how to build and use AI Agent

Welcome! I am so excited to help you dive into the world of AI agents. Building your own agents is incredibly empowering because it lets you transition from just talking to AI to having AI actually go out and do real work for you.

Before we map out our route and start building, I would love to learn a little bit more about you so I can make this session as valuable as possible. To help me tailor this session, could you tell me a little about your experience level with AI or programming, and if you have a specific goal or project in mind for building an agent?

I am a complete beginner and just want to understand how they work.

It is great to have you here! Starting from absolute scratch is actually the best way to learn, because it lets you see past all the tech hype and understand the simple logic that makes these systems work.

Your path

Choosing Your Tools (No-Code vs. Code)

Building Your First Agent

Best Practices & Safety

What Exactly is an AI Agent?

To understand AI agents, let's contrast them with the standard we use every day. When you text a chatbot like ChatGPT or Claude, the interaction is passive and conversational. You ask a question, the AI generates text based on what it already knows, and then it stops and waits for your next input. It is entirely up to you to guide the next step. An , on the other hand, is active and goal-oriented. Instead of just writing a response, you give it a broad goal (e.g., "Find the best 3-day flight and hotel package for Tokyo next month"). The agent then takes that goal, figures out what steps are needed, uses external tools to look up real-time flight data and hotel reviews, and keeps working autonomously until the task is complete.

Give me a real-world example of an agent in action

Let's look at a concrete, real-world example to see exactly how this works! Imagine you are self-employed and want to stay on top of your business finances. Instead of manually tracking everything, you decide to build an to handle it for you. Instead of you manually copying and pasting numbers, the agent handles the entire lifecycle of the task autonomously.

Step	What the Agent Does	Behind the Scenes
1. Trigger	You email a receipt photo to `expenses@mycompany.com`.	The agent detects a new email has arrived and extracts the attachment.
2. Reason	It analyzes the receipt and notices a charge for "$45.00 at Joe's Diner".	The agent's brain (the LLM) classifies this as a "Client Meals" business expense.
3. Act	It opens your financial spreadsheet and appends a new row.	The agent uses a custom spreadsheet tool to write the date, category, and amount automatically.
4. Verify	It double-checks your monthly budget to see if you are on track.	It reads the spreadsheet to calculate your total monthly meal spend.
5. Report	It emails you back: "Receipt logged! You have spent $120 of your $200 meal budget."	It drafts a natural language update and sends the email response.

The key takeaway here is that you did not write a rigid, step-by-step program that says "open this specific file, look for column B, and paste this number." You simply gave the agent a general rule ("Categorize and log any emailed receipts"), and its internal brain figured out the exact sequence of steps to make it happen.

how to make AI agent by using Chat GPT

You can actually build highly functional agents directly inside ChatGPT! OpenAI lets you create custom versions of ChatGPT—simply called —using a friendly, chat-based builder without writing a single line of code.

The Four Core Building Blocks

Before we build one together in ChatGPT, we need to look at what makes an agent actually tick. Every agent—whether built with zero code inside ChatGPT or hand-coded in Python—relies on four essential ingredients:

The Brain (LLM): This is the core engine, like GPT-4o. It processes your input, understands what you want, and figures out how to handle it.
The Skills (Tools): These are the capabilities you give your agent so it can interact with the outside world. This could be a tool to browse the web, write to a Google Sheet, send an email, or run code.
The Context (Memory): This is how the agent keeps track of what has happened so far. Without memory, it would forget your goal immediately after taking its first action.
The Reasoning (Planning): This is the agent's ability to take your broad goal and break it down into logical steps before jumping straight to a solution.

These four elements work in a continuous loop: the Brain creates a Plan, uses a Tool to execute a step, stores the result in Memory, and then decides what to do next. Let's see how we can set these up using ChatGPT's built-in creator tool.

Continue to building a custom GPT step-by-step

Let's roll up our sleeves and build one! Doing this step-by-step is the absolute best way to see how the four core building blocks we just talked about translate into a working digital assistant.

Step 1: Open the 'Create a GPT' Interface

To get started, make sure you are logged into ChatGPT on your computer. Look at the left-hand sidebar and click on . From there, you will see a button in the top right corner that says + Create. Clicking that opens up the split-screen GPT Builder workspace: the left side is where you talk to the AI builder to set things up, and the right side is a preview playground where you can test your agent in real-time as you build it.

Step 2: Meet the GPT Builder vs. the Configure Tab

The Builder is split into two tabs on the left panel:

Create: This is a conversational builder. You tell it what you want in plain English (e.g., "I want to build a travel agent"), and it will automatically generate instructions and set up the agent for you.
Configure: This is where you can manually adjust the settings yourself. This tab gives you direct control over the , uploaded knowledge files, and specific tools (like web browsing or code execution).

While talking to the 'Create' tab is easy, using the Configure tab is actually much better for understanding how agents work because it forces you to consciously define the agent's Brain, Skills, Context, and Reasoning. Let's switch over to that Configure tab now.