The previous article talked about GenLayer, and some friends may not fully understand its value. Let's talk from a different perspective this time. I have always believed that what is truly worth paying attention to in the AI field is not just the models becoming smarter, but the AI agents starting to truly work for people, make decisions, and even complete transactions on their own. That's where the problem comes in. What if two agents can negotiate requirements, sign agreements, deliver tasks, and pay fees on their own in the future, and there are problems in between? For example, if an agent spends money to find another agent to write code, does the delivered product meet the requirements? Does a predicted event in the market count as happening? Does a transaction meet the conditions agreed upon by both parties? These problems cannot be solved simply by executing a few fixed codes. Traditional smart contracts excel at deterministic rules: execute when conditions are met, and do not execute when conditions are not met. But the real world is full of ambiguous conditions, natural language, and non standardized demands. The more popular AI agents are, the more they need an infrastructure on the chain that can understand context, judge actual situations, and form results through decentralized consensus. This is also the reason why I have been following GenLayer recently. It does not simply apply a layer of AI to smart contracts, but rather enables intelligent contracts to read web pages, understand natural language, and be independently judged by multiple AI validators. The final result is determined through consensus and appeal mechanisms. Simple understanding: Previously, smart contracts were mainly responsible for executing according to rules. GenLayer aims to solve the problem of how to make judgments on the chain when rules encounter complex real-world situations. Of course, this does not mean that traditional smart contracts will be eliminated. Deterministic rules still have value, but AI judgments also face issues such as model bias and validation costs. But with more and more interactions between agents, who will judge performance and who will resolve disputes may become an unavoidable new requirement. So I think the GenLayer narrative is worth studying in advance. And currently, the participation threshold is very low. With Twitter, you can try it out and participate at zero cost. While understanding the project itself, it can also be considered as familiarizing yourself with the direction of AI Agent+Web3 in advance. Missed in the previous article, you can take a look this time: https://portal.genlayer.foundation/go/bqlsj2023