<?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>Letta on TechLLM</title><link>https://techllm.github.io/tags/letta/</link><description>Recent content in Letta on TechLLM</description><generator>Hugo</generator><language>ko</language><lastBuildDate>Sat, 02 May 2026 00:14:00 +0900</lastBuildDate><atom:link href="https://techllm.github.io/tags/letta/index.xml" rel="self" type="application/rss+xml"/><item><title>AI Agent Memory: 에이전트가 기억하고 학습하게 만드는 설계법</title><link>https://techllm.github.io/posts/letta-agent-memory-context-engineering/</link><pubDate>Sat, 02 May 2026 00:14:00 +0900</pubDate><guid>https://techllm.github.io/posts/letta-agent-memory-context-engineering/</guid><description>Letta의 Agent Memory 글을 바탕으로, 에이전트 메모리를 단순 저장소가 아니라 컨텍스트 엔지니어링 문제로 이해하는 방법을 정리한다.</description></item></channel></rss>