Anthropic 为 Claude 推出动态工作流，最多可并行编排 1,000 个 AI 智能体

Anthropic's Claude can now orchestrate up to 1,000 AI agents in parallel through dynamic workflows

文章要点

1Anthropic 为 Claude Managed Agents 推出动态工作流，由主智能体拆解任务、分发给子智能体并汇总结果。
2单次执行最多支持 1,000 个智能体并行运行，选择 multiagent_20261001 智能体类型即可激活。
3Anthropic 官方测试在 116,000 行代码库中藏入 70 个 bug，单智能体每轮发现 14 至 27 个，动态工作流稳定发现 66 个。
4OpenAI 一位高级工程师称智能体集群是 token 的巨大浪费，Anthropic 因 token 消耗大建议从小规模开始。

决策要点

多智能体编排从实验走向托管平台的标准功能，但 token 成本是否划算，业界仍有明显分歧。

影响：代码查错这类可量化验证的任务多了一个并行编排选项；官方提示 token 消耗很大，相关成本预算需要重新测算；检出效果数字目前只覆盖官方自己的测试场景。
参考：可考虑在代码查错等能量化结果的任务上先做小规模试点，对比单智能体与动态工作流的检出率和 token 成本，再决定是否扩大范围。
依据：检出率数据来自 Anthropic 官方测试，暂无独立验证；成本质疑出自 OpenAI 一位高级工程师的个人说法。

正文

Anthropic is adding dynamic workflows to its Claude Managed Agents, bringing multi-agent orchestration to the platform. The managed agent infrastructure has been around for a while, but dynamic workflows are new. A lead agent creates a plan, distributes tasks to sub-agents, and merges the results when they're done. Up to 1,000 agents can run in parallel per execution.

Whether this is cost-effective seems debatable. A senior OpenAI engineer recently called agent swarms a massive waste of tokens, but Anthropic points to its own testing: The team hid 70 bugs in a 116,000-line codebase and found that a single agent caught between 14 and 27 per run, while the dynamic workflow consistently hit 66. Whether those gains hold across different task types remains to be seen, so, as always, it's worth testing with your own workloads.

To activate dynamic workflows, select the "multiagent_20261001" agent type. Because these workflows can burn through "a lot of tokens," Anthropic recommends starting small. You can get going through the documentation or by running "/claude-api managed-agents-onboard" in Claude Code.

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