动态工作流解决了 Agent 编排中灵活性和可观测性的痛点，做 Agent 系统或自动化流程的开发者可以直接参考他的实现思路，看完会有启发。
开发者 @omarsar0 分享了他对动态工作流的深度实践，通过反向工程为自己的 Agent 编排器实现了动态生成 harness 的能力，并构建了监控仪表盘。他成功在 Claude Code、Codex 等编码 Agent 中运行动态工作流，用于分支研究、并行任务、Bug 排查、事实核查等复杂场景。作者认为动态工作流是 Agent 协作的重要原语，不仅限于编程，还能扩展到商业、科研等领域。
I am hooked on Dynamic Workflows! The idea of generating harnesses on the fly is so compelling that...
I am hooked on Dynamic Workflows! The idea of generating harnesses on the fly is so compelling that I reverse-engineered it for my agent orchestrator. And then I built a monitoring dashboard (as an HTML artifact) to track tasks, metrics, and reports. I can now use and monitor dynamic workflows in my agent orchestrator with coding agents like Claude Code, Codex, Pi, and even my own custom-built @dair_ai agent. This is clearly the future of working with agents to accomplish complex, long-running tasks. Some use cases I'm having success with: - Branching deep research tasks (with verification) - Parallel deep research tasks - Session mining of all my agent sessions - Bug hunting - Triaging - Fact-checking - LLM councils - AI simulations - Data synthesis - Evals generation ... and many others Dynamic workflows, like agent skills, feel like an important primitive to not only get the most out of agents but also incorporate dynamic behaviors and important components like cooperation and verification. There is so much exploration ground here. The exciting part is that this is not limited to coding tasks; it extends to business use cases and many other technical domains like science and research. Your browser does not support the video tag. 🔗 View on Twitter 💬 9 🔄 9 ❤️ 72 👀 5425 📊 35 ⚡