Master OpenAI Agent Builder for Your Business

Transform your workflow with visual, no-code AI agents. Build powerful automations tailored to your role and industry.

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Video Overview

Intro to Agent Builder

By Christina Huang, OpenAI

5 minutes 29 seconds

Key Takeaways

Visual No-Code Builder

Drag and drop nodes to create complex AI workflows without writing any code. Perfect for non-technical users.

Built-in Evaluation

Test and understand how your agents perform with integrated eval tools before deploying to production.

Fast Deployment

Export as code or deploy directly to your product with ChatKit. From design to production in minutes.

What You'll Learn

Master the complete Agent Builder workflow from start to deployment

Drag-and-Drop Workflows

Build sophisticated AI agent workflows using visual nodes. Connect agents, tools, and logic flows without code.

Classifier Agents

Route user requests intelligently by classifying intent. Learn to build agents that understand context and make decisions.

Conditional Routing

Create dynamic pathways using if-else logic. Build agents that adapt to different scenarios and user needs.

Web Search Integration

Give your agents access to real-time information with web search tools. Build agents that stay current and informed.

Custom Widgets

Design rich, interactive outputs using Widget Studio. Transform plain text responses into beautiful, structured displays.

Deployment Options

Publish your agents with ChatKit or export as code with the Agents SDK. Choose the deployment method that fits your needs.

Follow Along: Step-by-Step Tutorial

Click any timestamp to jump to that section of the video

Video Chapters

0:00 Introduction to Agent Builder
0:44 Starting in OpenAI Platform
0:47 Start Node and Variables
0:57 Creating Classifier Agent
1:41 Adding If-Else Conditional Node
2:01 Building Flight Agent with Web Search
2:32 Building Itinerary Agent
2:55 Testing with Itinerary Query
3:20 Widget Studio for Custom Outputs
3:42 Adding Flight Widget
4:21 Testing with Flight Query
4:56 Publishing the Agent
5:08 Deployment Options (SDK vs ChatKit)

Tools & Features

Everything you need to build production-ready AI agents

OpenAI Platform

Your central hub for building and managing AI applications. Access Agent Builder, API keys, and usage analytics.

Visit Platform

Agent Builder

Visual, no-code tool for creating agentic workflows. Drag, drop, and connect nodes to build complex agent systems.

Try Agent Builder

Widget Studio

Design custom, rich UI components for agent outputs. Transform plain text into interactive, structured displays.

Explore Widgets

ChatKit

Deploy your agents as chat interfaces instantly. One-click deployment for customer-facing conversational AI.

Learn About ChatKit

Agents SDK

Export your workflows as Python code. Full control for developers who want to customize and extend agents.

SDK Documentation

Web Search Tool

Built-in web search capability for agents. Give your agents access to real-time, up-to-date information from the internet.

View Tools

Classifier Agent

Intelligent routing based on user intent. Automatically classify messages and route to specialized sub-agents.

Best Practices

Conditional Nodes

If-else logic for dynamic workflows. Create branching paths that adapt to different scenarios and conditions.

Guide

Why This Matters for Your Business

Agent Builder delivers measurable business impact

Save Time

80% Faster Development

Build AI workflows in hours instead of weeks. No-code interface eliminates the development bottleneck.

  • No programming required
  • Visual drag-and-drop interface
  • Instant testing and iteration
  • Pre-built templates to start

Reduce Costs

60% Lower Implementation Costs

Eliminate expensive custom development. Build and maintain agents with your existing team.

  • No specialized developers needed
  • Reduce external consulting fees
  • Lower maintenance overhead
  • Pay only for what you use

Scale Faster

10x Productivity Multiplier

Handle growing demand without adding headcount. Agents work 24/7 and scale infinitely.

  • Automate repetitive tasks
  • 24/7 availability
  • Consistent quality at scale
  • Easy to clone and replicate

Try It Out: Hands-On Exercises

Practice building agents with these guided exercises

Exercise 1

Build a Simple Classifier

Beginner

Objective

Create a classifier agent that routes user messages to either "Sales" or "Support" based on intent.

