HN 提问：生产环境中的多智能体工作流；谁在使用数千个智能体？
2 分•作者: ramstar3000•7 天前
我认为大多数人工智能工作流都可以通过一个能力强大的大型语言模型（LLM）或最多五个子代理有效地解决，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，究竟在什么时候，大规模多代理蜂群才真正值得投入，或者说，它们有哪些生产环境下的应用场景：我正试图准确理解其价值所在。
如果您在生产环境中运行代理蜂群，其主要用例/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）？
[背景信息：我是 Acyclic Labs（YC F26）的创始人，我们正在构建用于扩展代理的基础设施。我希望了解代理蜂群何时真正有必要，何时又是一种浪费！]
查看原文
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!]