Interpretation of Y Combinator’s Spring Entrepreneurship Guide, Six Major AI Agent Track Layout for Future Entrepreneurship

AI agents are redefining the way we interact, build, and automate in Web2 and Web3.

Author:0xJeff

Compiled by: Shenchao TechFlow

Y Combinator recently released its Spring 2025 Request for Startups, which lists the directions they want more entrepreneurs to focus on. These ideas reflect the emerging trend of AI agents in Web2, focusing on solving practical problems and pain points, including:

• AI App Store

• data center

• Compliance and audit tools

• DocuSign 2.0 (the next generation electronic signature solution)

• Browsers and computer automation tools

• AI personal assistant

• Agent development tools (Devtools)

• The future of software engineering (engineering agents)

• AI Commercial Open Source Software

• Agents that optimize code for hardware

• Business-to-Agent (B2A)

• Vertical domain AI agents (agents focusing on specific industries or scenarios)

• Reasoning AI infrastructure (the technical foundation that supports efficient reasoning and operation of AI models)

These directions are very informative, but if you are already deeply involved in this field, you will find that many Web3 agent teams have already laid out in these areas.

If you want to learn more about these trends, check out the original post posted by @ycombinator:

I think the following areas will become key trends in the development of Web3 AI agents (in no particular order):

1. AI Commercial Open Source Software

2. Agent development tools (Devtools)

3. Vertical domain AI agent

4. AI personal assistant

5. AI App Store

6. B2A (Business-to-Agent)

1.AI commercial open source software

Web3 AI has a natural connection with open source AI, which makes the open source field an important driving force for Web3. Take@ai16zdao as an example. They have promoted one of the largest open source AI movements. The ElizaOS framework they launched has currently received 14k stars and 4,227 forks on GitHub. Despite market volatility, adoption of this framework is steadily increasing.

This open source movement has also inspired Web3 developers to open source their own technologies, pushing teams to develop AI technologies and frameworks that allow other developers to collaborate more efficiently. In recent years, we have seen many open source frameworks that surpass ElizaOS emerge, such as @arcdotfun,@GAME_Virtuals,@sendaifun,@pippinlovesyou and @freysa_ai, which together promote the development of the open source innovation ecosystem.

With the rapid development of AI agents, such as the o3 launched by OpenAI, the new models released by DeepSeek, and the accelerated launch of related products by technology giants, the demand for open source AI and Web3 AI is heating up. The combination of cryptocurrency and AI (Crypto x AI) is expected to occupy an important position in the AI market.

2. Devtools for AI Agents

Building AI agents is not just about creating intelligent models, but also needs to provide developers withEfficient tools and infrastructureHelp them transform these agents into practical applications. As AI agents become more complex,Developer demand for friendly tools, frameworks and platforms is also growing rapidlyThese tools can simplify the process of building, deploying and managing agents.

In the Web2 era, the popularity of developer tools has significantly improved the capabilities of AI technology. Web3 further promotes this trend byIntroduce features such as decentralization, trustlessness, and open source collaboration, bringing new possibilities to AI development. We are moving into a new era in whichAI agentThe construction, iteration and large-scale deployment of new technologies will no longer rely on the capabilities of a few technology giantsclosed ecosystem。

This trend has given rise to many aspects AI development platform,agentEcosystem and codeless/low-code (No-code/Low-code) tool.These tools aim to lower the threshold for AI agent development and make it easier for more developers to participate.

In the field of Web3, more and more platforms are beginning to provide AI agent development toolkits to help developers quickly create and commercialize AI-based applications. Some noteworthy examples include:

• @ai16zdao: Launched ElizaOS, which has the richest plug-ins and integrated functions.

• @sendaifun: Solana Agent Kit, which focuses on agent development on the Solana blockchain.

• @CoinbaseDev: CDP Agent Kit provides basic tools for the development of on-chain AI agents.

• @autonolas: Launch Pearl, a utility-focused Agent App Store that provides services such as predictive markets, DeFi automation, and autonomous executing agents.

• @AlloraNetwork: Provide machine learning infrastructure to help AI agents make more accurate predictions in real time.

• @cookiedotfun: Focus on AI agent-driven data analysis to help agents extract social emotional information from on-chain and off-chain data.

• @getmasafi: Provide real-time data streaming solutions to provide AI agents with the latest dynamic intelligence.

Some code-less AI platforms focused on Web3 include:

• @virtuals_io: The leading non-code/low-code AI agent construction platform that helps developers quickly transform AI agents from concepts to actual products.

• @HoloworldAI: A code-less platform that focuses on building 3D audio-visual AI agents to help users design AI-driven virtual characters.

• @Cod3xOrg: A code-less tool specifically designed for automated trading agents that helps traders automate trading strategies with AI.

• @Almanak__: A platform specially developed for institutional-level quantitative agents to support the application of advanced financial scenarios.

