Post by Keywords Studios

Is your AI workflow at risk of falling apart when the model changes? Here is how we set up model-agnostic workflows at Keywords Studios. Across our AI art R&D projects, we have gone through the same trial-and-error process in different pipelines, from character creation and storyboarding to 3D creation and gameplay trailer generation. What that made clear very quickly: if the workflow depends too heavily on one model, it will not stay useful for long. We needed to build production logic that survives the next wave of tools. That's why we defined stable blocks of work that remain useful even as models change. The essentials we keep coming back to are: a clear definition of done, a shared record of what the workflow already knows, and a clear process for validation. Swipe through for the details. Which of these is the hardest to get right in your team right now? If you already apply a model-agnostic workflow, what other building blocks have turned out useful?