Vertical Proxy: Application Scenarios and Disruptive Potential of Crypto-Native Proxy

Author: 0xJeff, Head of Steak Studio; Translation: Golden Finance xiaozou

When we look at the wide range of application scenarios beyond Web3, many companies, both large and small, have begun to integrate artificial intelligence agents (AI Agents) into their daily operations - including sales, marketing, finance, law, IT, project management, logistics, customer service, and workflow automation, etc. Almost all imaginable areas.

We have transitioned from an era where humans manually processed data, performed repetitive tasks, and filled out Excel sheets to an era where digital workers (AI agents) operate autonomously 24/7. Not only are these agents more efficient, but they also cost significantly less.

Web2 companies are willing to pay $50,000 to $200,000 or more for AI-driven sales and marketing agents. Many proxy providers operate high-margin businesses through a SaaS subscription model or a usage-based model (charging by token usage).

1Application scenarios of AI agents in Web2: insights from Y Combinator

Apten - an agent tool that combines artificial intelligence and SMS technology to optimize sales and marketing processes.

Bild AI – an artificial intelligence tool that can read building blueprints, extract material and specification data, and make cost estimates based on the collected information.

Casixty — a marketing agency tool that identifies trending topics on Reddit, automatically generates replies and increases brand engagement. Imagine what the effect would be if this product was applied to CT (crypto community)!

These cases show how AI agents are changing traditional industries, automating manual tasks and optimizing workflows. While Web2 companies have been quick to adopt AI-driven proxy technology, the Web3 space is also beginning to embrace it — but there is a key difference.

Unlike Web2 which only focuses on operational efficiency, Web3's AI agent is deeply integrated with blockchain technology, thus unlocking new application scenarios.

2Web3 AI Agent: Beyond “Chatting Robots”

A few months ago, most Web3 agents were just conversational robots on Twitter. However, this area has changed significantly. Today, these agents are being integrated with various tools and plugins, enabling them to perform more complex operations.

@sendaifun — Solana AI agent toolkit, supporting a range of functions from basic token management to complex DeFi operations.
@ai16zdao——Integrates more than 100 plug-ins, covering areas such as social media interaction, automated transactions, and DeFi operations.
@Cod3xOrg , @Almanak__ — No-code infrastructure that allows users to create autonomous trading agents.
@gizatechxyz — An autonomous DeFi assistant designed for investors.

As the largest sector in the crypto space (with a total locked value of over $100 billion), DeFi has become the hub of the most influential crypto-native AI agent application scenarios, namely DeFAI (decentralized financial artificial intelligence).

AI agents in DeFi not only simplify complex operations through natural language processing (NLP) interfaces, but also leverage on-chain data to unlock new opportunities. Blockchain provides a rich collection of structured data — including credentials, transaction histories, profit and loss records, governance activities, and lending patterns. AI can process, analyze and extract insights from this data to automate workflows and optimize decision making.

3Web2 vertical field agents based on encryption infrastructure

We have also witnessed the rise of Web2 vertical field agents that integrate encryption native models. A typical example is the launch of Virtuals.io on Solana.

Perspective AI – An AI-powered fact-checking tool that’s continuously refined through community feedback.

R6D9——A personal assistant tool that can book flights, taxis, order groceries, and arrange meetings.

HeyTracyAI - an artificial intelligence-driven sports commentary and analysis platform, initially focusing on NBA events.

Unlike the traditional SaaS (software as a service) model, these agents usually adopt a token gating mechanism, that is, users need to stake or hold a certain number of tokens to obtain advanced access rights, while still being able to use the basic level services for free. Its income mainly comes from token transaction fees and API interface usage fees.

4Can Web3 AI agents compete with Web2 startups?

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

• Community-driven growth: Promoting spontaneous community growth through token incentives and alignment of interests.

• Global Liquidity and Accessibility: The decentralized and non-custodial platform removes barriers to adoption and enables seamless access around the world.

In addition, the rise of DeepSeek and the interest of Web2 AI talents in open source AI are further accelerating the coordinated development of the encryption field and artificial intelligence.

5Core application scenarios of crypto-native AI agents

• DeFAI(Decentralized Financial Artificial Intelligence) - Abstraction layer, automated trading agent, and staking/lending/borrowing solutions: Provide front-end support for DeFi infrastructure and improve the efficiency and user experience of DeFi products.

• Research and Reasoning Agent – ​​AI-powered research assistant: analyzes data, filters noise, and generates actionable insights. My recent personal favorite is Security Proxy. @soleng_agent is a developer relations agent that focuses on analyzing GitHub code repositories and helping developers optimize their projects. @CertiK_Agent provides AI-based auditing services to identify potential threats (agent scoring system coming soon) and provide security assurance for smart contracts and blockchain projects.

• Data-driven AI agents – leveraging on-chain data and social media data to enable autonomous decision-making and execution.
  These three verticals represent the most promising development directions for crypto-native AI agents.

6Summary of the Current Situation and Future Outlook

Over the past month, the market has continued to consolidate, and altcoins and AI agent-related tokens have experienced a sharp correction. However, we are entering a phase where the fundamentals of the token are becoming clearer.

AI agents in Web2 verticals have proven their value, and many businesses are willing to pay high fees for AI-driven automation services. At the same time, AI agents in the Web3 vertical are still in their early stages, but their potential is huge. By combining token incentives, decentralized access, and deep integration with blockchain data, Web3 AI agents have the opportunity to go further than their Web2 counterparts.

But the core question remains: will AI agents in Web3 verticals reach adoption levels comparable to Web2, or will they completely reshape the space by leveraging blockchain’s native strengths?

As vertical AI agents continue to develop in Web2 and Web3, the boundaries between the two may gradually blur. Teams that can successfully combine the advantages of both - leveraging the efficiency of AI and the decentralized nature of blockchain - are likely to shape the future of the next generation of automation and intelligence in the digital economy.