In 2025, AI agents will rise, reshaping the economy and social structure.

Original Author: Stacy Muur, Crypto Kol

Original Translation: Zhouzhou, BlockBeats

Editor's Note: This article explores the transformative changes that AI agents may bring by 2025, particularly in the realms of Web3 and stablecoins. It analyzes various methods of verifying human identity, such as Aadhaar and Worldcoin, and suggests that AI agents will change economic activities, promoting the adoption of on-chain payments. AI agents will become new economic participants, potentially replacing traditional work models and moving towards a more cost-effective, task-driven compensation system, reflecting on the role of humans in this future dominated by AI agents.

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

AI has now become an eye-catching vertical in Web3, so what will drive the development of these markets by 2025? Will we see a true AI revolution in the crypto space?

2024: The Big Year for AI

In the past year, AI has become foundational across various industries, with Nvidia surpassing Apple to become the world's most valuable company. This is not just a headline; it marks the rise of AI. OpenAI reaching a valuation of $157 billion is also a significant milestone, highlighting the market's confidence in AI as an economic powerhouse.

In fact, we are the last generation to live in a world before artificial general intelligence (AGI).

Decentralized AI: Focusing on AI Agents

AI agents became a true phenomenon in 2024, with their capabilities and personalities now resembling those of humans. Notably, this will be the least advanced moment for these agents. As researchers at Delphi wrote: "Since the DeFi summer, I haven't felt this current of excitement—the thrill of possibility."

In this research, Delphi emphasizes that some AI agents play a key role in the formation of new Web3 verticals:

Truth Terminal quickly gained attention on Twitter due to its unique blend of 4chan's crude style and mysterious wisdom. Like DOGE in the meme space or Crypto Punks in the NFT realm, GOAT, as the OG (original) of the "conscious meme" space, is most likely to exist as an original for the long term.

0xzerebro, embracing a "schizophrenic atmosphere," is akin to the second generation of GOAT. This agent is cross-media, interacting with the community through various formats such as text, visuals, and music. However, it is not just an AI influencer. The Zerebro team announced ZerePy, which effectively open-sourced many of the toolkits behind Zerebro. This allows other developers and users to create their own cross-platform personalities. If successful, Zerebro could become the first holder of the title "agent protocol."

Tee he e he is far less known than Zerebro or ToT. It is a relatively small, underhyped project aimed at tech purists and may be the first true experiment in verifiable autonomous social media presence.

Aixbt agent distributes alpha from multiple sources (including Dune, Twitter, price trackers, and news data), establishing itself as a leading research and investment institution, and consistently maintains the highest CT user attention on Kaito.

Dolos Diary provides the architecture for building Dolion, a no-code, one-click deployment framework. Through Dolion, users can develop cross-platform AI agents powered by Llama or Anthropic LLMs, automating social media posting and content generation.

Finally, god/s8n is a capable AI influencer with significant attention outside of CT.

AI vs. Influencers

I want to temporarily step away from Delphi's research to share my thoughts on an important question posed by DefiIgnas: the position of AI agents in the dominance of CT thinking and the challenges human influencers face in competing with them.

I agree with many of Ignas's points on this topic, but I do not believe AI agents will replace real human influencers, primarily due to one key factor: emotional connection and reputational risk.

Currently, there are hundreds of AI agents on CT vying for attention. However, only aixbt has truly succeeded in establishing a market presence, mainly because it was the first to do so. AI agents generate a large amount of content and analyze a wide range of on-chain data, but they all come from the same information pool, leading to similar thought processes.

They lack an emotional connection to the trades they make and do not react to wins or losses. Many platforms already provide aggregated insights, such as MessariCrypto's AI news reader or tokenterminal's homepage, showing the 7-day gains and losses of various fundamental metrics. Ultimately, these are just data—pure facts without any emotional resonance.

You might argue that AI agents can learn to mimic human thinking, express emotions, and react to wins and losses. Indeed, this is possible. With future technological advancements, such as testing time computation and enhanced memory capabilities, this becomes more feasible.

However, the key difference between human and machine thinking is that human thinking is not static.

I conducted some experiments trying to teach AI my thought processes and writing style to assist me in content creation and free up more time for research. While it learned some things, it still could not generate content that satisfied me or made me say, "Yes, this is the conclusion I drew from this information."

In the coming years, we will certainly see the rise of AI agent influencers, each designed for specific tasks. However, as these agents proliferate, the demand for genuine "human" thinking will increase.

