<?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/56a885213477450d8eb1ea67a4c83297&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/56a885213477450d8eb1ea67a4c83297-0a5764e76d3255c7.gif</thumbnail_url><duration>143.456</duration><title>AI Resume Checker: Enhancing Candidate Evaluation 🤖</title><description>In this video, I share an update on my AI resume checker, which successfully processes resumes and appends data to a Google Sheet. I&apos;m pleased with the automation, but I have some questions about how to incorporate additional candidate queries, such as part-time availability and state licensing, into the analysis. Specifically, I need to figure out how to have the AI agent evaluate these responses and append the relevant data accordingly. If a candidate is not licensed in Texas, they would be disqualified, so I want to ensure that this is handled correctly. I would appreciate any thoughts on how to integrate these questions into the existing process.</description></oembed>