• @EliteAgents_AI: Focus on plug-in enhanced AI agents and seamlessly integrate with AI ecosystems such as ElizaOS and G.A.M.E.

Although Web3 ‘s AI development tool ecosystem is still in its infancy, its infrastructure is rapidly improving. In the next few years, we hope to seeThe emergence of a fully decentralized AI development ecosystem。In this ecosystem, AI agents will become easier to build and have full autonomy, scalability and commercialization capabilities. The development tools that drive this transformation will become indispensable infrastructure in the Web3 AI economy.

3. Vertical AI Agents

AI agents are gradually evolving from universal tools for performing simple tasks to highly specialized vertical domain agents. These agents focus onAbility to handle complex and sophisticated tasks in specific industries or scenarios。By deepening their domain knowledge, they can not only complete basic automation, but also serve as decision-making agents to perform operations that require deep human expertise.

Today, the wave of AI-driven verticalization is gradually emerging. In fields such as finance, law, and scientific research, agents already have the ability to analyze, recommend, and even perform operations on behalf of users. This vertical trend will further enhance the effectiveness of AI agentsThe influence and depth of application in various industries.

Some typical examples of Vertical AI Agents include:

• taxagent: Help users calculate, optimize and implement tax-saving plans.

• legalagent: Ability to review contracts and optimize terms, and even represent users in legal disputes.

• financialagent: Analyze financial statements, interpret macroeconomic trends, and provide investment advice.

What makes Web3 unique to vertical domain AI agents is its emphasisAutonomy, decentralization and On-chain Integration。Traditional AI services often rely on centralized data silos, while Web3 ‘s native AI agents achieve greater transparency and trust through On-chain verifiability. This feature gives Web3 agents more advantages in data processing and results credibility.

In the cryptocurrency space,Community interaction and personalization are particularly importantTherefore, Web3 AI agents are developing in a more personalized and interactive direction. Unlike the usually cold and only functional AI agents in Web2,Web3 agents have gradually formed unique personalities and interaction patterns, to adapt to the culture of decentralized communities. For example:

• AI influencers: For example,@aixbt_agent shares unique insights and cutting-edge market information on Crypto Twitter to attract community attention.

• agent: For example,@unit00x0,@kwantxbt,@tri_sigma_,@mobyagent and @_AgentScarlett focus on analyzing token data and providing relevant suggestions.

• studyagent: For example,@DV_Memetics and@S4mmyEth provide actionable market intelligence through @orbitcryptoai.

• DeFAI agent: Focus on managing liquidity mining (LP ing), yield farming (Yield Farming) and trading strategies, developed by teams such as@Cod3xOrg,@gizatechxyz and @autonolas.

In addition, AI model platforms such as @NousResearch,@BagelOpenAI and @PondGNN are further enhancing the personalization capabilities of agents to make them more suitable for the needs of decentralized communities. As DeFAI agents gradually simplify the complex operations of DeFi, they could become a key driving force in attracting billions of new users into the blockchain world. These agents provide users with a more intuitive experience by lowering the threshold for DeFi, and are expected to set off a new wave of AI adoption in the future.

4. AI personal assistant

AI personal assistants are revolutionizing the way we handle daily tasks, making many previously unimaginable functions a reality by providing convenience and automation. These assistants will no longer be limited to reminders and scheduling, but will be able to proactively make decisions, helping users manage time and resources more efficiently.

Imagine an AI that can book travel for you, recommend restaurants based on your preferences, check traffic, and automatically adjust meeting schedules when you are late. It can also summarize meeting content, make follow-up suggestions, and even automatically book transportation. In addition, it can organize your photos, classify them by location and event, and generate beautiful memory albums that are easy to review at any time.

With the support of Web3, these features will be further expanded:

• airdropagent (Airdrop Agents): Help users scan all wallets and automatically detect whether they meet the airdrop conditions of encrypted items (such as @berachain,@monad_xyz,@StoryProtocol).

• Income agriculture and liquidity mining managementagent (Yield Farming & LP Management Agents): Track and optimize DeFi positions in real time, automatically collect rewards and compound gains into the best strategy.

• GitHub warehouse analysisagent: For example,@soleng_agent can evaluate the strength of the project development team and help users identify potential scams.

• automated tradingagent (Automated Trading Agents): For example,@Cod3xOrg and @Almanak__execute trades based on preset conditions and optimize the timing of entering and leaving positions to maximize market returns.

The next generation of AI personal assistants will no longer be passive assistants, but co-pilots who can take proactive actions. As AI models continue to improve their reasoning and decision-making capabilities, these agents will shift from responsive to predictive, able to complete complex multi-step tasks with minimal user input.

Web3 plays a key role in this transformation. Decentralized AI agents have trust, transparency and censorship resistance, ensuring that users have complete control over AI-driven workflows. This ability will allow users to hand complex financial and operational decisions to AI, revolutionizing the way we work.

