diff --git a/website/docs/docs/build/build-metrics-intro.md b/website/docs/docs/build/build-metrics-intro.md
index ed10a874a3c..232b3f83ee0 100644
--- a/website/docs/docs/build/build-metrics-intro.md
+++ b/website/docs/docs/build/build-metrics-intro.md
@@ -21,7 +21,7 @@ Before you start, consider the following guidelines:
 
 - Define metrics in YAML and query them using these [new metric specifications](https://github.com/dbt-labs/dbt-core/discussions/7456).
 - You must be on dbt v1.6 or higher to use MetricFlow. [Upgrade your dbt Cloud version](/docs/dbt-versions/upgrade-core-in-cloud) to get started.
-- Use MetricFlow with Snowflake, Postgres, BigQuery, Databricks, or Redshift.
+- Use MetricFlow with Snowflake, BigQuery, Databricks, Postgres (CLI only), or Redshift. (dbt Cloud Postgres support coming soon)
 - Unlock insights and query your metrics using the [dbt Semantic Layer](/docs/use-dbt-semantic-layer/dbt-sl) and its diverse range of [available integrations](/docs/use-dbt-semantic-layer/avail-sl-integrations).
 
 
diff --git a/website/docs/docs/build/metrics-overview.md b/website/docs/docs/build/metrics-overview.md
index eaa0b306674..4a926589de2 100644
--- a/website/docs/docs/build/metrics-overview.md
+++ b/website/docs/docs/build/metrics-overview.md
@@ -13,9 +13,9 @@ The keys for metrics definitions are:
 | Component | Description | Type |
 | --------- | ----------- | ---- |
 | `name` | Provide the reference name for the metric. This name must be unique amongst all metrics.   | Required |
-| `type` | Define the type of metric, which can be a measure (`simple`) or ratio (`ratio`)).  | Optional |
+| `type` | Define the type of metric, which can be a measure (`simple`) or ratio (`ratio`)).  | Required |
 | `type_params` | Additional parameters used to configure metrics. `type_params` are different for each metric type. | Required |
-| `filter` | For any type of metric, you may optionally include a filter string, which applies a filter for a dimension, entity or time dimension when computing the metric. You can think of this as your WHERE clause.   | Optional |
+| `filter` | For any type of metric, you may optionally include a filter string, which applies a filter for a dimension, entity, or time dimension when computing the metric. You can think of this as your WHERE clause.   | Optional |
 |  `meta` | Additional metadata you want to add to your metric. |
 
 
@@ -38,7 +38,7 @@ metrics:
 This page explains the different supported metric types you can add to your dbt project. 
 <!--
 - [Cumulative](#cumulative-metrics) — Cumulative metrics aggregate a measure over a given window.
-- [Derived](#derived-metrics) — An expression of other metrics, which allows you to do calculation on top of metrics.
+- [Derived](#derived-metrics) — An expression of other metrics, which allows you to do calculations on top of metrics.
 - [Expression](#expression-metrics) — Allow measures to be modified using a SQL expression.
 - [Measure proxy](#measure-proxy-metrics) — Metrics that refer directly to one measure.
 - [Ratio](#ratio-metrics) — Create a ratio out of two measures. 
@@ -148,7 +148,8 @@ metrics:
 ```
 
 ## Filters
-Filter are configured using jinja templating. Use the following syntax to refrence entites, dimensions and time dimensions in filters:
+
+A filter is configured using Jinja templating. Use the following syntax to reference entities, dimensions, and time dimensions in filters:
 ```yaml
 filter: |
   {{ Entity('entity_name') }} 
@@ -163,7 +164,7 @@ You can set more metadata for your metrics, which can be used by other tools lat
 
 - **Description** &mdash;  Write a detailed description of the metric.
 
