sim/apps/docs/content/docs/en/getting-started/index.mdx

---
title: Getting Started
---

import { Callout } from 'fumadocs-ui/components/callout'
import { Card, Cards } from 'fumadocs-ui/components/card'
import { File, Files, Folder } from 'fumadocs-ui/components/files'
import { Step, Steps } from 'fumadocs-ui/components/steps'
import { Tab, Tabs } from 'fumadocs-ui/components/tabs'
import {
  AgentIcon,
  ApiIcon,
  ChartBarIcon,
  CodeIcon,
  ConditionalIcon,
  ConnectIcon,
  ExaAIIcon,
  FirecrawlIcon,
  GmailIcon,
  NotionIcon,
  PerplexityIcon,
  SlackIcon,
} from '@/components/icons'
import { Video } from '@/components/ui/video'
import { Image } from '@/components/ui/image'

Build your first AI workflow in 10 minutes. In this tutorial, you'll create a people research agent that uses advanced LLM-powered search tools to extract and structure information about individuals.

<Callout type="info">
  This tutorial covers the essential concepts of building workflows in Sim. Estimated completion time: 10 minutes.
</Callout>

## What You'll Build

A people research agent that:
1. Accepts user input through a chat interface
2. Searches the web using AI-powered tools (Exa and Linkup)
3. Extracts and structures information about individuals
4. Returns formatted JSON data with location, profession, and education

<Image
  src="/static/getting-started/started-1.png"
  alt="Getting Started Example"
  width={800}
  height={500}
/>

## Step-by-Step Tutorial

<Steps>
  <Step title="Create a workflow and add an AI agent">
    Click **New Workflow** in the dashboard and name it "Getting Started".
    
    Every new workflow includes a **Start block** by default—this is the entry point that receives user input. Since we'll trigger this workflow via chat, no configuration is needed for the Start block.
    
    Drag an **Agent Block** onto the canvas from the left panel and configure it:
    - **Model**: Select "OpenAI GPT-4o"
    - **System Prompt**: "You are a people research agent. When given a person's name, use your available search tools to find comprehensive information about them including their location, profession, educational background, and other relevant details."
    - **User Prompt**: Drag the connection from the Start block's output into this field to connect `<start.input>` to the user prompt
    
    <div className="mx-auto w-full overflow-hidden rounded-lg">
      <Video src="getting-started/started-2.mp4" width={700} height={450} />
    </div>
  </Step>
  
  <Step title="Add search tools to the agent">
    Enhance your agent with web search capabilities. Click on the Agent block to select it.
    
    In the **Tools** section:
    - Click **Add Tool**
    - Select **Exa** and **Linkup** from the available tools
    - Provide your API keys for both tools to enable web search and data access
    
    <div className="mx-auto w-3/5 overflow-hidden rounded-lg">
      <Video src="getting-started/started-3.mp4" width={700} height={450} />
    </div>
  </Step>
  
  <Step title="Test your workflow">
    Test your workflow using the **Chat panel** on the right side of the screen.
    
    In the chat panel:
    - Click the dropdown and select `agent1.content` to view the agent's output
    - Enter a test message: "John is a software engineer from San Francisco who studied Computer Science at Stanford University."
    - Click **Send** to execute the workflow
    
    The agent will analyze the person and return structured information.
    
    <div className="mx-auto w-full overflow-hidden rounded-lg">
      <Video src="getting-started/started-4.mp4" width={700} height={450} />
    </div>
  </Step>
  
  <Step title="Configure structured output">
    Configure your agent to return structured JSON data. Click on the Agent block to select it.
    
    In the **Response Format** section:
    - Click the **magic wand icon** (✨) next to the schema field
    - Enter the prompt: "create a schema named person, that contains location, profession, and education"
    - The AI will automatically generate the JSON schema
    
    <div className="mx-auto w-full overflow-hidden rounded-lg">
      <Video src="getting-started/started-5.mp4" width={700} height={450} />
    </div>
  </Step>
  
  <Step title="Test with structured output">
    Return to the **Chat panel** to test the structured response format.
    
    With the response format configured, new output options are now available:
    - Click the dropdown and select the structured output option (the schema you just created)
    - Enter a test message: "Sarah is a marketing manager from New York who has an MBA from Harvard Business School."
    - Click **Send** to execute the workflow
    
    The agent will now return structured JSON output with the person's information organized into location, profession, and education fields.
    
    <div className="mx-auto w-full overflow-hidden rounded-lg">
      <Video src="getting-started/started-6.mp4" width={700} height={450} />
    </div>
  </Step>
</Steps>

## What You've Built

You've successfully created an AI workflow that:
- ✅ Accepts user input through a chat interface
- ✅ Processes unstructured text using AI
- ✅ Integrates external search tools (Exa and Linkup)
- ✅ Returns structured JSON data with AI-generated schemas
- ✅ Demonstrates real-time testing and iteration
- ✅ Showcases the power of visual, no-code development

## Key Concepts You Learned

### Block Types Used

<Files>
  <File
    name="Start Block"
    icon={<ConnectIcon className="h-4 w-4" />}
    annotation="Entry point for user input (auto-included)"
  />
  <File
    name="Agent Block"
    icon={<AgentIcon className="h-4 w-4" />}
    annotation="AI model for text processing and analysis"
  />
</Files>

### Core Workflow Concepts

**Data Flow**  
Connect blocks by dragging connections to pass data between workflow steps

**Chat Interface**  
Test workflows in real-time with the chat panel and select different output options

**Tool Integration**  
Extend agent capabilities by integrating external services like Exa and Linkup

**Variable References**  
Access block outputs using the `<blockName.output>` syntax

**Structured Output**  
Define JSON schemas to ensure consistent, formatted responses from AI

**AI-Generated Schemas**  
Use the magic wand (✨) to generate schemas from natural language prompts

**Iterative Development**  
Build, test, and refine workflows quickly with immediate feedback

## Next Steps

<Cards>
  <Card title="Explore Workflow Blocks" href="/blocks">
    Discover API, Function, Condition, and other workflow blocks
  </Card>
  <Card title="Browse Integrations" href="/tools">
    Connect 80+ services including Gmail, Slack, Notion, and more
  </Card>
  <Card title="Add Custom Logic" href="/blocks/function">
    Write custom functions for advanced data processing
  </Card>
  <Card title="Deploy Your Workflow" href="/execution">
    Make your workflow accessible via REST API or webhooks
  </Card>
</Cards>

## Resources

**Need detailed explanations?** Visit the [Blocks documentation](/blocks) for comprehensive guides on each component.

**Looking for integrations?** Explore the [Tools documentation](/tools) to see all 80+ available integrations.

**Ready to go live?** Learn about [Execution and Deployment](/execution) to make your workflows production-ready.