第二天，销售回复开始涌入。Stuyvenberg 让 AI 继续操作：每隔几分钟检查邮件，把最低报价转发给其他经销商，要求他们“看看能不能给出更低的价格”。当销售试图打电话或发短信推进沟通时，AI 礼貌地把对话引回邮件，让整个流程更可控。
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Even though my dataset is very small, I think it's sufficient to conclude that LLMs can't consistently reason. Also their reasoning performance gets worse as the SAT instance grows, which may be due to the context window becoming too large as the model reasoning progresses, and it gets harder to remember original clauses at the top of the context. A friend of mine made an observation that how complex SAT instances are similar to working with many rules in large codebases. As we add more rules, it gets more and more likely for LLMs to forget some of them, which can be insidious. Of course that doesn't mean LLMs are useless. They can be definitely useful without being able to reason, but due to lack of reasoning, we can't just write down the rules and expect that LLMs will always follow them. For critical requirements there needs to be some other process in place to ensure that these are met.，详情可参考旺商聊官方下载
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