video1.0<iframe src="https://www.loom.com/embed/0a0d06dcc3d44874b881c3e7ce9e403e" frameborder="0" width="1712" height="1284" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>12841712Loomhttps://www.loom.com12841712https://cdn.loom.com/sessions/thumbnails/0a0d06dcc3d44874b881c3e7ce9e403e-05044631f3e2e7f7.gif145.467This Loom explains how Stackspend was created to prevent surprise AI infrastructure and API costs. Andrew describes getting ambushed by AI bills across tools like Cursor and Claude Code, and a major incident where a Google Cloud account was infiltrated and $12,000 in Gemini API requests were submitted to generate training data. The team built Stackspend to provide a 360 view of AI usage across providers with real-time alerting, forecasting, anomaly detection, and GitHub-linked cost history to identify likely release diffs. The dashboard also includes an explorer and tracked tasks for digging into issues and seeing what changed and when.