<?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>Architecture on MK's Lab</title><link>https://blog.mklee.org/tags/architecture/</link><description>Recent content in Architecture on MK's Lab</description><generator>Hugo -- 0.146.0</generator><language>zh-tw</language><lastBuildDate>Thu, 16 Apr 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://blog.mklee.org/tags/architecture/index.xml" rel="self" type="application/rss+xml"/><item><title>從 OpenAI Agents SDK 偷了三個概念，用在我們的 Claude Code 工作區 template</title><link>https://blog.mklee.org/posts/2026-04-16-workspace-template-v3-openai-sdk-borrowings/</link><pubDate>Thu, 16 Apr 2026 00:00:00 +0000</pubDate><guid>https://blog.mklee.org/posts/2026-04-16-workspace-template-v3-openai-sdk-borrowings/</guid><description>OpenAI 新的 Agents SDK 發布了 Manifest、Capabilities、serialize_session_state 三個概念。我們的 agent workspace template 定位完全不同，但有三個結構性想法值得借過來。</description></item><item><title>AI Agent 記憶的 Context Tree：從日誌地獄到兩層架構</title><link>https://blog.mklee.org/posts/context-tree-agent-memory/</link><pubDate>Sat, 28 Mar 2026 00:00:00 +0000</pubDate><guid>https://blog.mklee.org/posts/context-tree-agent-memory/</guid><description>當 AI agent 的記憶系統塞滿了 37 個檔案，65% 是噪音，你需要的不是更大的 context window，而是更好的架構。這是把扁平日誌改造成 journal + knowledge 兩層記憶的實戰記錄。</description></item><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 自我管理：從 LLM 做所有事到只做該做的事</title><link>https://blog.mklee.org/posts/agent-self-management/</link><pubDate>Fri, 06 Mar 2026 00:00:00 +0000</pubDate><guid>https://blog.mklee.org/posts/agent-self-management/</guid><description>一個 AI agent 如何學會「省著點用 AI」——從全 LLM heartbeat 到 Rust binary，從被動維護到主動自省的演化記錄。</description></item><item><title>OpenClaw 記憶管理：從零到自迭代的架構演化</title><link>https://blog.mklee.org/posts/openclaw-memory-architecture/</link><pubDate>Wed, 18 Feb 2026 00:00:00 +0000</pubDate><guid>https://blog.mklee.org/posts/openclaw-memory-architecture/</guid><description>一個 AI agent 的記憶系統如何從空白 MEMORY.md 演化成帶有 Events Timeline、L0 索引、自動提取規則的結構化架構。</description></item></channel></rss>