自己动手做编排器，比依赖供应商强
作者用6个月自建了一套Agent编排器，包含路由、动态工作流、验证器、MCP工具等功能。他通过挖掘Agent会话记录递归构建和测试新想法，涵盖自主循环和持续学习系统。他认为锁定特定工具或模型供应商风险过高，必须自己控制成本、决策和上下文管理。这为应对本周Fable事件提供了最佳防御。
I spent the last 6 months building my own harness and orchestrator. I built it to allow me to expe...
I spent the last 6 months building my own harness and orchestrator. I built it to allow me to experiment on the frontier of ideas. Little did I know that the orchestration, the harness, routing capabilities, dynamic artifacts/workflows, verifiers, ability to switch/route between agent backends, automations, the skills, and the MCP tools would be the absolute best defense for what happened with Fable this week. The argument folks made when I was talking about "owning the agent orchestrator" at the beginning of the year is that this is just high maintenance, too costly, and is unsustainable. It might still feel like it to many. But there is too much to lose if you decide to lock yourself in with a specific tool or model provider. Really, the way I have built my orchestrator is through mining my agent sessions and using that to recursively build and test our new ideas that range from autonomous loops to continual learning/memory systems. I can test research ideas on the fly. I just can't go back to using a vendor that only offers me a set of features. My argument now is that you really don't have a choice. You need to be able to control cost, decision making, context management, and everything in between. If you don't, then how are you going to tap into the world of recursive self-improving AI? It won't get any easier if you don't own the decision-making part of the intelligence stack. 💬 0 🔄 0 ❤️ 2 👀 103 📊 1 ⚡