diff --git a/website/docs/docs/build/sl-getting-started.md b/website/docs/docs/build/sl-getting-started.md
index f070bc27538..c638470d0ff 100644
--- a/website/docs/docs/build/sl-getting-started.md
+++ b/website/docs/docs/build/sl-getting-started.md
@@ -34,7 +34,7 @@ However, to experience the power of the universal [dbt Semantic Layer](/docs/use
 
 - Have an understanding of key concepts in [MetricFlow](/docs/build/about-metricflow), which powers the revamped dbt Semantic Layer.
 - Have both your production and development environments running dbt version 1.6 or higher. Refer to [upgrade in dbt Cloud](/docs/dbt-versions/upgrade-core-in-cloud) for more info.
-- Use Snowflake, BigQuery, Databricks, Redshift, or  Postgres (CLI only. dbt Cloud support coming soon). 
+- Use Snowflake, BigQuery, Databricks, Redshift, or Postgres (Postgres available in the CLI only, dbt Cloud support coming soon). 
 -  Create a successful run in the environment where you configure the Semantic Layer. 
    - **Note:** Semantic Layer currently supports the Deployment environment for querying. (_development querying experience coming soon_)
 - Set up the [Semantic Layer API](/docs/dbt-cloud-apis/sl-api-overview) in the integrated tool to import metric definitions.