video1.0<iframe src="https://www.loom.com/embed/f5b3e4e9c23941638e08a9c308c9cf0b" frameborder="0" width="1920" height="1440" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>14401920Loomhttps://www.loom.com14401920https://cdn.loom.com/sessions/thumbnails/f5b3e4e9c23941638e08a9c308c9cf0b-59750f7e67cbc64d.gif127.928In this video, I showcase a full-stack web application I've built that uses AI to help developers optimize their SQL queries and identify performance risks. I demonstrate how users can input SQL queries and receive analysis on potential risks, such as scanning entire tables without filtering. For example, I show how adding a WHERE clause can mitigate risks, and I highlight that even with optimizations, issues may arise as data grows. I encourage viewers to try out the application with their own queries and explore the recommendations provided. Overall, it’s a practical tool for improving SQL query performance.