Steps

  1. Create Start Node

    Accept a user message as input variable

  2. Add Classifier Agent

    Configure with instruction: "Classify if the user wants to buy (sales) or needs help (support)"

  3. Set JSON Output

    Define output format with property "department" having options ["sales", "support"]

  4. Add If-Else Node

    Check if output.department === "sales"

  5. Connect Agent Nodes

    True branch → Sales Agent, False branch → Support Agent

  6. Test It

    Try messages like "I want to purchase a license" and "My account isn't working"

Example Configuration

{
  "classifier_instruction": "You classify user messages into departments.",
  "output_format": {
    "type": "json",
    "properties": {
      "department": {
        "type": "string",
        "enum": ["sales", "support"]
      }
    }
  }
}

Tips

  • Be specific in your classifier instructions
  • Test with edge cases (ambiguous messages)
  • Use clear, descriptive enum values
Exercise 2

Add Web Search to an Agent

Intermediate

Objective

Build an agent that searches the web for current information and provides updated answers.

Steps

  1. Create Agent Node

    Add a new agent with name "Research Assistant"

  2. Write Instructions

    "You are a research assistant. Always use web search to find the most current information before answering."

  3. Enable Web Search Tool

    In the agent's tools section, toggle on "Web Search"

  4. Configure Search Behavior

    Set preferences for how the agent should use search results

  5. Test with Time-Sensitive Query

    Ask: "What are today's top tech headlines?" or "Current stock price of AAPL"

  6. Review Search Usage

    Check the execution log to see when and how the agent used web search

Example Agent Config

{
  "name": "Research Assistant",
  "instruction": "You are a research assistant. Use web search to find current information.",
  "tools": [
    {
      "type": "web_search",
      "config": {
        "max_results": 5,
        "prefer_recent": true
      }
    }
  ]
}

Tips

  • Instruct the agent to prioritize recent information
  • Test queries that require up-to-date data
  • Review search quality in the logs
Exercise 3

Create a Custom Widget

Advanced

Objective

Design a custom widget in Widget Studio to display structured data beautifully.

Steps

  1. Open Widget Studio

    Navigate to Widget Studio from the Agent Builder interface

  2. Choose Template or Start Blank

    Select a template close to your needs or create from scratch

  3. Define Data Schema

    Specify the JSON structure your agent will output

  4. Design Layout

    Arrange fields, add icons, choose colors and typography

  5. Add Conditional Styling

    Create rules like "if status === 'urgent', show red border"

  6. Preview with Test Data

    Use sample JSON to see how your widget renders

  7. Download and Import

    Download the widget file and import it into your agent's output format

  8. Instruct Agent to Use Schema

    Add to agent instructions: "Output your response in the following JSON format: [schema]"

Example Widget Schema

{
  "title": "string",
  "description": "string",
  "status": {
    "type": "string",
    "enum": ["pending", "active", "completed"]
  },
  "priority": {
    "type": "string",
    "enum": ["low", "medium", "high"]
  },
  "assignee": "string",
  "dueDate": "string"
}

Tips

  • Keep the schema simple and clear
  • Use enums for fields with limited options
  • Test with various data scenarios
  • Make sure agent instructions match the schema exactly

Knowledge Check

Test your understanding of Agent Builder concepts

Question 1 of 5

What is the primary purpose of a classifier agent in Agent Builder?

Which tool allows you to give agents access to real-time information from the internet?

What is the purpose of an if-else conditional node?

What does Widget Studio allow you to create?

What are the two main deployment options mentioned in the video?

Flashcard Master Quiz

Test your knowledge with 16 interactive flashcards across 4 key topics

Section 1: The Basics

1

What is Agent Builder?

Click to reveal answer

1

A visual, no-code tool for building AI workflows by connecting nodes to create agents without writing code.