-<!--Provide a detailed description of the metric. This description is surfaced in the main “definition” section of the metric page using rich Markdown formatting in the Transform UI. [this includes transform and not sure how this looks in core and cloud]-->
+<!--Provide a detailed description of the metric. This description surfaced in the main “definition” section of the metric page using rich Markdown formatting in the Transform UI. [this includes transform and not sure how this looks in core and cloud]-->
 
 
 ## Related docs
diff --git a/website/docs/docs/build/sl-getting-started.md b/website/docs/docs/build/sl-getting-started.md
index 7259a7eb22c..bfe8eb00f4d 100644
--- a/website/docs/docs/build/sl-getting-started.md
+++ b/website/docs/docs/build/sl-getting-started.md
@@ -29,7 +29,7 @@ To fully experience the power of a universal dbt Semantic Layer, take the follow
 
 - 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, or Redshift data platform
+- Use MetricFlow with Snowflake, BigQuery, Databricks, Postgres (CLI only), or Redshift. (dbt Cloud Postgres support coming soon)
 - A successful run in the environment where your Semantic Layer is configured
 - To query with dbt Cloud:
   * Have a dbt Cloud Team or Enterprise [multi-tenant](/docs/cloud/about-cloud/regions-ip-addresses) deployment, hosted in North America (Other regions coming soon)
diff --git a/website/docs/docs/use-dbt-semantic-layer/quickstart-sl.md b/website/docs/docs/use-dbt-semantic-layer/quickstart-sl.md
index 8dbcc6c46f3..f70433cd10a 100644
--- a/website/docs/docs/use-dbt-semantic-layer/quickstart-sl.md
+++ b/website/docs/docs/use-dbt-semantic-layer/quickstart-sl.md
@@ -23,7 +23,7 @@ import TestQuery from '/snippets/_sl-test-and-query-metrics.md';
 
 The dbt Semantic Layer, powered by [MetricFlow](/docs/build/about-metricflow), simplifies defining and using critical business metrics. It centralizes metric definitions, eliminates duplicate coding, and ensures consistent self-service access to metrics in downstream tools. 
 
-MetricFlow is a powerful component within the dbt Semantic Layer that helps users define and manage company metrics efficiently. It provides flexible abstractions and SQL query generation, and also allows data consumers to retrieve metric datasets quickly and easily from a data platform.
+MetricFlow is a powerful component within the dbt Semantic Layer that helps users define and manage company metrics efficiently. It provides flexible abstractions and SQL query generation and also allows data consumers to retrieve metric datasets quickly and easily from a data platform.
 
 Use this guide to fully experience the power of a universal dbt Semantic Layer. Here are the following steps you'll take:
 
diff --git a/website/snippets/_v2-sl-prerequisites.md b/website/snippets/_v2-sl-prerequisites.md
index 95d563c9359..8e7075db257 100644
--- a/website/snippets/_v2-sl-prerequisites.md
+++ b/website/snippets/_v2-sl-prerequisites.md
@@ -3,11 +3,11 @@
 
 To use the Semantic Layer, you must:
 
-- Have a dbt Cloud Team or Enterprise [multi-tenant](/docs/cloud/about-cloud/regions-ip-addresses) deployment, hosted in North America
-- Have both your production and development environments running dbt version 1.6 or higher 
-- Use Snowflake, BigQuery, Databricks, and Redshift data platform
+- Have a dbt Cloud Team or Enterprise [multi-tenant](/docs/cloud/about-cloud/regions-ip-addresses) deployment, hosted in North America.
+- Have both your production and development environments running dbt version 1.6 or higher.
+- Use Snowflake, BigQuery, Databricks, or Redshift (dbt Cloud Postgres support coming soon).
 -  Create a successful run in the environment where you configure the Semantic Layer. <br/>
-  **Note:** Semantic Layer currently supports Deployment environment. (_development experience coming soon_)
+  **Note:** Semantic Layer currently supports the Deployment environment. (_development experience coming soon_)
 - Install the [MetricFlow CLI](/docs/build/metricflow-cli). After installing the package, make sure you run at least one model.
 - Set up the [Semantic Layer API](/docs/dbt-cloud-apis/sl-api-overview) in the integrated tool to import metric definitions. <br /> 
 **Note:** Developer accounts can only query data manually using the [MetricFlow CLI](/docs/build/metricflow-cli) and SQL. To dynamically query metrics using external tools, you must have a dbt Cloud Team or Enterprise account with access to the Semantic Layer API.<br />