<?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>LLM on MK's Lab</title><link>https://blog.mklee.org/tags/llm/</link><description>Recent content in LLM on MK's Lab</description><generator>Hugo -- 0.146.0</generator><language>zh-tw</language><lastBuildDate>Wed, 18 Mar 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://blog.mklee.org/tags/llm/index.xml" rel="self" type="application/rss+xml"/><item><title>AI Agent 記憶系統的三個難題：壓縮、演化、衝突</title><link>https://blog.mklee.org/posts/ai-agent-memory-three-challenges/</link><pubDate>Wed, 18 Mar 2026 00:00:00 +0000</pubDate><guid>https://blog.mklee.org/posts/ai-agent-memory-three-challenges/</guid><description>context window 有限、偏好會變、新舊記憶會矛盾——分享我們在 OpenClaw 上實作記憶系統時遇到的三個核心難題與解法。</description></item><item><title>讓 AI Agent 學會做夢：記憶的睡眠循環機制</title><link>https://blog.mklee.org/posts/ai-agent-memory-sleep-cycle/</link><pubDate>Tue, 17 Mar 2026 00:00:00 +0000</pubDate><guid>https://blog.mklee.org/posts/ai-agent-memory-sleep-cycle/</guid><description>AI agent 的記憶不該只有寫入和讀取。借鏡人類睡眠的三個階段——做夢、反芻、遺忘——為 agent 建立一套自動化的記憶維護機制。</description></item></channel></rss>