what we're able to do, especially when we you looking at at at videos, A, we we changed from a very complex pipeline, right? To an agentic workflow. The reason behind this is, a, the pipelines work great if you have a very very unique use case. But one once you put put put it in front of users, they'll have a very very distinct story that they want to tell with their own characters, with with their own images, and their own voice. So that's where it starts to drift. But by providing the agents with tools to validate the quality of of the outputs it's creating, it's able to adapt to changes better. It's also able to verify its own work and and and fix things as they go along. So if you're going to steal from from these from the stock of a few things, one, go relative, not absolute, right? As I explained earlier, the the value of comparing video A versus video B will always give you a better result going forward. Be score the real axis that you care about. So if you care about storytelling, if you care about pacing, if you care about physics, score those axes. Don't expect them to miraculously appear. And put eval inside the generation loop, right? Especially if your goal is is is is to have a higher quality of generation, get the the eval as close to to the generation loop loop as possible. Eventually evaluate it as a story. Videos are stories. Videos are just