<?xml version="1.0" encoding="UTF-8"?><oembed><type>video</type><version>1.0</version><html>&lt;iframe src=&quot;https://www.loom.com/embed/6a024ebfec164188bd7de353f16efc57&quot; frameborder=&quot;0&quot; width=&quot;1920&quot; height=&quot;1440&quot; webkitallowfullscreen mozallowfullscreen allowfullscreen&gt;&lt;/iframe&gt;</html><height>1440</height><width>1920</width><provider_name>Loom</provider_name><provider_url>https://www.loom.com</provider_url><thumbnail_height>1440</thumbnail_height><thumbnail_width>1920</thumbnail_width><thumbnail_url>https://cdn.loom.com/sessions/thumbnails/6a024ebfec164188bd7de353f16efc57-6cc453a47c2f8a57.gif</thumbnail_url><duration>3352.9485</duration><title>Hierarchical Memory Planning and Reasoning in AI 🤖</title><description>In this video, I demonstrate how to utilize files as a hierarchical memory system within Claude Code, focusing on short-term, long-term, and core memories, as well as a diary for episodic memory. I walk through tasks such as organizing papers and saving memories about ongoing projects. I emphasize the importance of naming agents for better interaction and memory sharing. Additionally, I discuss the potential risks of memory poisoning and the need to manage what is remembered. I encourage viewers to implement these memory systems in their own workflows and be mindful of the information stored.</description></oembed>