The Rise of the Agent Economy: Trends in AI Agents in Web2 and Web3

Original title: The Agentic Economy: Web2 Web3 AI Agent Trends

Original author: 0xJeff ( @ Defi0xJeff )

Compiled by: Asher ( @Asher_0210 )

Y Combinator (YC, one of the worlds most well-known startup accelerators, headquartered in Silicon Valley, USA, has incubated well-known companies including Airbnb, Stripe, Dropbox, Reddit, Coinbase, OpenAI, etc., with a very high success rate and influence) released its Request for Startups for the spring of 2025, listing the ideas they hope to see more founders explore. Many of these ideas show that the application of AI agents in the Web2 field is becoming an emerging trend, dedicated to solving real pain points.

Personally, I think the areas that will shape the Web3 AI agent trend are: AI commercial open source software, AI agent development tools, vertical AI agents, AI personal assistants, AI app stores, and B2A .

AI Commercial Open Source Software

Web3 AI is closely tied to open source AI, making it a natural fit for the space. ai16z DAO has spearheaded 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 volatility, adoption continues to climb.

This movement has inspired Web3 developers to open source their technologies, driving teams to build AI technologies and frameworks that other developers can use and collaborate with 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 , which have jointly promoted the development of the open source innovation ecosystem.

As AI agents continue to evolve, OpenAI launches o3, DeepSeek releases new models, and tech giants accelerate the deployment of AI agents, the demand for open source AI and Web3 AI is growing rapidly. Crypto x AI may eventually occupy a significant share of the AI market.

Devtools for AI Agents

Building AI agents is not just about creating intelligent models. The key is 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 growing rapidly to support their construction, deployment, and management.

In the Web2 era, a large number of development tools have emerged to enhance AI capabilities, and Web3 is further advancing this process. By introducing decentralization, trustless mechanisms, and open source collaboration, Web3 breaks the limitations of the traditional closed ecosystem, making the development and deployment of AI agents no longer dependent on systems controlled by a few technology giants.

This trend has driven the rise of AI-focused development platforms, agent ecosystems, and no-code/low-code building tools, greatly lowering the threshold for creating AI agents, allowing more developers to easily participate and accelerating the innovation and popularization of AI technology.

In the Web3 space, more and more platforms are beginning to provide AI agent development toolkits, making it easier for developers to create and monetize AI-driven applications. Some noteworthy examples include:

• ai16z DAO : 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 functions, covering areas such as 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 : Focuses on AI agent-driven data analysis, helping AI agents extract social sentiment insights from on-chain and off-chain data;

• Masa : Provides real-time data streaming solutions to provide AI agents with 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 launch platform that helps developers take AI agents from concept to usable products with minimal investment;

• Holoworld AI : A code-free building tool focused on 3D audio-visual AI agents, helping users design AI-driven virtual characters;

• Cod3x : A no-code platform specifically designed for building autonomous trading agents, helping traders leverage AI to automate trading strategies;

• Almanak : A platform for building institutional-level quantitative brokers, focusing on advanced financial application scenarios;

• Elite Agents : Focuses on plugin-enhanced AI agents and integrates with ElizaOS, GAME and other AI ecosystems.

The Web3 AI development tool ecosystem is still in its early stages, but the infrastructure is being built and improved rapidly. As technology continues to advance, a fully decentralized AI development ecosystem is expected to emerge in the next few years. In this ecosystem, AI agents will not only become easier to build, but will also have the ability to be fully autonomous, scalable, and monetizable. One of the key factors driving this change will be 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 tools for performing simple tasks to highly specialized, industry-specific intelligent agents capable of handling complex and nuanced business operations. These agents go beyond basic automation capabilities by leveraging domain expertise to become intelligent agents with decision-making capabilities capable of performing tasks that typically require deep human expertise.

With this development, a wave of AI-driven industry verticalization is emerging, covering finance, law, research, etc. AI agents are becoming increasingly capable of not only analyzing and recommending solutions, but also executing decisions and actions on behalf of users, driving profound changes in various industries.

Some notable examples of vertical AI agents include:

• Tax agent: Able to calculate, optimize and implement tax saving strategies;

• Legal representation: able to review contracts, detect unfavorable clauses, and suggest more favorable alternatives (and even represent you in legal disputes);

• Financial Agents: Ability to analyze financial statements, interpret macroeconomic trends, and generate investment insights.

The difference between Web3 and Web2 in the application of vertical AI agents is mainly reflected in the emphasis on autonomy, decentralization, and on-chain integration. Unlike traditional AI services that rely on centralized data silos, Web3 native AI agents have on-chain verifiability, which can provide higher transparency and trust.

In addition, in the Web3 field, community interaction and personality are crucial, which also affects the development direction of Web3 AI agents. Unlike the AI agents in Web2, which are usually impersonal and purely functional, 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 Platform X;

• 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 agent, which manages LP provision, yield farming and trading strategies, was created by teams including Cod3x , Giza and Olas .