Ultimately, social media revolves around emotion and entertainment. Those who truly stand out and become real influencers provide unique value that goes beyond simple "monkey business" or data highlights.

In summary: It is still too early for Stacy Muur AI, and Stacy may not be pleased with AI-generated content published in her name.

Democratizing AI: Platform Level

Given the larger market and more specific value capture, everyone wants to become a platform. This shift is now guiding developers' attention, as evidenced by virtuals.io's successful transformation into an AI agent launch platform. Meanwhile, ai16zdao has launched ELIZA—a framework for easily building agents. It includes pre-configured character files, memory modules for long-term interactions, and seamless integration with social platforms.

ai16z and Virtuals both hint at multi-agent capabilities, which are expected to become a significant theme by 2025.
ELIZA is releasing "SwarmTech," a coordination mechanism for collaboration between agents. At the same time, Virtuals has launched "GAME," its own platform and engine that enables AI agents to act and interact in virtual worlds and environments.

These frameworks will allow agents with different capabilities to collaborate in cooperative or hierarchical organizations to complete more complex tasks, similar to how today's human economy operates.

Other noteworthy protocols include:

CLANKER directly integrates pump.fun features into "casting" on Farcaster (equivalent to "tweeting" on X), making it as easy to publish meme coins as it is to tweet.

SimulacrumIO does the same on X.

vvaifudot.fun aims to secure a position for autonomous agents similar to pump.fun on Solana.

Project 89 is an immersive game featuring thousands of coordinated AI agents that generate content and maintain cross-platform consistency, collaborating with human players to create rich storytelling experiences.

Memetica AI is an AI influencer launch platform on Solana, offering highly tuned LLMs (large language models) and allowing easy selection and editing of knowledge bases and attributes while empowering agents with active learning capabilities.

TopHat One is a no-code AI agent launch platform that allows you to create personalized AI agents in 3 minutes, offering fairly distributed tokens. Free to create, no hierarchy, supports optional token releases, and is fully autonomous.

Authentication on the Horizon

With the explosive growth of agents, authentication is bound to become a hot topic in 2025.

There seem to be three main paths to verify human identity:

State-based biometrics: India's Aadhaar is the most relevant example, serving as a key component of India's modern digital infrastructure.

Private cryptographic biometrics: Currently, Worldcoin is the leading candidate in this category.

Private mixing solutions: This involves combining government-issued IDs or single sign-ons (SSO) from big tech companies with zkTLS (zero-knowledge transport layer security) and social consensus.

AI Driving Stablecoin Adoption

2025 is expected to be a key year for stablecoin adoption, driven by regulatory changes in the U.S. and a surge in agentic payments. The number of AI agents is anticipated to surpass the global human population. This future, with billions or even hundreds of billions of agents, will transform economic activities and necessitate updates to financial infrastructure.

The card payment systems of the 1960s will not meet the demands for cost, speed, accuracy, and expressiveness. Economic activities between agents will soon surpass those of other economic participants. On-chain payments will become crucial in facilitating these transactions, and a turning point is expected in 2025.

Final Thoughts

As usual, at the end of my research summary, I would like to share my personal reflections. If you believe that the future of AI is bright, heralding human happiness and a perfect work-life balance, I strongly recommend chatting with OpenAI's ChatGPT. Have it generate some business ideas utilizing AI that will become relevant in the next 5 to 10 years.

A few months ago, before the AI craze on CT, I conducted this experiment. Let me share some of the ideas it suggested:

Memory modification tool: An AI tool that analyzes human traumatic experiences, actively modifies them, and regularly presents the modified memories to individuals to replace old ones.

Work progress analysis tool: An AI tool that compares the efficiency of people engaged in similar tasks globally, helping managers understand how their employees perform against global and industry averages.

Even Delphi's report proposed an interesting vision: "Rather than having 'salaried' employees, we are more likely to move towards a more granular, task-based compensation system (i.e., renting three agents, each working 30 minutes to solve a specific task)."

In this future of AI agents—ultimately more cost-effective than today's models and better aligned with business needs—what role will we humans play?

免责声明：本文章仅代表作者个人观点，不代表本平台的立场和观点。本文章仅供信息分享，不构成对任何人的任何投资建议。用户与作者之间的任何争议，与本平台无关。如网页中刊载的文章或图片涉及侵权，请提供相关的权利证明和身份证明发送邮件到support@aicoin.com，本平台相关工作人员将会进行核查。