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docs: document discovering semantic model fields via AI chat #11022

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19 changes: 19 additions & 0 deletions docs-mintlify/docs/explore-analyze/analytics-chat.mdx
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Expand Up @@ -17,6 +17,25 @@ The AI agent interprets your questions, generates queries against your semantic
- **Queued messages** – Send follow-up messages while the agent is still processing
- **Save to Workbook** – Export insights to [Workbooks](/docs/explore-analyze/workbooks) for further analysis

## Discover available fields

You can ask the AI agent what's available in your semantic model before
diving into analysis. This is useful when you're new to a deployment or
exploring an unfamiliar view.

Try prompts like:

- "What fields are available?"
- "What measures and dimensions can I query in the Orders view?"
- "Describe the fields in the Customers view and what each one means."
- "What does the `lifetime_value` measure represent?"

The agent uses the descriptions and [AI context](/docs/data-modeling/ai-context)
defined on your views, measures, and dimensions to answer. Well-documented
semantic models produce better answers — see
[AI context best practices](/docs/data-modeling/ai-context#best-practices)
for guidance on writing descriptions the agent can use.

## Queued messages

You can send follow-up messages while the AI agent is still processing a
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