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      <title>How Slack Manages Context in Long-Running Multi-agent Systems</title>
      <link>https://www.infoq.com/news/2026/04/slack-agent-context-management/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Slack</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/04/slack-agent-context-management/en/headerimage/slack-context-management-agents-1777407896875.jpeg"/&gt;&lt;p&gt;To sustain productivity in long-running agent systems, Slack engineers moved away from accumulating chat logs and started using structured memory, validation, and distilled truth to maintain coherence and accuracy of long-running agent systems.&lt;/p&gt; &lt;i&gt;By Sergio De Simone&lt;/i&gt;</description>
      <category>Agents</category>
      <category>Large language models</category>
      <category>Slack</category>
      <category>AI, ML &amp; Data Engineering</category>
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      <pubDate>Tue, 28 Apr 2026 21:00:00 GMT</pubDate>
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      <dc:creator>Sergio De Simone</dc:creator>
      <dc:date>2026-04-28T21:00:00Z</dc:date>
      <dc:identifier>/news/2026/04/slack-agent-context-management/en</dc:identifier>
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