<?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/12a035661ca2490f9dae1f70452cc792&quot; frameborder=&quot;0&quot; width=&quot;1886&quot; height=&quot;1414&quot; webkitallowfullscreen mozallowfullscreen allowfullscreen&gt;&lt;/iframe&gt;</html><height>1414</height><width>1886</width><provider_name>Loom</provider_name><provider_url>https://www.loom.com</provider_url><thumbnail_height>1414</thumbnail_height><thumbnail_width>1886</thumbnail_width><thumbnail_url>https://cdn.loom.com/sessions/thumbnails/12a035661ca2490f9dae1f70452cc792-5d9eecc26efa8e2d.gif</thumbnail_url><duration>459.98</duration><title>Clay Uni - AI Formulas and Conditional Runs</title><description>In this video, I delve into the power of AI formulas in Clay, showcasing how they can manipulate data effortlessly without consuming credits. I demonstrate how to extract valuable insights from enriched data, such as education and job experiences, using AI formulas. Additionally, I explore the significance of conditional runs in Clay, illustrating how they can optimize workflows by executing specific actions based on predefined conditions. No action is requested from the viewers in this video.</description></oembed>