diff --git a/website/blog/2023-10-31-to-defer-or-to-clone.md b/website/blog/2023-10-31-to-defer-or-to-clone.md
index a39fc3ac0b7..00aa8c7f7e5 100755
--- a/website/blog/2023-10-31-to-defer-or-to-clone.md
+++ b/website/blog/2023-10-31-to-defer-or-to-clone.md
@@ -87,7 +87,7 @@ Using the cheat sheet above, let’s explore a few common scenarios and explore
     1. Make a copy of our production dataset available in our downstream BI tool
     2. To safely iterate on this copy without breaking production datasets
     
-    Therefore, we should use **clone** in this scenario
+    Therefore, we should use **clone** in this scenario.
     
 2. **[Slim CI](https://discourse.getdbt.com/t/how-we-sped-up-our-ci-runs-by-10x-using-slim-ci/2603)**
 
@@ -96,7 +96,11 @@ Using the cheat sheet above, let’s explore a few common scenarios and explore
     2. Only run and test models in the CI staging environment that have changed from the production environment
     3. Reference models from different environments – prod for unchanged models, and staging for modified models
     
-    Therefore, we should use **defer** in this scenario
+    Therefore, we should use **defer** in this scenario.
+
+:::tip Use `dbt clone` in CI jobs to test incremental models
+Learn how to [use `dbt clone` in CI jobs](/best-practices/clone-incremental-models) to efficiently test modified incremental models, simulating post-merge behavior while avoiding full-refresh costs.
+:::
     
 3. **[Blue/Green Deployments](https://discourse.getdbt.com/t/performing-a-blue-green-deploy-of-your-dbt-project-on-snowflake/1349)**