Continuing from what GenLayer does in the previous article, today I will talk about which group of people are suitable for using GenLayer! Suggest forwarding and bookmarking to read slowly and directly enter the main topic. In the current era of AI agents, we almost use AI trading bots to scan links or write data every day. The two subjective aspects that have been causing me headaches recently are "achievement verification" and "incentive distribution". Take the AI trading bot+bounty incentive platform that my studio is currently running, for example; After community contributors submit optimization strategy alpha signals or meme marketing plans How to determine if the execution quality of this bot strategy is sufficient? Is there any vulnerability in the backtesting logic? Does creativity have a good grasp of market sentiment? Like before, relying solely on manual review was inefficient, prone to controversy, and delayed many things. But now, since using @ GenLayer, I have basically solved this pain point perfectly. It is an AI validator that can capture on chain transaction data, market feedback, and submit documents in real time, understand the strategic intentions described in natural language, and quickly provide trusted consensus on subjective quality, For example, determining whether "this solution has truly improved the Sharpe Ratio of the bot" or "whether the content is considered high-value by community consensus". The result was directly uploaded to the chain, automatically triggering bounty payment, and the entire process changed from a few days to a few minutes. This not only enhances the efficiency of Bounty platform, but also extends to DeFi insurance claims, real-time verification of vague claim conditions, market prediction, contextual judgment of subjective events' impact on prices', and even automatic collaborative settlement between AI agents. In my opinion, GenLayer, as an on chain trust layer, makes smart contracts no longer a closed code box, but a powerful tool that can truly interact with the real world and solve subjective problems that smart contracts cannot handle. So the question is again: which industry do you think needs this level of AI Truth the most besides predicting the market? I personally believe that decentralized insurance claims is definitely the next track that needs to be thoroughly upgraded. When the claims conditions are vague and the evidence is subjective, AI validators can provide reliable judgments in real time, directly maximizing efficiency and fairness.