The AI track shows signs of fatigue; will vertical agents break the deadlock?

Original Title: Vertical Agents: The Crypto-Native Agent Use Cases
Original Author: Defi0xJeff, Head of steak studio
Original Compiler: Ashley, BlockBeats

Editor's Note: This article explores the applications of AI Agents in Web2 and Web3. Web2 has widely adopted AI Agents to enhance efficiency across various fields, including sales and marketing. Web3, on the other hand, combines blockchain technology to unlock new application scenarios, particularly in DeFi and decentralized domains. Web3 Agents have the potential to surpass Web2 Agents through token incentives, decentralized platforms, and on-chain data. The author points out that while Web3 faces challenges in the short term, its unique advantages position it to compete with Web2 and redefine the industry landscape in the medium to long term.

The following is the original content (reorganized for readability):

When we examine general application scenarios outside of Web3, many companies, from large enterprises to small businesses, have begun to integrate AI Agents into their daily operations—sales, marketing, finance, legal, IT, project management, logistics, customer service, workflow automation—almost every conceivable field.

We have transitioned from manually handling numbers, executing repetitive tasks, and filling out Excel sheets to having autonomous, 24/7 online digital workers (AI Agents). These Agents are not only more efficient but also significantly reduce costs.

Web2 companies are willing to pay between $50,000 to $200,000 or even more for AI-driven sales and marketing Agents. Many Agent providers operate highly profitable businesses through SaaS subscription models or consumption-based models (charging based on token usage).

Web2 AI Agent Application Scenarios

Apten_AI

AI + SMS Agent, facilitating sales/marketing processes.

Bild_AI

Reads architectural blueprints, extracts material/specification data, and estimates costs based on the collected data.

Casixty

Marketing Agent that identifies trending topics on Reddit, automates responses, and increases brand engagement. Imagine this product applied to CT!

These examples demonstrate how AI Agents have already transformed traditional industries by automating manual tasks and optimizing workflows. While Web2 companies have rapidly adopted AI-driven Agents, the Web3 space has also begun to embrace this technology—but with a key distinction.

Web3 AI Agents not only focus on operational efficiency but also integrate blockchain technology to unlock entirely new application scenarios.

Web3 AI Agents: More Than Just "Fluff" Bots

A few months ago, most Web3 Agents were merely chatbots on Twitter. However, the industry landscape has significantly changed. These Agents are now integrating with various tools and plugins, enabling them to perform more complex operations.

sendaifun

Solana AI Agent suite, supporting everything from basic token management to complex DeFi operations.

ai16zdao

Integrated with over 100 plugins, from social media interactions to automated trading and DeFi operations.

Cod3xOrg, @Almanak__

No-code infrastructure that allows users to create autonomous trading Agents.

gizatechxyz

Autonomous DeFi assistant tailored for investors.

DeFi is the largest sector in cryptocurrency (with TVL exceeding $100 billion), and the most influential crypto-native AI Agent application scenarios belong to DeFAI.

AI Agents in DeFi not only simplify complex experiences through NLP interfaces but also leverage on-chain data to unlock new opportunities.

Blockchain provides a wealth of structured data—credentials, transaction history, profit and loss, governance activities, lending patterns, etc. AI can process, analyze, and extract insights from this data, automating workflows and enhancing decision-making capabilities.

Crypto-Driven Web2 Vertical Agents

We are also witnessing the fusion of Web2 vertical Agents with crypto-native models. A typical example is the launch of virtuals_io on Solana.

_PerspectiveAI

AI-driven fact-checking, continuously improved through community feedback.

Roboagent69

Acts as a personal assistant, booking flights, taxis, grocery shopping, and arranging meetings.

HeyTracyAI

AI-driven sports commentary and analysis, starting with the NBA.

Unlike the SaaS model, these Agents typically rely on token-gated mechanisms, where users must stake or hold a certain amount of tokens to gain premium access while maintaining free basic tier access. Revenue is generated through token transaction fees and API usage fees.

Can Web3 AI Agents Compete with Web2 Startups?

In the short term, Web3 teams face challenges in finding product-market fit and achieving meaningful adoption. They need at least $1 million to $2 million in annual recurring revenue to compete effectively. However, in the medium to long term, the Web3 model has inherent advantages:

Community-driven growth propelled by token incentives and alignment.

Global liquidity and accessibility, with decentralized and non-custodial platforms eliminating barriers to adoption.

Additionally, the rise of DeepSeek and the interest of Web2 AI talent in open-source AI further accelerate the synergy between crypto and AI.

Key Application Scenarios for Crypto-Native AI Agents

DeFAI—abstraction layer, automated trading Agents, and staking/lending/borrowing solutions, serving as the frontend of DeFi infrastructure while enhancing the efficiency of DeFi products.

Research and reasoning Agents—AI-driven research copilots that analyze data, filter out noise, and generate actionable insights. Recently, my favorites include security Agents, such as:

• @soleng_agent—analyzing GitHub repositories as a DevRel Agent.
• @CertaiK_Agent—AI-based auditing services that identify potential threats (an Agent rating system will be launched soon).
• Data-driven AI Agents—utilizing on-chain data and social data to drive autonomous decision-making and execution.

These three areas represent the most promising application directions for crypto-native AI Agents.

Conclusion

The market has been integrated for over a month, and altcoins and Agent-related tokens have experienced significant pullbacks. However, we are approaching a stage where the fundamentals of tokens are becoming clearer.

Web2 vertical Agents have proven their value, with many companies willing to pay substantial fees for AI-driven automation. Meanwhile, Web3 vertical Agents are still in their early stages, but their potential is immense. By combining token-based incentives, decentralized access, and deep integration with blockchain data, Web3 AI Agents have the opportunity to surpass their Web2 counterparts.

The core question remains: Will Web3 vertical Agents achieve adoption levels comparable to Web2, or will they redefine the entire industry landscape by leveraging blockchain-native advantages?

As vertical AI Agents in both Web2 and Web3 continue to evolve, the lines between them may blur. Teams that successfully integrate the best features of both—leveraging the efficiency of AI and the decentralization of blockchain—may shape the automation and intelligence of the next generation of the digital economy.