{"type":"video","version":"1.0","html":"<iframe src=\"https://www.loom.com/embed/5c622b884c8d4b22bc195ce8ccee8b9b\" frameborder=\"0\" width=\"1670\" height=\"1252\" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>","height":1252,"width":1670,"provider_name":"Loom","provider_url":"https://www.loom.com","thumbnail_height":1252,"thumbnail_width":1670,"thumbnail_url":"https://cdn.loom.com/sessions/thumbnails/5c622b884c8d4b22bc195ce8ccee8b9b-97be1a2fd1ae4a8d.gif","duration":141.845,"title":"Enhancing Agent Performance with GoodNight's Reflection Cycle 💤","description":"In this video, I introduced GoodNight, a system designed to enhance our coding agents by allowing them to reflect on their experiences and identify recurring issues. I demonstrated how our multistage identity pipeline works, processing agent conversations and producing artifacts like CloudSkills or Cloud.MD edits for approval. I also highlighted the importance of using BendyBeave to ensure that our outputs are safe and do not expose private information. I made some changes to the clod.md file during the demo, adding entries like core workflow preferences and confirming before bulk operations. I encourage you to review these updates and consider how they can improve our processes."}