Qdrant 展示如何构建从运行历史中学习的自愈研究代理
A research agent that gets better from its own run history. At n8n in the loop 2026, @itsclelia, De...
朋友，Qdrant 的 Clelia 要在大会上分享一个很酷的技巧，教你如何让研究代理自己从失败中学习，不用重新训练模型，挺实用的。
在 n8n in the loop 2026 大会上，Qdrant 的 DevRel 工程师 Clelia 将演示如何构建一个自愈研究代理，它从自己的运行历史中学习，无需微调。该代理运行研究并产生答案，然后 Discord 用户给出人类判断，该判断被存储回相同的向量存储中。在下次运行时，代理检索过去的成功和失败案例，以理解什么有效、什么无效。相同的集合成为代理的运行历史、评估集和训练信号，人类在循环中充当作者的角色。
A research agent that gets better from its own run history. At n8n in the loop 2026, @itsclelia, De...
A research agent that gets better from its own run history. At n8n in the loop 2026, @itsclelia , DevRel Engineer at Qdrant, will show how to build a self-healing research agent that learns from its own run history, without fine-tuning. The setup is simple: → The agent runs research and produces an answer. → A Discord user gives it a human verdict. → That verdict is stored back in the same vector store the agent retrieves from. → On the next run, the agent retrieves both past successes and failures to understand what worked and what didn’t. The same collection becomes the agent’s run history, evaluation set, and training signal, with the human in the loop acting as the writer. Date: October 13–14, 2026 Get your ticket now: n8n.io/intheloop/ 💬 0 🔄 1 ❤️ 3 👀 93 📊 1 ⚡