2

What does "no-code" mean in Agent Builder?

Click to reveal answer

2

You can build fully functional AI agents using a visual drag-and-drop interface without writing any programming code.

3

What is the visual interface used for?

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3

To connect nodes and create agent workflows by dragging, dropping, and linking different components together visually.

4

What is built-in eval?

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4

Built-in evaluation tools that let you test and measure how well your agents perform before deploying them.

Section 2: Building Blocks

5

What is a start node?

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5

The entry point of every workflow where you define input variables and state variables that the agent will use.

6

What is a classifier agent?

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6

An agent that analyzes user input to determine intent and categorize it, enabling intelligent routing to specialized sub-agents.

7

How does conditional routing work?

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7

Uses if-else nodes to check conditions and branch the workflow to different paths based on the results (e.g., if type === "A", go left; else go right).

8

Why enable web search for an agent?

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8

To give the agent access to real-time, up-to-date information from the internet, ensuring responses are current and accurate.

Section 3: Advanced Features

9

What is Widget Studio?

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9

A tool for designing custom visual outputs (widgets) that transform plain text agent responses into rich, structured, interactive displays.

10

Why use custom outputs?

Click to reveal answer

10

To provide a better user experience with formatted, visual data instead of plain text (e.g., flight cards, product listings, dashboards).

11

What is JSON format output?

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11

A structured data format where the agent returns information as key-value pairs, making it easy to parse and use in widgets or other systems.

12

How do you test an agent workflow?

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12

Use the "Run Preview" feature to input test queries and watch the message flow through your workflow nodes in real-time.

Section 4: Deployment

13

What does "publishing" mean?

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13

Making your agent workflow live and available for use, either through a direct deployment or by exporting the code.

14

What is ChatKit?

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14

A deployment option that lets you instantly publish your agent as a chat interface that can be embedded directly into your product.

15

What is SDK export?

Click to reveal answer

15

Exporting your workflow as Python code using the Agents SDK, giving developers full control to customize and integrate it.

16

When to use ChatKit vs SDK?

Click to reveal answer

16

Use ChatKit for quick, no-code deployment with a ready-made UI. Use SDK when you need full control and custom integration into existing code.

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Frequently Asked Questions

Common questions about OpenAI Agent Builder

Do I need coding experience to use Agent Builder?

No! Agent Builder is designed as a no-code visual tool. You can build sophisticated AI workflows by dragging and dropping nodes. The interface is intuitive enough for business users, marketers, and other non-technical roles. However, if you are a developer, you can export your workflows as code for advanced customization.

How much does Agent Builder cost?

Agent Builder is available to OpenAI Platform users. You pay for the API usage based on the models and features you use in your workflows (e.g., GPT-4, web search). There's no separate fee for using Agent Builder itself. Check the OpenAI pricing page for current API rates.

Can I integrate my own APIs and data sources?

Yes! Agent Builder supports custom tools and integrations. You can connect external APIs, databases, and services using the Model Context Protocol (MCP). This allows your agents to interact with your existing business systems and proprietary data.

What's the difference between Agent Builder and ChatGPT?

ChatGPT is a conversational AI interface for end users. Agent Builder is a development tool that lets you create custom AI workflows with specialized logic, routing, and integrations. Think of Agent Builder as a way to build your own custom ChatGPT-like experiences tailored to specific business processes.

How do I deploy my agent to production?

You have two main options: (1) Use ChatKit for instant deployment as a chat interface that can be embedded in your product, or (2) Export your workflow as code using the Agents SDK for full control and custom integration. Both options are production-ready and scalable.

Can I test my agent before deploying?

Absolutely! Agent Builder includes built-in testing tools. You can use "Run Preview" to test your workflows with sample inputs and watch the execution flow in real-time. The platform also includes evaluation (eval) tools to measure agent performance and quality before going live.

What are widgets and why should I use them?

