users no longer need to manually search for applications; they simply state their needs, and suitable AI agents will be recommended, even forming solutions instantly.
Therefore, the AI app store in Web3 is not just a marketplace; it must also curate and review applications, ensure privacy, and facilitate seamless interactions between agents.
Key players are driving this advancement, including:
Virtuals Protocol, expanding its vision of an agent society, attracting high-quality agent teams, and developing inter-agent communication protocols;
Santa by Virtuals and Questflow, optimizing coordination among Virtuals agents to improve resource allocation efficiency;
Abstract layers like Orbit and Hey Anon help integrate AI agents with DeFi, enhancing their accessibility.
While AI collaborative management is still in its early stages, it is evident that the ability to seamlessly operate and monetize AI agents will become a massive market, with Web3 occupying a significant market share.
B2A (Business-to-Agent)
AI agents are no longer just tools; they are gradually becoming active economic participants capable of trading, managing resources, and even autonomously collaborating with other AI agents. This transformation requires a new infrastructure that serves not only humans but also AI agents as clients. This is the concept of B2A.
Just as SaaS (Software as a Service) changed the way businesses operate, B2A will define how AI agents interact, transact, and operate in the digital economy. AI agents will need their own payment solutions, data access, computing power, and even privacy frameworks. Some Web3 projects are already paving the way for this:
AI business payments: Nevermined is developing agent-native payment solutions, effectively becoming the "PayPal for AI agents";
Computing management: Hyperbolic is developing self-sustaining agents capable of efficiently managing their computing resources;
Privacy and security infrastructure: Phala Network, ORA, and Brevis are building privacy-preserving computing layers for AI agents, ensuring secure and verifiable interactions;
Quality data access: Grass, vana, Masa, and Cookie DAO are providing structured high-quality data sources for AI agents, helping them train, learn, and operate effectively;
Inter-agent communication: Virtuals Protocol is building inter-agent communication protocols to enable AI agents to collaborate with each other;
AI intellectual property: Story is developing a TCP/IP-like framework for AI-generated content, allowing agents to autonomously manage and license their creations.
B2A is not just a theoretical concept; it is actively being constructed. As AI agents become more complex, they will require specialized infrastructure to operate independently within the economic ecosystem. If you haven't considered how to serve AI agents as a market, you are already falling behind.
Conclusion
AI agents are shaping the way we interact, build, and automate in Web2 and Web3. With the rise of the Web3 native AI ecosystem, they bring a new paradigm that drives the development of open-source collaboration, agent-driven business, and decentralized automation.
Although the integration of AI and crypto is still in its early stages, the momentum of this trend is undeniable. Unlike Web2, Web3 offers unparalleled advantages for AI agents: ownership, permissionless innovation, and a fully composable ecosystem. Therefore, the question is no longer whether AI agents will reshape Web3, but how quickly this transformation will occur and which industries will become the leaders of the future.
As the agent-driven economy continues to expand, future opportunities are also growing immensely. Whether you are a developer, investor, or curious observer, now is the best time to pay attention to this field. The infrastructure is being rapidly built, key players are beginning to emerge, and potential opportunities are everywhere.
The only question is: will you be a part of it?
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