video1.0<iframe src="https://www.loom.com/embed/bb5263596a9d4be7a906b4c2b34df36a" frameborder="0" width="1334" height="1000" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>10001334Loomhttps://www.loom.com10001334https://cdn.loom.com/sessions/thumbnails/bb5263596a9d4be7a906b4c2b34df36a-64202ced8899786e.gif302.173This Loom demonstrates MOSS, a tool to speed up and de risk hiring by showing what candidates have actually built before you decide. The presenter connects via an MCP to query a database of top AI talent, then retrieves and ranks candidates and opens a specific profile, like Leo Gao, to view endorsements, a skill board, and recorded mock interview practice across April and May. MOSS collects signals by analyzing conversations and project interactions with its AI, including Slack-based PM support and integration with GitHub to review repositories and test and give concrete feedback on each PR. The profile also includes mock interview review artifacts for the candidate.