As AI model platforms like Nous Research , Bagel , and Pond continue to enhance the personality of agents, the application scenarios of Web3 native AI are developing rapidly. DeFAI agents simplify the complexity of DeFi and guide the next wave of billions of users to settle in, which may become 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. These assistants will no longer be limited to simple reminders and scheduling, but will proactively make decisions for users and optimize the use of time and resources.

For example, an AI can not only book travel, but also recommend the best restaurants based on the users preferences, check traffic conditions, and even reschedule meetings if the user is late. It can also summarize all meetings, make follow-up suggestions, and even book transportation if needed. At the same time, AI automatically organizes photos, annotates places and events, and creates a convenient memory album for users to access at any time.

In the Web3 ecosystem, the application of AI personal assistants will be further expanded:

• Airdrop Agent: Scans user wallets and determines if they are eligible for upcoming airdrops;

• Yield Farming and LP Management Agent: Automatically track and rebalance DeFi positions, claim rewards and compound interest under the best strategy;

• GitHub repository analysis agents: such as SOLENG , which assess whether the project’s development team is strong or whether the project may 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 making adjustments based on market changes.

The next evolution of AI personal assistants will be fully autonomous intelligent agents, which are not just assistants, but partners that can take proactive actions. As AI models continue to improve their reasoning and decision-making capabilities, these agents will move from passive response to proactively anticipating user needs and performing complex multi-step tasks with little to no human intervention.

Web3 plays a crucial role in this transformation: decentralized AI agents provide trust, transparency, and censorship resistance, ensuring that users have full control over their AI-driven workflows. Automating decision-making and tasks through AI, especially outsourcing of financial and operational decisions, will significantly change the way we work.

AI App Store

One of the most exciting and inevitable developments in AI is the AI app store. Just as mobile apps have their own app stores, AI agents also need a dedicated marketplace where users can discover, purchase, and seamlessly integrate AI-powered apps.

In Web3, this concept is developing into a combination of Multi-Agent Orchestration Network (MAO) and Agent Distribution Network:

• Agent distribution networks drive market construction by attracting builders, investors, and users into the ecosystem. Virtuals Protocol is a typical representative of this model, which is building an agent society where different AI agents live and interact;

• The MAO network ensures that AI applications can accurately match user needs and coordinate agents to efficiently deliver value. Users no longer need to search for applications manually, they only need to state their needs, and suitable AI agents will be recommended or even instantly form solutions.

Therefore, Web3’s AI app store is more than just a market; it must curate and review applications, ensure privacy, and facilitate seamless interactions between agents.

Key players driving this progress include:

• Virtuals Protocol , expanding its agent society vision, recruiting high-quality agent teams, and developing inter-agent communication protocols;

• Santa by Virtuals and Questflow , which optimizes coordination between Virtuals agents to improve resource allocation efficiency;

• Abstraction layers such as Orbit and Hey Anon help integrate AI agents with DeFi and improve its accessibility.

While AI co-management is still in its early stages, it is clear that the ability to seamlessly run and monetize AI agents will become a large market, and Web3 is taking a significant market share for this.

B2A (Business-to-Agent)

AI agents are no longer just tools, they are gradually becoming active economic participants, able to conduct transactions, manage resources, and even collaborate autonomously with other AI agents. This transformation requires a completely new infrastructure that serves not only humans but also AI agents as customers. 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 Commerce Payments: Nevermined is developing an agent-native payment solution, effectively becoming the “PayPal of AI agents”;

• Compute Management: Hyperbolic is developing self-sustaining agents that can efficiently manage its compute resources;

• Privacy and security infrastructure: Phala Network , ORA , and Brevis are building a privacy-preserving computing layer for AI agents to ensure secure and verifiable interactions;

• Access to high-quality data: Grass , vana , Masa , and Cookie DAO are providing structured, high-quality data sources for AI agents to help them train, learn, and operate efficiently;

• Inter-agent communication: Virtuals Protocol is building an inter-agent communication protocol that enables 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 being actively built. As AI agents become more sophisticated, they will require specialized infrastructure to operate independently in the economic ecosystem. If you haven’t yet considered how to serve AI agents as a marketplace, you are already behind.

summary

AI agents are shaping the way we interact, build, and automate in Web2 and Web3. As Web3 native AI ecosystems emerge, they bring a whole new paradigm that drives open source collaboration, agent-driven commerce, and decentralized automation.

Although the convergence of AI and crypto is still in its early stages, the momentum of this trend is already impossible to ignore. Unlike Web2, Web3 offers AI agents unparalleled advantages: ownership, permissionless innovation, and a fully composable ecosystem. Therefore, the question is no longer whether AI agents will reshape Web3, but how quickly this change will happen and which industries will be the leaders of the future.

As the agent-driven economy continues to expand, the opportunities ahead are huge. Whether you are a developer, investor, or curious observer, now is the best time to pay attention to this space. The infrastructure is being built rapidly, key players are beginning to emerge, and the potential opportunities are everywhere.

The only question is: will you be a part of it?