Widgets are custom UI components that transform plain text responses into rich, interactive displays. Instead of getting a wall of text, users see beautifully formatted cards, tables, or dashboards. Widget Studio lets you design these without code, creating professional-looking outputs that match your brand.

How does web search work in Agent Builder?

The web search tool gives your agents access to real-time information from the internet. When enabled, the agent can automatically search the web when it needs current data (like stock prices, news, or product availability). You control when and how the agent uses this capability through your workflow design.

Can I use multiple agents in one workflow?

Yes! This is a core pattern in Agent Builder. You typically create a classifier agent that routes to multiple specialized agents (e.g., a sales agent, support agent, and billing agent). Each specialized agent can be optimized for its specific task, creating a more efficient and accurate system.

What happens if my agent makes a mistake?

Agent Builder includes logging and monitoring tools so you can review agent behavior and identify issues. You can iterate on your instructions, add validation nodes, and use conditional logic to handle edge cases. The built-in eval tools help you catch problems before deployment. You can also version your agents to easily roll back if needed.

Additional Tips & Best Practices

Expert insights from OpenAI documentation and community

Start with Clear Instructions

Write specific, detailed instructions for each agent. Instead of "help users," write "You are a customer support agent for [product]. Help users troubleshoot login issues by checking X, Y, Z."

Source: OpenAI Practical Guide to Building Agents

Keep Agents Specialized

Rather than one mega-agent that does everything, create specialized agents for specific tasks. A classifier routes to the right specialist. This improves accuracy and makes debugging easier.

Source: OpenAI Developer Community Best Practice

Test Early and Often

Don't wait until your workflow is complete to test. Use Run Preview after adding each node to ensure it behaves as expected. This catches issues early when they're easier to fix.

Source: OpenAI Building Agents Track

Use JSON for Structured Data

When you need structured output (for widgets or conditional logic), specify JSON format with clear property names. This ensures consistent, parseable responses.

Source: Agent Builder Documentation

Add Guardrails

Use conditional nodes to validate inputs and outputs. Add checks like "if user message contains profanity, route to moderation" or "if confidence < 0.7, ask for clarification."

Source: OpenAI Safety Best Practices

Design Widgets for User Experience

Plain text works, but custom widgets dramatically improve user experience. Invest time in Widget Studio to make outputs visually appealing and easy to scan.

Source: Widget Studio Best Practices

Version Your Workflows

Before making major changes, save a version of your workflow. This makes it easy to roll back if something breaks and helps you track improvements over time.

Source: Development Best Practice

Enable Web Search Thoughtfully

Web search is powerful but adds latency and cost. Use it only when you need real-time data. For static information, include it in your agent's instructions instead.

Source: Performance Optimization Guide

Monitor Agent Performance

After deployment, regularly review logs and usage analytics. Look for common failure patterns, slow responses, and user satisfaction. Iterate based on real-world data.

Source: Production Monitoring Best Practice

Start Simple, Iterate

Build a minimal viable agent first (MVP). Get it working end-to-end, deploy it to a small group, gather feedback, then add complexity. This approach reduces risk and accelerates learning.

Source: Agile Development Principle

Additional Resources

Official Agent Builder Guide Practical Guide to Building Agents (PDF) Building Agents Learning Track Agents SDK Documentation Launch Agent Builder

Visual Walkthrough

See Agent Builder in action

Agent Builder Interface

Agent Builder Visual Interface

The main canvas where you drag and drop nodes to create your workflow. Connect agents, tools, and logic nodes visually.

Travel Agent Example

Travel Agent Example from Tutorial

The demo agent built in the video: routes between itinerary planning and flight search based on user intent.

Key Visual Elements to Notice

Nodes

Each node represents a step: start, agent, condition, or tool. Connect them to build your workflow.

Connections

Lines between nodes show the flow of data and logic. Follow the path to understand execution order.

Node Settings

Click any node to configure its behavior, instructions, tools, and output format in the right panel.

Run Preview

The test interface on the right lets you input queries and watch your workflow execute in real-time.