想解决Agent盲目信任检索结果的问题？听Qdrant团队拆解自我改进循环，还和Future AGI、AWS的工程师同场交流。
Qdrant团队的JKupchanko41535在活动中介绍如何构建自我改进的检索循环。该循环能检测弱检索结果、动态调整策略，并在必要时重试、升级或终止，防止Agent产生幻觉。同场还有Future AGI的Nikhil Pareek和AWS代表分享相关技术。活动于7月29日下午5点在旧金山AWS Builder Loft举行，现场有实际基础设施演示。
Most agents trust the first search result and keep going, even when retrieval fails. That's the pro...
Most agents trust the first search result and keep going, even when retrieval fails. That's the problem @JKupchanko41535 from the Qdrant team is tackling at this event. His talk covers how to build a self-improving retrieval loop that detects weak results, changes strategy, and knows when to retry, escalate, or stop before the agent hallucinates. Joining him are Nikhil Pareek from Future AGI on engineering self-improving agent systems, Amazon Web Services (AWS) on agentic AI and Amazon Bedrock, and builder demos from teams shipping real agent infrastructure. If you're in San Francisco and building agents, workflows, or AI infrastructure - this is a good room to be in. 📅 July 29th, 5pm PDT 📍 AWS Builder Loft, 525 Market St, San Francisco Register here (AWS registration required for entry) luma.com/future-arpz D7 💬 0 🔄 0 ❤️ 0 👀 111 ⚡