<?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/0094d5bb49234ab0935eb84752424844&quot; frameborder=&quot;0&quot; width=&quot;1728&quot; height=&quot;1296&quot; webkitallowfullscreen mozallowfullscreen allowfullscreen&gt;&lt;/iframe&gt;</html><height>1296</height><width>1728</width><provider_name>Loom</provider_name><provider_url>https://www.loom.com</provider_url><thumbnail_height>1296</thumbnail_height><thumbnail_width>1728</thumbnail_width><thumbnail_url>https://cdn.loom.com/sessions/thumbnails/0094d5bb49234ab0935eb84752424844-8eb4a057b57f77b1.gif</thumbnail_url><duration>606.119</duration><title>Building a Production-Ready Semantic Search Engine from Scratch 🚀</title><description>Hi, I&apos;m Ace, and in this video, I walk you through the Defector DBQ, a production-ready semantic search engine I built from scratch for Stack.ai. I designed it with a four-layer domain-driven architecture for flexibility and scalability, implementing two indexing algorithms: flat indexing for smaller datasets and IVF indexing for larger ones, achieving around 100 milliseconds search time. I also introduced a read-write lock system to handle concurrent requests efficiently. If you have any questions or feedback, please reach out—I&apos;m happy to discuss!</description></oembed>