<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Summarization on Mohamed Abdelrahman</title><link>https://mkabdelrahman.github.io/tags/summarization/</link><description>Recent content in Summarization on Mohamed Abdelrahman</description><generator>Hugo</generator><language>en</language><lastBuildDate>Thu, 30 Apr 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://mkabdelrahman.github.io/tags/summarization/index.xml" rel="self" type="application/rss+xml"/><item><title>[Draft] Compaction Algorithms for Long-Running Agent Sessions</title><link>https://mkabdelrahman.github.io/posts/agent-context-compaction-strategies/</link><pubDate>Thu, 30 Apr 2026 00:00:00 +0000</pubDate><guid>https://mkabdelrahman.github.io/posts/agent-context-compaction-strategies/</guid><description>&lt;h2 id="the-problem">
 The problem
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&lt;p>A long-running agent accumulates messages over time: user prompts, model responses, reasoning traces, tool calls, tool outputs. The model&amp;rsquo;s context window is finite — from a hundred thousand tokens on the smaller end to a million or more on the largest current frontier models. Once the conversation no longer fits, continuing without intervention triggers a hard error or silent truncation by the provider.&lt;/p></description></item></channel></rss>