video1.0<iframe src="https://www.loom.com/embed/5936cd9779504aa5a7dce5d72370c35d" frameborder="0" width="1280" height="960" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>9601280Loomhttps://www.loom.com9601280https://cdn.loom.com/sessions/thumbnails/5936cd9779504aa5a7dce5d72370c35d-47800f1471456996.gif298.3656In this video, I’m excited to share a demo of the muscle memory system I've been developing. This system allows agents to log and replay tool actions in familiar environments, significantly reducing token costs and improving efficiency. I demonstrate how the engine operates in both agent mode and cache hit scenarios, showcasing its capabilities. Please take a look and let me know your thoughts on the performance and any potential improvements!