人工智能代理的演变：从聊天机器人到专家助理

随着人工智能代理领域的发展，市场已经从最初只专注于个性化的代理发生了巨大转变。

As the field of AI agents has evolved, the market has shifted dramatically from agents that were initially focused on personalization alone. In the early days, people were attracted to agents that could entertain, tell jokes, or "create a buzz" on social media. These agents did generate buzz and attention, but as the market evolved, it became clear that utility value was far more important than personalization.

随着人工智能代理领域的发展，市场已经从最初只专注于个性化的代理发生了巨大转变。早期，人们被那些可以娱乐、讲笑话或在社交媒体上“引起轰动”的经纪人所吸引。这些代理商确实引起了轰动和关注，但随着市场的发展，很明显实用价值比个性化更重要。

Many agents that focused on personalization generated huge attention when they were launched, but eventually faded into obscurity because they failed to provide value beyond surface-level interactions. This trend highlights a key lesson: in the Web3 space, substantive value takes precedence over superficial effects, and practicality trumps novelty.

许多专注于个性化的智能体在推出时引起了巨大的关注，但最终因为无法提供超越表面交互的价值而变得默默无闻。这一趋势凸显了一个重要的教训：在Web3领域，实质性价值优先于表面效果，实用性胜过新颖性。

This evolution is in line with the transformation of the Web2 AI field. Specialized large language models (LLMs) are being developed to meet the specific needs of niche areas such as finance, law, and real estate. These models focus more on accuracy and reliability, making up for the shortcomings of general AI.

这种演变与Web2 AI领域的变革是一致的。专门的大语言模型 (LLM) 正在开发中，以满足金融、法律和房地产等利基领域的特定需求。这些模型更注重准确性和可靠性，弥补了通用人工智能的缺点。

The limitation of general AI is that it can often only provide "almost" answers, which is unacceptable in some scenarios. For example, a popular model may only be 70% accurate on a specific professional problem. This may be sufficient for daily use, but it can have disastrous consequences in high-stakes scenarios such as court decisions or major financial decisions. This is why professional LLMs that are finely tuned to achieve 98-99% accuracy are becoming increasingly important.

通用人工智能的局限性在于它往往只能提供“几乎”的答案，这在某些场景下是不可接受的。例如，一个流行的模型对于特定的专业问题可能只有 70% 的准确率。这可能足以满足日常使用，但在法院判决或重大财务决策等高风险场景中可能会产生灾难性后果。这就是为什么经过精心调整以达到 98-99% 准确率的专业法学硕士变得越来越重要。

So the question is: Why choose Web3? Why not let Web2 dominate the professional AI field?

那么问题来了：为什么选择Web3？为什么不让Web2主导专业AI领域呢？

Web3 has several significant advantages over traditional Web2 AI:

与传统的Web2 AI相比，Web3有几个显着的优势：

Web3 AI EcosystemIn the Web3 AI agent ecosystem, we see that each ecosystem improves its capabilities by integrating new features and opening up new application scenarios. From Bittensor subnets to Olas, Pond, and Flock, these ecosystems are building more interoperable and functional agents. At the same time, easy-to-use tools such as SendAI's Solana Agent Kit or Coinbase CDP SDK are also emerging.

Web3 AI生态系统在Web3 AI代理生态系统中，我们看到每个生态系统都通过集成新功能、开辟新应用场景来提升自身能力。从 Bittensor 子网到 Olas、Pond 和 Flock，这些生态系统正在构建更具互操作性和功能性的代理。与此同时，SendAI 的 Solana Agent Kit 或 Coinbase CDP SDK 等易于使用的工具也不断涌现。

These ecosystems are building AI applications that prioritize utility:

这些生态系统正在构建优先考虑实用性的人工智能应用程序：

Individual agents focused on real use casesOutside the ecosystem, individual agents in specialized fields are also emerging. For example:

专注于真实用例的个体代理在生态系统之外，专业领域的个体代理也在不断涌现。例如：

This shift from “chatbots chatting away on social media” to “experts sharing professional insights” is here to stay.

这种从“聊天机器人在社交媒体上聊天”到“专家分享专业见解”的转变将会持续下去。

The future of AI agents lies not in chatbots that chat casually, but in expert agents in various professional fields that deliver value and insights in an engaging way. These agents will continue to create mindshare and guide users to actual products, whether it is a trading terminal, tax calculator or productivity tool.

人工智能代理的未来不在于随意聊天的聊天机器人，而在于各个专业领域的专家代理，以引人入胜的方式提供价值和见解。这些代理商将继续创造思想共享并引导用户使用实际产品，无论是交易终端、税务计算器还是生产力工具。

Where will value be concentrated?The biggest beneficiaries will be the proxy L1 and coordination layers.

价值会集中在哪里？最大的受益者将是代理L1和协调层。

Final ThoughtsThe narrative of AI applications that prioritize practicality has just begun. Web3 has a unique opportunity to carve out a space where AI agents can not only entertain, but also solve practical problems, automate complex tasks, and create value for users. 2025 will witness the transition from chatbots to collaborative assistants, and specialized LLMs and multi-agent orchestration will redefine the perception of AI.

最后的想法 以实用性为优先的人工智能应用的叙述才刚刚开始。 Web3 有一个独特的机会来开辟一个空间，让人工智能代理不仅可以娱乐，还可以解决实际问题、自动化复杂任务并为用户创造价值。 2025 年将见证从聊天机器人到协作助理的转变，专业的法学硕士和多代理编排将重新定义人工智能的认知。

While Web2 and Web3 will gradually merge, the open, collaborative nature of Web3 will lay the foundation for the most innovative breakthroughs. It is no longer about "AI agents with personality", but about agents that can provide practical value and create meaningful impact. It is worth paying attention to agentic L1, coordination layer, and emerging AI applications. The era of agency has arrived, and this is just the beginning.

虽然 Web2 和 Web3 将逐渐融合，但 Web3 的开放、协作性质将为最具创新性的突破奠定基础。它不再是“有个性的人工智能代理”，而是能够提供实用价值并产生有意义影响的代理。值得关注的是代理 L1、协调层和新兴的人工智能应用。代理时代已经到来，而这仅仅是开始。