# Getting started as an Admin

Studio is where data teams build and configure AI Analysts. This guide walks you through setting up your first AI Analyst from scratch.

### Setup flow

{% @mermaid/diagram content="flowchart TD
A\[Sign in] --> B\[Connect your data]
B --> C\[Build your semantic layer]
C --> D\[Create an AI Analyst]
D --> E\[Test your AI Analyst]
E --> F\[Invite users and deploy]" %}

## Step 1: Sign in

Go to [wobby.ai](https://www.wobby.ai/) and sign in with your account. If you don't have one yet, click *Get started for free* to create an organisation.

## Step 2: Connect your data

AI Analysts need access to your data before they can answer questions.

1. In Studio, open **Connections** in the left sidebar
2. Click **Add connection** and select your data source (PostgreSQL, Snowflake, BigQuery, etc.)
3. Enter your connection credentials and save

See [Connect a data source](/connections/connect-a-data-source.md) for detailed instructions per database type.

## Step 3: Build your semantic layer

The semantic layer is what keeps your AI Analyst accurate — it maps your raw tables and columns to business concepts your team actually uses.

1. Go to **Semantic Layer** in the sidebar
2. Create your first **Model** by selecting a table from your connected data source
3. Add **Dimensions** (descriptive attributes like `region` or `customer_tier`) and **Measures** (numeric calculations like `total_revenue`)
4. Optionally add **Metrics** for your most important KPIs

See [Models](/semantic-layer/models.md) and [Metrics](/semantic-layer/metrics.md) to go deeper.

## Step 4: Create an AI Analyst

1. Go to **AI Analysts** in the sidebar and click **New AI Analyst**
2. Give it a name and description that reflects its purpose (e.g. "Sales Performance Analyst")
3. Under **Models**, link the models you built in Step 3
4. Under **Instructions**, write a brief description of what the AI Analyst should focus on and how it should behave

See [Instructions](/ai-analysts/creating-an-agent/agent-instructions.md) for guidance on writing effective instructions.

## Step 5: Test your AI Analyst

Open your AI Analyst and switch to Explorer view to test it. Ask a few questions that you'd expect a real user to ask. If results are off, go back to your semantic layer and refine your models, dimensions, or measures.

## Step 6: Invite users and deploy

1. Under **Access Management**, invite users or share the AI Analyst with your team
2. Optionally connect to [Slack](/connections/messaging-apps/slack.md) or [Microsoft Teams](/connections/messaging-apps/teams.md) so users can query data directly from those tools

***

*Next:* explore [Suggestions](/ai-analysts/creating-an-agent/suggestions.md) and [Saved Prompts](/explorer/working-with-agents/saved-prompts.md) to give your users a great first experience.


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# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.wobby.ai/quick-start/getting-started-studio.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.