5. AI App Store

AI app stores are one of the most anticipated developments in the field of artificial intelligence. Just as mobile app stores have changed the way software is distributed, AI agents also need a dedicated market where users can easily discover, purchase, and integrate AI-driven applications.

In Web3, this concept is evolving intomoreagentMulti-Agent Orchestration Network (MAO) and Agent Distribution Network combination of:

• agentAgent Distribution Network: Attract developers, investors and users to the ecosystem. For example,@virtuals_io is building an Agent Society where different AI agents can coexist and collaborate with each other.

• MAO Network: Through intelligent matching technology, recommend appropriate AI applications to users and efficiently coordinate the collaborative work of multiple agents. Users do not need to manually search, only need to express their needs, and the system can instantly combine solutions that meet their needs.

Therefore, Web3 ‘s AI application store is not just a trading market. It also needs to have functions such as planning, review and privacy protection, while supporting seamless interaction between agents. This model will completely change the way users interact with AI and lay the foundation for the future AI ecosystem.

Key players driving development in this area:

• @virtuals_io: Committed to expanding its blueprint for Agent Society, attracting high-quality agent teams to join, and taking the lead in developing inter-agent communication protocols to lay the foundation for agent collaboration.

• @santavirtuals and @questflow: Optimize resource allocation efficiency by improving the coordination capabilities between Virtuals agents.

• abstraction layer (Abstraction Layers) Projects such as @orbitcryptoai and @HeyAnonai: By integrating AI agents and decentralized finance (DeFi) into an efficient abstraction layer, the barrier to use is lowered and more users can easily access these technologies.

Although AI orchestration is still in its early stages, it is foreseeable that seamlessly operating and profitable AI agents will open up a huge market, and Web3 is actively deploying to occupy an important position in this market.

6.B2A (Business-to-Agent)

AI agents are now more than just tools; they are becoming active participants in the digital economy, able to complete transactions, manage resources, and even collaborate with other agents on their own. This trend has given rise to new infrastructure requirements, and B2A (Business-to-Agent) has emerged to provide services specifically for AI agents.

Just as SaaS (Software-as-a-Service) has changed the way enterprises operate, B2A will redefine the way AI agents interact, transact, and operate in the digital economy. In the future, AI agents will require exclusive payment solutions, data access, computing power, and privacy protection frameworks. Currently, multiple Web3 projects are driving this transformation:

• AI Business Payments (AI-commerce Payments):@Nevermined_io is developing a payment solution for agents with the goal of becoming the PayPal of AI agents.

• Computing resource management (Compute Management): Self-sustaining agent developed by @hyperbolic_labs can efficiently manage its own computing resources.

• Privacy and Security Infrastructure Infrastructure):@PhalaNetwork,@OraProtocol and @brevis_zk are building a privacy-friendly computing layer to provide a secure and verifiable interactive environment for AI agents.

• Quality Data Access:@getgrass_io,@vana,@getmasafi and @cookiedotfun provide structured, high-quality data sources to help AI agents train, learn and operate efficiently.

• agentAgent-to-Agent Communication:@virtuals_io is developing an inter-agent communication protocol to enable AI agents to collaborate efficiently.

• AI intellectual property (Intellectual Property for AI):@StoryProtocol is developing a TCP/IP-like framework to manage intellectual property rights for AI-generated content, allowing agents to independently manage and authorize content they create.

B2A is not just a theoretical concept, it is becoming a reality.As AI agents continue to increase in functionality and complexity, they require specialized infrastructure to support their independent operation in economic ecosystems. If you haven’t started thinking about how to serve the AI agent market, you may have missed the opportunity.

Summarize thinking

AI agents are redefining the way we interact, build, and automate in Web2 and Web3. With the rise of the Web3 native AI ecosystem, they have brought new models, including open source collaboration, agent-driven business models, and decentralized automation solutions.

Although the integration of AI and encryption technology is still in its early stages, its development momentum is unstoppable. Web3 provides AI agents with key capabilities that Web 2 cannot achieve: such as asset ownership, a permission-free innovation environment, and a highly composable ecosystem. These characteristics create infinite possibilities for an agent-driven economy. The question is no longer whether AI agents will change Web3, but how quickly this change will come and which industries will be at the core of this change.

As the size of the agent-driven economy continues to expand, whether you are a developer, investor, or a curious observer, now is the best time to focus on this area. Infrastructure is being built rapidly, key players are being formed, and opportunities are emerging.

So the question is: Are you ready to join this wave of change?

Welcome to join the official social community of Shenchao TechFlow

Telegram subscription group: www.gushiio.com/TechFlowDaily
Official Twitter account: www.gushiio.com/TechFlowPost
Twitter英文账号：https://www.gushiio.com/DeFlow_Intern