请问HN：生产中的多代理工作流程；在哪里有人使用成千上万的代理？
我觉得大多数人工智能工作流程可以通过一个强大的大型语言模型（LLM）或最多五个子代理有效解决。然而，许多工程团队却专注于大规模的多代理架构。
我很好奇，究竟在什么情况下使用大型多代理群体是值得的，以及有哪些生产用例：我想了解这种价值究竟在哪里。
如果您在生产中运行代理群体：主要的用例或需求是什么？您目前最大的痛点是什么（状态同步、代币成本、级联故障、延迟）？
[作为背景：我是一家名为Acyclic Labs（YC F26）的创始人，我们正在构建基础设施以扩展代理。希望能够梳理出何时使用代理群体是合理的，何时又是浪费的！]
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I feel like most AI workflows can be solved pretty effectively by a single capable LLM or with upto 5 subagents however, many engineering teams are focused on multi-agent architectures at huge scales.<p>Curious to understand exactly when it becomes worth it / what production use cases there are for large multi-agent swarms: I’m trying to understand exactly where that value lies.<p>If you are run agent swarms in production: what is the main use case / need and what is your biggest pain point right now (state sync, token costs, cascading failures, latency)?<p>[As context: I am a founder at Acyclic Labs (YC F26) and we are building infra to scale agents. Looking to map out when the swarms are actually justified and when they are wasteful!]