<?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>Memory on danilchenko.dev</title><link>https://danilchenko.dev/tags/memory/</link><description>Recent content in Memory on danilchenko.dev</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Fri, 17 Apr 2026 10:00:00 +0000</lastBuildDate><atom:link href="https://danilchenko.dev/tags/memory/index.xml" rel="self" type="application/rss+xml"/><item><title>Agentic Memory: The Paper That Teaches LLMs to Manage Their Own Memory</title><link>https://danilchenko.dev/posts/agentic-memory-llm/</link><pubDate>Fri, 17 Apr 2026 10:00:00 +0000</pubDate><guid>https://danilchenko.dev/posts/agentic-memory-llm/</guid><description>A new paper from Alibaba teaches LLM agents to store, update, and delete their own memory via reinforcement learning. Beats Mem0 and A-Mem on 5 benchmarks.</description></item></channel></rss>