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Author: mintlify[bot]

guides/ai-agents.mdx

@@ -10,7 +10,7 @@ title: "AI agents"
   />{" "}
 </CardGroup>
 
-Lightdash AI agents transform the way you interact with your data by allowing you to ask questions in natural language and get answers back. Whether you're exploring data in Lightdash or collaborating with your team in Slack, AI agents make data analysis as simple as having a conversation.
+AI agents transform the way you interact with your data by allowing you to ask questions in natural language and get answers back. Whether you're exploring data in Lightdash or collaborating with your team in Slack, AI agents make data analysis as simple as having a conversation.
 
 <Frame>
   <img src="/images/guides/ai-agent-chat-intro.png" alt="" />
@@ -83,13 +83,30 @@ You can also summon the bot on a thread to continue the conversation. In order f
   <img src="/images/guides/ai-agent-slack-thread-consent.png" alt="" />
 </Frame>
 
+#### Demo
+
+Watch this comprehensive demo to see AI agents in action:
+
+<Frame>
+  <iframe
+    width="100%"
+    height="420"
+    src="https://www.loom.com/embed/f38e27fee7784e7f95538613b3b77bb5?sid=a13feb5b-fef3-4f68-9fbf-e54f928c28e5"
+    frameborder="0"
+    webkitallowfullscreen
+    mozallowfullscreen
+    allowfullscreen
+  />
+</Frame>
+
+
 ## Best practices
 
 To get the most accurate and useful answers from your AI agents, follow these best practices for preparing your data and configuring your agents.
 
 ### Think specialized, not general
 
-Think of AI agents as your specialized analysts - each one can be configured to focus on specific areas of your business. For example, you might create a "Marketing Assistant" that only has access to marketing data like campaign performance, lead generation, and customer acquisition metrics. This focused approach ensures more accurate, relevant responses and prevents sensitive data from being accessible to the wrong teams. To find out more about how to configure specific access, see [Curating fields with tags](#curating-fields-with-tags).
+Think of AI agents as your specialized analysts - each one can be configured to focus on specific areas of your business. For example, you might create a "Marketing Assistant" that only has access to marketing data like campaign performance, lead generation, and customer acquisition metrics. This focused approach ensures more accurate, relevant responses and prevents sensitive data from being accessible to the wrong teams. To find out more about how to configure specific access, see [Limiting access to specific explores/fields](#limiting-access-to-specific-explores/fields).
 
 ### Document your data thoroughly
 
@@ -169,18 +186,12 @@ For more granular control, tag specific metrics and dimensions:
             tags: ['ai', 'finance'] #    <--------- tagging the metric
 ```
 
-## Learn more
+## FAQs
 
-Watch this comprehensive demo to see AI agents in action:
+1. Does Lightdash store the query data?
 
-<Frame>
-  <iframe
-    width="100%"
-    height="420"
-    src="https://www.loom.com/embed/f38e27fee7784e7f95538613b3b77bb5?sid=a13feb5b-fef3-4f68-9fbf-e54f928c28e5"
-    frameborder="0"
-    webkitallowfullscreen
-    mozallowfullscreen
-    allowfullscreen
-  />
-</Frame>
+  Lightdash only stores one-line-answers, for example: "How many orders we've had so far?". So you can look back at your threads' history, we have to keep this record stored. All other queries that result a query do **not** get stored. We only store the fields (and filters if applicable) to generate the query to your warehouse.
+
+2. Why can't I set multiple Agents for the same Slack channel?
+
+  Since you have to mention the Slack App for your organization, and to avoid unexpected results, we don't allow multiple agents for the same slack channel. To align with best practices, we recommend one slack channel per project, so you prompt with confidence.