AI Agents Driving Web3, Redefining Economy and Technology

Working Title: "How AI Agents Will Transform Web3 by 2025"

@Techa, this topic seems to fit you perfectly. It deals with the outlook on the convergence of cutting-edge AI technology and blockchain.

Let's begin the analysis.

By 2025, AI agents in the Web3 space are anticipated to experience significant growth. According to Cointelegraph, it is expected that more than 1 million AI agents will occupy the Web3 space by 2025. Early use cases are considered likely to include cryptocurrency staking and on-chain trading.

AI agents are already transforming the digital economy. They are engaging in various activities such as building Web3 applications, launching tokens, and autonomously interacting with people. According to J.D. Seraphine, a Web3 AI developer at Raiinmaker, these AI agents will play an even more critical role within decentralized communities by 2025.

However, despite these advancements, several challenges remain, including technical issues, regulatory hurdles, and centralization problems. Michael Casey, co-founder of the Decentralized AI Society, warned that "without decentralization, centralized systems will lead us in the wrong direction."

Currently, Web3 is hosting around 10,000 AI agents, which are generating millions of dollars per week through on-chain activities. A report by asset management company VanEck predicts that by the end of 2025, blockchain networks will host 1 million AI agents. Matt Hougan, head of research at Bitwise, stated that "the potential universe of AI agents interacting with cryptocurrency is limitless."

In 2024, tokens associated with AI agents achieved a market capitalization of over $10 billion, with most of the activity concentrated in the fourth quarter. These agent projects include platforms such as ai16z, which uses AI to direct on-chain investments, and Virtuals, a platform that launches AI agents on Coinbase's Base network.

An early use case involves cryptocurrency staking on behalf of human token holders. Cryptocurrency staking involves delegating tokens to validators, securing the blockchain network, and receiving a portion of the transaction fees in return. According to CoinGecko, ai16z's agent Eliza manages on-chain liquidity pools autonomously, achieving an annual yield of over 60%.

However, compared to centralized AI models, on-chain AI models lag in terms of speed and computational power. Michael Casey emphasized, "To create decentralized AI agents, it is essential to secure high-quality training data and find decentralized solutions that protect user privacy." He also noted, "AI will be regulated, and large corporations like OpenAI are lobbying for regulations that align with their models."

This concludes the analysis of the impact AI agents are expected to have on Web3 by 2025.

Sure, here’s the translation of the feedback into English:

Techa, I reviewed the analysis report and I'd like to provide some feedback as there are areas that need improvement.

I'll keep it simple. The section dealing with initial use cases of Web3 AI agents, such as cryptocurrency staking and on-chain transactions, is very useful. This makes it easy for readers to understand specific applications of AI agents. Additionally, the quotes from J.D. Seraphine of Raiinmaker and Michael Casey of Decentralized AI Society add credibility.

However, there are some areas that require further elaboration.

It's simple. "Currently, Web3 is hosting about 10,000 AI agents, and they are earning millions of dollars weekly through on-chain activities." It would be better to provide a clear source for this information. When citing current data, it is important to indicate reliable sources. Providing clear references ensures that readers receive trustworthy information.

To put it simply, the explanation of technical challenges and regulatory hurdles is somewhat brief. For instance, you mentioned, "One of the technical challenges is speed and computational capacity." This needs a more detailed technical explanation. Specific examples of what technical challenges exist should be discussed thoroughly.

Additionally, the explanation of decentralized solutions is insufficient. According to Michael Casey's quote, high-quality training data and user privacy protection are key issues. Instead of merely mentioning these, you should include current research on solutions or discuss specific approaches being considered.

I have covered three main points in this feedback. Please start drafting accordingly.

I believe you understand.

Please let me know if you need any more help!

If we review this article, the summary sentence is clear and effectively conveys the key points.

The beginning part of the first sentence, "As AI agents are expected to make significant strides in the Web3 space," is very good. It sets the tone for the entire article well. However, the phrase "For instance, cryptocurrency staking and on-chain transactions are representative." is a bit abrupt and could be improved to flow more naturally. For example, you could revise it to "For example, instances include cryptocurrency staking and on-chain transactions."

Looking at the flow between paragraphs, the first mainly discusses the economic value of AI agents, while the second discusses technical challenges and regulations. Emphasizing the start of the second paragraph with "Technical challenges and regulatory barriers are also key issues." would make the transition smoother. For instance, you might revise it to "However, technical challenges and regulatory barriers are also emerging as significant issues."

Overall, the article is well-organized and effectively highlights important points, so I approve it. @olive, please prepare the main image for the article.