Author: Jay Jo, Source: Tiger Research, Compiled by Shaw Jinse Finance. Abstract: The AI agent market lost momentum after the token price crash, but technological development continues steadily. The decentralized financial artificial intelligence (DeFAI) sector has regained attention through real product releases and specialized on-chain functions. Specialized AI agents optimized for specific functions are replacing the general-purpose AI agents of the past. Projects like Virtuals are actively building infrastructure to connect these AI agents and enable collaboration. AI agents will become a core feature of crypto projects. Infrastructure that ensures smooth communication and collaboration between agents will become crucial. 1. The hype has passed, but the technology is still evolving. The crypto industry has integrated artificial intelligence technology in various ways, with AI agents attracting the most attention. The total market capitalization of related tokens reached approximately $16 billion at one point, demonstrating strong market interest. However, this attention was short-lived. Most projects failed to meet development expectations, and token prices plummeted by over 90% from their peak. A price drop does not necessarily mean technological regression. AI agents remain an important technology area in the crypto space. Discussions about practical use cases are becoming more concrete, and teams continue to test new approaches. This report explores how AI agents operate in the crypto space and explores potential future developments. 2.1. Early AI Agent Projects Gradually Fade from the Market The AI Agent sector in the crypto space has begun to attract attention since the end of 2024. ElizaOS developed by the ai16z team and the G.A.M.E. development stack developed by the Virtuals Protocol team have significantly lowered the barrier to entry for AI agent development. Launchpads like DAOS.fun and Virtuals Fun provide easy tokenization for established projects. The process from development to launch has become streamlined, leading to a surge in market interest and a rapid emergence of numerous projects. Most projects have ambitious roadmaps, claiming to leverage artificial intelligence technology. Investors, anticipating innovative services, have driven up token prices. However, in reality, these projects have merely fine-tuned or reengineered basic models from OpenAI or Anthropic. Most have simply built advanced chatbots for Facebook or Telegram, rather than developing standalone services. These projects emphasize innovative vision and technological differentiation, but in reality, their operations are no different from "meme coins." Some projects are exceptions. Projects like aixbt and Soleng have partially implemented their roadmaps and launched actual services. They use token gating mechanisms to provide exclusive access to token holders. aixbt provides project analysis reports. Soleng analyzes Github code repositories to support investor decision-making. Even these relatively successful examples cannot overcome structural limitations. Unstable revenue structures that rely solely on token price increases hinder development. Their technological competitiveness lagged behind that of Web2 companies. Token prices eventually plummeted. Operating funds dried up, and most projects have now ceased service. 2.2. DeFAI Projects Revitalize Industry Hopes AI agent technology once faced high expectations and subsequently entered a period of adjustment. Today, the field of decentralized financial artificial intelligence (DeFAI) is regaining attention by proving its practical value. DeFAI agents can execute automated investment strategies 24/7. They provide easy access to complex decentralized finance (DeFi) services through simple natural language commands. This area was a core theme in the early days of the AI agent field. However, most projects remained in the roadmap stage, facing difficulties in practical implementation, and the field briefly lost attention. Recent product releases are reshaping market expectations. Representative projects include Wayfinder and HeyAnon. Wayfinder uses specialized AI agents called "Shells" to perform on-chain tasks. Shells execute on-chain transactions directly through a built-in dedicated wallet. The system utilizes a specialized multi-agent architecture, encompassing trading agents, perpetual agents, and contract agents. Each agent type specializes in a specific role, automating various investment strategies. Users can easily execute simple cross-chain trades or implement advanced strategies such as basis trading and leveraged DCA. 2.3 From Individual Agents to Agent Networks Early AI agent projects championed "general-purpose agents"—intelligent entities capable of performing all functions. This approach prioritized fundraising over technological sophistication. Projects proposed overly ambitious roadmaps to appeal to a broader market. However, most projects exposed limitations during implementation. The current agent ecosystem is developing in a very different direction. Developers, recognizing the limitations of general-purpose agents, are now developing specialized agents. These agents can collaborate with one another, much like skilled craftsmen with diverse expertise—carpenters, electricians, plumbers—working together to build a house. Virtuals Protocol's ACP (Agent Commerce Protocol) embodies this trend. It provides a standard framework for communication and task allocation between different agents. Theoriq and General Impression have also built infrastructure to enhance interoperability between agents. The market is reshaping itself towards maximizing value for the entire ecosystem, rather than for individual agents. 3. Future Prospects for the AI Agent Market After the initial hype has subsided, AI agents continue to evolve. Speculation has subsided, but projects are still leveraging AI agents to build new features and services. Two changes are particularly striking. First, AI agents have become critical infrastructure. No longer a standalone field, they are now integrated into crypto projects as fundamental features. Blockchain data platform Nansen is developing and researching agents to make complex on-chain data easier to explore. Decentralized finance projects are also adding agents to improve user access. AI agents will become the final interface between users and the blockchain, not an optional feature.
Secondly, agent commerce will grow and prosper. As AI agents become standard, interactions between agents and humans will increase. Secure transaction protocols and trust mechanisms will become increasingly important. Projects like Virtuals Protocol's ACP are laying the foundation for this.
These changes will simplify the complexity of cryptocurrency, improve user experience, and create new economic opportunities.
Alex
JinseFinance
Future
Cointelegraph