<?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/131da37da34744f7b722d1d1171f9d06&quot; frameborder=&quot;0&quot; width=&quot;1920&quot; height=&quot;1440&quot; webkitallowfullscreen mozallowfullscreen allowfullscreen&gt;&lt;/iframe&gt;</html><height>1440</height><width>1920</width><provider_name>Loom</provider_name><provider_url>https://www.loom.com</provider_url><thumbnail_height>1440</thumbnail_height><thumbnail_width>1920</thumbnail_width><thumbnail_url>https://cdn.loom.com/sessions/thumbnails/131da37da34744f7b722d1d1171f9d06-fed76d8f6bef48b5.gif</thumbnail_url><duration>56.133333</duration><title>Can Wild 6 keep optimizing the solution after launch?</title><description>This Loom explains what happens after launching an AI solution and how to keep improving it. Launch marks the start of the adopt phase, after which real work begins flowing through the system and teams learn things that tests cannot reveal. Before go-live, the creator trains the people who will use the solution and documents the workflow, what the AI should do, the automations, and how the team manages it going forward. They recommend comparing what success was expected to look like during assessment with what is actually happening, so teams can adjust instructions or approvals as needed and take ownership or continue optimization support.</description></oembed>