How AI Agents Are Reshaping the Future of Web3?

Introduction

The AI Agent has emerged as a standout in this round of the crypto cycle, and Shaw, the founder of ai16z and Eliza, has undoubtedly seized this trend. The ai16z he initiated is the first on-chain fund themed around AI Memes, derived from a satirical expression of the well-known venture capital firm a16z. Starting from zero in fundraising in October 2024, it has rapidly grown to become an AI DAO with a market cap exceeding $2.5 billion on Solana in just a few months. The core of ai16z, ElizaOS, is a multi-agent simulation framework that allows developers to create, deploy, and manage autonomous AI Agents on it. Thanks to its first-mover advantage and the thriving TypeScript community, the Eliza codebase has garnered over ten thousand stars on GitHub, commanding about 60% of the current market share in Web3 AI Agent development.

Despite Shaw being quite controversial on social media platforms, he has undoubtedly become a key figure in the crypto AI space. Tom Shaughnessy, co-founder of leading crypto research institution Delphi Digital, and Ejazz from 26 Crypto Capital conducted an in-depth interview with Shaw on January 6, discussing his views and future judgments on AI Agent use cases in the Web3 industry, covering important topics such as Agent development frameworks, token economics, and the future of open-source AGI platforms.

Main Highlights

• The creation of Eliza Labs and the inside story of ai16z's rapid development
• In-depth exploration of various aspects of the Eliza framework technology
• Analysis of agency platforms and the transition from garbage bots to utilities
• Discussion on token economics and value capture mechanisms
• Explore cross-chain development and blockchain selection
• The vision of open-source AGI and the future of AI agents

Entrepreneurial Experience and Journey in Asia

Shaw shared his frustrations in developing open source projects, as well as how he later focused on AI Agent research and ultimately founded Eliza. He also talked about his recent trip to the developer community in Asia, where he discovered many interesting projects, especially the potential of integrating AI Agents into DeFi protocols.

Discussion on Use Cases and Practicality of AI Agent + DeFi Integration

Shaw believes that the three types of agents with the most business opportunities right now are: agents that can help users make money, agents that can bring products to the right customers, and agents that can save users time. He is particularly optimistic about applications in the DeFi space because it has many arbitrage opportunities. Shaw also discussed the possibility of agents managing funds for trading, as well as the limitations of LLM in trading decisions.

Value of the Agent Framework and the Development Advantages of Eliza

Shaw explained the value of the Eliza framework, believing that the key lies in connecting existing functionalities, changing current models, and bringing products onto social media. He emphasized that Eliza provides end-to-end solutions, significantly lowering the development threshold. Shaw also discussed the reasons for choosing TypeScript as the development language, as well as the advantages of Eliza compared to other frameworks.

The Vision of Open Source AGI and the Future of AI Agents

Shaw believes that AGI is essentially an internet form composed of numerous agents. He envisions a future where multiple open-source models compete and optimize with each other, ultimately forming a multi-agent system similar to the internet. Shaw also discusses the role of cryptocurrencies in realizing this vision, including providing crowdfunding mechanisms and capturing user sentiment needs.

Discussion on Token Economics and Value Capture Mechanisms

Shaw acknowledged that the token economic model of ai16z needs to continuously evolve, and the Launchpad is just the initial version. He emphasized that the future focus is on investing in technologies that can expand the overall ecological value, rather than just simply launching Agents. Shaw also discussed how to drive ecosystem development by accumulating value through tokens, forming a positive cycle.

Exploring Cross-Chain Development and Blockchain Selection

Shaw believes that the future of agents should blur the differences between chains, with tokens frequently bridging between different chains. He stated that the choice of Solana was mainly because users are there, but he does not have a strong preference for the platform. The best strategy is to cover all platforms, observe where users are, and then provide services there.

The Transition from Garbage Bot to Utility

Shaw envisions that AI Agents will soon enter a new stage, capable of performing surprising tasks. He believes that "garbage Agents" may not completely disappear, but more useful Agents will emerge in the future. Shaw also discussed how to improve the credibility and verifiability of Agents, anticipating the emergence of specialized Agent verification systems.