AI Track Showing Signs of Fatigue, Will Niche Agents Break the Deadlock?

Original Article Title: Vertical Agents: The Crypto-Native Agent Use Cases
Original Article Author: Defi0xJeff, Founder of Steak Studio
Original Article Translation: Ashley, BlockBeats

Editor's Note: This article explores the application of AI Agents in Web2 and Web3. While Web2 has widely adopted AI Agents to enhance efficiency across sales, marketing, and other fields, Web3 has opened up new application scenarios by combining blockchain technology, especially in the DeFi and decentralized domains. Web3 Agents, through token incentives, decentralized platforms, and on-chain data, have the potential to surpass Web2 Agents. The author points out that although Web3 faces challenges in the short term, its unique advantages make it likely to compete with Web2 in the medium to long term and redefine the industry landscape.

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

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

We have moved from manual digital processing by humans, performing repetitive tasks, 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 $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 the sales/marketing process.

Bild_AI

Reading architectural blueprints, extracting material/spec data, and estimating costs based on the collected data.

Casixty

Marketing Agent, identifying popular topics on Reddit, automating responses, and increasing brand engagement. Imagine this product applied to CT!

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

Web3 AI Agents not only focus on operational efficiency but also integrate blockchain technology, unlocking entirely new use cases.

Web3 AI Agent: More Than Just "Buzzword Bingo" Bots

Just a few months ago, most Web3 Agents were mere conversational bots on Twitter. However, the landscape has significantly shifted. 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, spanning from social media interactions to automated trading and DeFi operations.

Cod3xOrg, @Almanak__

No-code infrastructure allowing users to create autonomous trading Agents.

gizatechxyz

Custom DeFi assistant tailored for investors.

DeFi is the largest sector in cryptocurrency (TVL exceeding $100 billion), and the most impactful crypto-native AI Agent use case falls under DeFAI.

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

Blockchain provides a wealth of structured data — credentials, transaction history, P&L, governance activities, lending models, and more. AI can handle, analyze, and extract insights from this data, automate workflows, and enhance decision-making.

Web2 Vertical Agent Driven by Cryptographic Technology

We are also witnessing the integration of Web2 vertical agents with the crypto-native model. A typical example is the launch of virtuals_io on Solana.

_PerspectiveAI

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

Roboagent69

Acting as a personal assistant, booking flights, taxis, purchasing groceries, and scheduling meetings.

HeyTracyAI

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

Unlike the SaaS model, these agents typically rely on a token-gating mechanism where users must stake or hold a certain amount of tokens to access advanced features while maintaining free basic-level 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 $1-2 million in annual recurring revenue to compete effectively. However, in the medium to long term, the Web3 model has intrinsic advantages:

Community-driven growth powered by token incentives and alignment.

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

Furthermore, the rise of DeepSeek and the interest of Web2 AI talent in open-source AI further accelerate the synergistic effect between crypto and AI.

Key Applications of Crypto-Native AI Agents

DeFAI – Abstraction Layer, Automated Trading Agent, and Staking/Lending/Borrowing Solution, serving as the front end of DeFi infrastructure while enhancing the efficiency of DeFi products.

Research & Inference Agent – AI-driven research co-pilot that analyzes data, removes noise, and generates actionable insights. A recent favorite of mine is the Security Agent, for example:

@soleng_agent – Analyzing GitHub repository as a DevRel Agent.

@CertaiK_Agent – AI-based audit service identifying potential threats (soon to launch an Agent scoring system).

Data-Driven AI Agent – Utilizing on-chain data and social data to drive autonomous decision-making and execution.

These three areas represent the most promising directions for the application of Crypto-Native AI Agents.

Conclusion

The market has undergone a consolidation phase for over a month, with altcoins and Agent-related tokens experiencing a significant pullback. However, we are nearing a stage where the fundamentals of tokens are becoming clearer.

Web2 vertical Agents have already proven their value, with many companies willing to pay substantial fees for AI-driven automation. Meanwhile, Web3 vertical Agents are still in the early stages but hold immense potential. 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: Can Web3 vertical Agents achieve a level of adoption equivalent to Web2, or will they redefine the entire industry landscape by leveraging the native advantages of blockchain?

As vertical AI Agents in both Web2 and Web3 continue to evolve, the boundaries between them may blur. Teams that can successfully blend the best features of both – harnessing the efficiency of AI and the decentralization of blockchain – may shape the automation and intelligence in the next generation of the digital economy.

Related Reading: "YC Spring Startup Guide Released: Besides AI Agents, What Other Tracks Could Be the Next Trend?"

「Original Post Link」