<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/"><channel><title>VectorSearch on TechLLM</title><link>https://techllm.github.io/tags/vectorsearch/</link><description>Recent content in VectorSearch on TechLLM</description><generator>Hugo</generator><language>ko</language><lastBuildDate>Sat, 02 May 2026 10:45:00 +0900</lastBuildDate><atom:link href="https://techllm.github.io/tags/vectorsearch/index.xml" rel="self" type="application/rss+xml"/><item><title>엔터프라이즈 AI 에이전트의 다음 병목은 ‘메모리’다</title><link>https://techllm.github.io/posts/oracle-ai-agent-memory-enterprise/</link><pubDate>Sat, 02 May 2026 10:45:00 +0900</pubDate><guid>https://techllm.github.io/posts/oracle-ai-agent-memory-enterprise/</guid><description>Oracle AI Agent Memory 발표를 바탕으로, 기업용 AI 에이전트에서 메모리가 왜 벡터 검색 이상의 거버넌스 인프라가 되는지 정리한다.</description></item></channel></rss>