<?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/44847c8e4f1b4697b9302d79079089dd&quot; frameborder=&quot;0&quot; width=&quot;1658&quot; height=&quot;1243&quot; webkitallowfullscreen mozallowfullscreen allowfullscreen&gt;&lt;/iframe&gt;</html><height>1243</height><width>1658</width><provider_name>Loom</provider_name><provider_url>https://www.loom.com</provider_url><thumbnail_height>1243</thumbnail_height><thumbnail_width>1658</thumbnail_width><thumbnail_url>https://cdn.loom.com/sessions/thumbnails/44847c8e4f1b4697b9302d79079089dd-a8da689225738124.gif</thumbnail_url><duration>210.304</duration><title>How Agents Match Slack and Linear Work</title><description>This Loom explains how a system automatically monitors Slack conversations and Linear data to match tasks and surface blockers. It demonstrates that items can appear mismatched, such as Slack conversation work not matching a Linear ticket, which leads to gaps like an unresolved blocker until the API team provides the needed API access. The speaker notes that some work is blocked waiting for API access, while other conversion references show no matching Linear ticket. The system is described as finding differences and notifying users about issues in company workflows.</description></oembed>