Agentic AI with OpenAI AgentBuilder

Projects:

1. FAQ Assistant Agent

2. Product Support CoPilot

3. Ticket Resolution AI Assistant

4. Investment Research AI Agent

5. Spend KPI Mini Dashboard Agent

6. Regulatory Change Impact Analyzer

Why this course?

AI agents are rapidly moving from experimentation to real-world adoption across enterprises. From compliance analysis and research assistants to internal copilots and decision-support systems, agentic AI systems are becoming the next layer of intelligent software.

However, building such systems has traditionally required:

• deep programming expertise,
• complex development environments,
• and significant engineering effort.

OpenAI AgentBuilder changes this.

AgentBuilder allows you to design, reason about, and prototype AI agents visually, using a browser-based interface—making agentic AI accessible to a much broader audience.

This course is designed to help you master AgentBuilder as a practical, real-world skill, without getting lost in SDKs, infrastructure, or heavy coding.

What you will learn

In this course, you will learn how to:

• Understand what agentic AI systems are and how they differ from traditional chatbots
• Design AI agents using OpenAI AgentBuilder’s visual workflow interface
• Break complex problems into agentic workflows
• Work with state, memory, and multi-step reasoning
• Use File Search to ground agents in internal documents
• Use Web Search to bring in external, real-time information
• Introduce tools and functions conceptually and understand how they fit into enterprise systems
• Simulate advanced behaviors where programmatic orchestration is required
• Build complete, end-to-end agent workflows for real business use cases

A project-driven approach (not toy examples)

This course follows a project-first learning approach.

You won’t just click through features—you’ll build agents that mirror real-world scenarios, including:

• Small focused agents to understand core concepts
• Intermediate projects that combine multiple tools and reasoning steps
• A full capstone project that replicates an enterprise-grade use case:
  Regulatory Change Impact Analyzer

In the capstone project, you will design an agent that:

• interprets regulatory changes,
• retrieves internal policy documents,
• researches external regulatory requirements,
• performs gap analysis,
• and generates executive-ready insights.

This mirrors how AI agents are actually designed inside enterprises.

No heavy coding required

This course is intentionally designed to be:

• browser-based
• low-code / no-code
• accessible on Windows or any modern OS

You do not need:

• Python or JavaScript expertise
• complex local development setups
• backend infrastructure

Where advanced programmatic orchestration would normally be required, we simulate those steps so you can focus on agent design and reasoning, not implementation complexity.

How this course fits into the larger OpenAI ecosystem

OpenAI provides multiple ways to build agents:

• AgentBuilder (visual design)
• Agents SDK (programmatic orchestration)
• ChatKit (delivery and UI integration)
• Eval (testing and evaluation)

This course focuses exclusively on AgentBuilder.

You will gain:

• a clear understanding of the full ecosystem,
• and deep, hands-on expertise in AgentBuilder specifically.

The agents you design here are intended to be:

• reviewed,
• refined,
• and handed off to developers for production implementation using the Agents SDK (covered in subsequent courses).

Who this course is for

This course is ideal for:

• Consultants and solution architects
• Business analysts and product managers
• AI enthusiasts and early-career professionals
• No-code / low-code technologists
• Developers who want to design before engineering
• Anyone curious about how real AI agents are designed in practice

You do not need prior experience with AI agents or OpenAI tools.

Who this course is NOT for

This course does not focus on:

• writing agent code using SDKs
• deploying agents to production
• backend integration or DevOps
• advanced evaluation frameworks

Those topics are covered in follow-up courses designed for developers and engineers.

Why this course is different

Most AI courses either:

• stay too theoretical, or
• jump straight into code without explaining why things work.

This course focuses on:

• thinking like an agent designer
• understanding reasoning flows
• building systems that make sense to both humans and machines

By the end of this course, you will not just know how to use AgentBuilder—you will understand when and why to use it, and how it fits into real enterprise workflows.

Ready to design your first AI agent?

If you want to learn agentic AI through real projects, without heavy coding or complex setups, this course is for you.

Let’s start building intelligent AI agents—visually.