[auto] adding content to release-x.57.x->release-x.57.x (#776)

Co-authored-by: Metabase Docs bot <[email protected]>

Author: github-automation-metabase

_docs/v0.57/ai/metabot.md

@@ -53,6 +53,7 @@ Some tips:
 - Whenever you want Metabot to do something completely different, you should reset the conversation, as Metabot might find that irrelevant historical context to be confusing.
 - Once Metabot creates a question for you, you can follow up with more questions or take over yourself. You can drill through the chart or step into the editor to tweak the query (both in the query builder and the SQL editor).
 - Metabot works best with English prompts. While it might understand other languages, you'll get the most reliable results by asking your questions in English.
+- Define domain-specific terms in the [glossary](../exploration-and-organization/data-model-reference#glossary) to help Metabot understand your organization's terminology.
 
 ### Metabot response menu
 

_docs/v0.57/ai/settings.md

@@ -48,6 +48,7 @@ The best thing you can do to improve Metabot's performance is to prep your data
 - [Add models and metrics to your Metabot collection](#add-models-and-metrics-to-your-metabot-collection)
 - [Add descriptions for your data and content](#add-descriptions-for-your-data-and-content)
 - [Make sure the semantic types for each field are correct](#make-sure-the-semantic-types-for-each-field-are-correct)
+- [Define domain-specific terms in the glossary](#define-domain-specific-terms-in-the-glossary)
 - [Curate prompt suggestions](#curate-prompt-suggestions)
 
 ### Add models and metrics to your Metabot collection
@@ -76,6 +77,12 @@ Make sure the semantic types for each field accurately describe the field's "mea
 
 Metabase will try to set semantic types automatically, but you should confirm that each field has the relevant semantic type. See [Data types and semantic types](../data-modeling/semantic-types). You can also set semantic types for [models](../data-modeling/models#add-metadata-to-columns-in-a-model).
 
+### Define domain-specific terms in the glossary
+
+Add your organization's terminology, acronyms, and business-specific terms to the [glossary](../exploration-and-organization/data-model-reference#glossary). When Metabot receives a prompt, it can look up terms in the glossary to better understand your request.
+
+For example, if you define "MRR" as "Monthly Recurring Revenue" in your glossary, Metabot will know what you mean when you ask "What's our MRR for Q4?" This is especially helpful for industry-specific jargon, internal product names, or abbreviations unique to your organization.
+
 ### Curate prompt suggestions
 
 When you select a collection for Metabot to "learn", Metabot will suggest a series of prompts based on the content it finds in that collection. These prompts just give people a feel for the kinds of things people can ask Metabot to do.

_docs/v0.57/data-modeling/models.md

@@ -126,6 +126,12 @@ There are some limitations to this indexing:
 
 You can edit a model's query by clicking on the down arrow next to the model's name and clicking on **Edit query definition**. When you're doing editing, be sure to save your changes. Unlike questions, which prompt you to save as a new question, any changes here will overwrite the existing model. If you want to create a new model from an existing model, select **Duplicate this model** from the model sidebar (the icon of two overlapping squares).
 
+### Checking for breaking changes
+
+> {% include plans-blockquote.html feature="Checking for breaking changes" %}
+
+When you save changes to a model, Metabase will try to detect whether your changes would break any other entities that depend on that model. For example, if you remove a column from the model, but other questions based on that model rely on that column, Metabase will warn you that those downstream questions will break. 
+
 ## Model list view
 
 ![Viewing a model as a list](./images/model-list.png)

_docs/v0.57/exploration-and-organization/data-model-reference.md

@@ -56,9 +56,9 @@ Admins can edit the metadata in this reference by clicking the **Edit** button i
 
 ## Glossary
 
-The glossary is a place where anyone can define terms relevant to your data. Currently, the glossary is a simple key-value store of terms and their definitions.
+The glossary is a place where anyone can define terms relevant to your data. To add a new term, click **+ New term**. Add the term name and its definitions, then click the checkmark to save the term to the glossary.
 
-To add a new term, click **+ New term**. Add the term name and its definitions, then click the checkmark to save the term to the glossary.
+The glossary is particularly useful for [Metabot](../ai/metabot). When Metabot gets a prompt, it can look up glossary terms to understand your request. For example, if you define "MRR" as "Monthly Recurring Revenue" in your glossary, Metabot will know what you mean when you ask "What's our MRR for Q4?"
 
 ## Segments