<?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/973658b180c94e08aacf1d4e554c492c&quot; frameborder=&quot;0&quot; width=&quot;1508&quot; height=&quot;1131&quot; webkitallowfullscreen mozallowfullscreen allowfullscreen&gt;&lt;/iframe&gt;</html><height>1131</height><width>1508</width><provider_name>Loom</provider_name><provider_url>https://www.loom.com</provider_url><thumbnail_height>1131</thumbnail_height><thumbnail_width>1508</thumbnail_width><thumbnail_url>https://cdn.loom.com/sessions/thumbnails/973658b180c94e08aacf1d4e554c492c-77a35680d9c63e8c.gif</thumbnail_url><duration>210.788</duration><title>Improving Document Coverage in AI Analysis</title><description>In this video, I address a common question about why the AI only references a few documents in my report analysis. I explain that the AI prioritizes content for efficiency, ranking documents by relevance to the request. I demonstrate a three-step approach to improve document coverage, starting with broad requests and then providing targeted instructions for specific documents. I also show how to include important files, like the employee performance review, in the analysis. Viewers are encouraged to try these methods to enhance their credibility assessments.</description></oembed>