Original Summary

Most multi-agent write ups are about quality - which model to use and why, more agents and generating better answers. I am interested in the failures that happen.<p>If you run more than one agent against shared state or shared tools, what actually went wrong?<p>1. Did two agents do the same work, or different work that conflicted? 2. Were your agents copies of each other (homogenous agents), or specialized with different roles (heterogenous)? 3. What did you add to stop or prevent the failure?<p>Anthropic&#x27;s multi-agent research found that agents are low-variance: 18 of 30 independently created a git branch with the identical name. That suggests the common failure is correlated duplication rather than disagreement. Does that match what you have seen, or do yours diverge?

  • 情报分类：技术学习与提效
  • 分类依据：内容涉及技术、AI、软件工具或工程实践
  • 信息来源：Hacker News 新项目
  • 发布时间：2026/10/2 01:03:54