diff --git a/docs/src/docs/mlops/ci-cd.md b/docs/src/docs/mlops/ci-cd.md
deleted file mode 100644
index 28d7f747..00000000
--- a/docs/src/docs/mlops/ci-cd.md
+++ /dev/null
@@ -1,18 +0,0 @@
-# Continuous Integration and Deployment
-
-## Continuous integration
-
-Ipsum rerum harum officia. Quo sit aut ea. Fuga autem non nostrum debitis. Laboriosam enim quisquam consequatur veniam.
-
-Accusamus et nulla vel. Odio dicta accusantium iste dolores qui doloremque magni rem. In doloremque ullam reiciendis cupiditate nulla corporis et nemo. Blanditiis harum sed expedita ullam consequatur qui. Est iste aut ut.
-
-Impedit commodi quod excepturi commodi sit ut fugit exercitationem quo. Quia provident rem voluptatem at iusto possimus et earum. Odit vel corrupti omnis quos impedit. Cupiditate illum in debitis.
-
-## Continuous deployment
-
-Libero corporis voluptatum cum nihil. Ea expedita aut. Quae occaecati qui maiores cupiditate qui veritatis. Eos eum unde itaque blanditiis sit eligendi. Perferendis nihil occaecati qui voluptas. Quia in similique.
-
-Rerum unde molestias amet. Dolore minus deleniti ut velit est. Accusamus porro tenetur molestiae quia excepturi quas aut officiis sit. Quisquam aut numquam velit aliquam eos dicta sint. Enim dolorem sunt architecto ipsam aut consequatur. Sequi atque placeat ipsa et aliquam odio sunt ut facere.
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-Exercitationem corporis rerum earum dolorem est culpa reprehenderit laborum rem. Nostrum quasi animi corrupti sed sint consequatur temporibus sed. Corporis autem repellat ut a qui quia. Exercitationem maiores voluptatem doloremque aut enim rerum et qui.
-
diff --git a/docs/src/docs/compatibility.md b/docs/src/docs/modelkit/compatibility.md
similarity index 100%
rename from docs/src/docs/compatibility.md
rename to docs/src/docs/modelkit/compatibility.md
diff --git a/docs/src/docs/use-cases.md b/docs/src/docs/use-cases.md
index 2e1d00a9..432c5229 100644
--- a/docs/src/docs/use-cases.md
+++ b/docs/src/docs/use-cases.md
@@ -1,16 +1,7 @@
# Use Cases
-## Table of Contents
-
-* [Use Case Context](#use-case-context)
-* Collaborating on an AI-Enabled Application for Production
- * [AI/ML Team Collaboration](#aiml-team-collaboration)
- * [AI/ML and App Team Collaboration](#aiml-and-app-team-collaboration)
- * [AI/ML, App, and SRE Team Collaboration](#aiml-app-and-sre-team-collaboration)
-* Collaborating on an Internal Model
- * [AI/ML and SRE Team Collaboration](#aiml-and-sre-team-collaboration)
-
## Use Case Context
+
Weyland-Yutani Corporation has been adding AI and ML models to its portfolio for both internal- and customer-facing deployment. There are three main groups that are involved in the development lifecycle for their AI/ML work:
* AI/ML Team, composed of data scientists, data engineers, and MLOps engineers. This specialized group builds, tunes, and validates the models that increasingly touch every aspect of the organization's work.
* Application Teams, composed of software and hardware engineers. This group builds the applications that the business and customers interact with - over time more and more of these applications are being integrated into the models the AI/ML team works on.
@@ -20,7 +11,9 @@ There has been a heated argument within Weyland-Yutani about how best to manage
...but all that's about to change! (Hint: the change involves KitOps...surprise!)
-## AI/ML Team Collaboration
+## Collaborating on an AI-Enabled Application for Production
+
+### AI/ML Team Collaboration
Rajat is working on tuning an open source foundational model for his company. After several days of work in his Jupyter notebook, he has a model that is outperforming the old model they've been using in production. But before he alerts the App and SRE teams Rajat wants to have another data scientist try the model and verify his findings.
@@ -43,9 +36,9 @@ Gorkem loads Rajat's notebook file and runs through Rajat's tests. He Slacks him
Thanks KitOps!
-## AI/ML and App Team Collaboration
+### AI/ML and App Team Collaboration
-Now that [Rajat and Gorkem have both agreed](#aiml-team-collaboration) that the newly trained model is a real challenger for production, they alert the Application Team who will need to do an integration test between their app and the model.
+Now that [Rajat and Gorkem have both agreed](#ai-ml-team-collaboration) that the newly trained model is a real challenger for production, they alert the Application Team who will need to do an integration test between their app and the model.
Rajat Slacks the application team a heads-up, and Nida volunteers to kick off integration testing. She needs the model and hopes that Rajat included a validation dataset. Nida uses the Kit CLI's flexible pull command to only extract the new model's Kitfile and check whether there's a validation dataset included:
@@ -65,9 +58,9 @@ Nida is a bit of an introvert so the fact that she didn't need to ask anyone for
Thanks KitOps!
-## AI/ML, App, and SRE Team Collaboration
+### AI/ML, App, and SRE Team Collaboration
-When the second [integration pipeline that Nida kicked off](#aiml-and-app-team-collaboration) completed successfully it automatically notified Annika in the SRE team. Annika quickly looks over the integration test results and sees that the model and application are ready for deployment. She issues a PR to Weyland-Yutani's GitOps repository to kick off the production deployment pipeline in GitLab.
+When the second [integration pipeline that Nida kicked off](#ai-ml-and-app-team-collaboration) completed successfully it automatically notified Annika in the SRE team. Annika quickly looks over the integration test results and sees that the model and application are ready for deployment. She issues a PR to Weyland-Yutani's GitOps repository to kick off the production deployment pipeline in GitLab.
Part of the GitOps automation calls the Kit CLI to extract only the model (saving a heap of time by not having to pull a +10GB dataset that isn't needed):
@@ -88,7 +81,9 @@ Once the deployment is complete across all galactic regions, Annika sends an upd
Thanks KitOps!
-## AI/ML and SRE Team Collaboration
+## Collaborating on an Internal Model
+
+### AI/ML and SRE Team Collaboration
Angel leads an internal data science team that builds models to help Weyland-Yutani's executives make faster and better decisions with the help of AI/ML models. Their team was asked in the most recent monthly business review to identify all the customers they have who might be a churn risk based on the set of common traits and behaviours seen in all churned customers over the last five years.