Lesson Overview

APIs, or Application Programming Interfaces, are how different software systems communicate and share information or actions. Whenever you ask a website for weather data, submit a form, or load a YouTube video, you’re likely using an API behind the scenes. APIs act as a menu of available actions and data that outside tools—like your AI agent—can use.

HTTP requests are the way those actions get triggered. If the API is like a vending machine with labeled buttons, an HTTP request is like choosing and pressing one: you ask for something, and the machine responds. Most agents rely on two main request types: GET (to pull information like news or weather) and POST (to send in new information, such as submitting forms or inputting prompts).

This lesson explains these foundational terms before you jump into building agents yourself. Understanding APIs and HTTP requests helps you configure your agent’s building blocks, troubleshoot issues, and reach for new use cases—especially when the tool you need isn’t pre-integrated. Even non-coders benefit by knowing these basics, as most agent platforms keep the technical side out of view, letting you focus on what you want your agent to do.

Who This Is For

If you’re new to building AI agents or interested in connecting tools and services, this lesson will help you understand the key concepts needed to move forward.

• Creators who want to automate tasks
• Product managers and operations leads learning agent workflows
• Educators exploring agent-powered projects
• Analysts and business users connecting data sources
• Anyone curious about the basics of APIs and how agents interact with them

Where This Fits in a Workflow

Learning about APIs and HTTP requests comes right before building functional AI agents. Picture a scenario where your agent delivers daily weather forecasts to your inbox or pulls information from an external app. This lesson gives you the logic behind “how” your agent can reach out, get the data, or send information somewhere else. For example, if you want to connect an AI prompt to update a Google Sheet or request up-to-date news for a report, you’ll use APIs and HTTP requests. These concepts are foundation stones for most automations, setting you up for the practical steps of linking and controlling outside apps through your agent.

Technical & Workflow Benefits

Previously, connecting different services meant manual copy-pasting, custom code, or heavy IT involvement. With APIs and HTTP requests, your agent can fetch, send, and process data in seconds—no manual effort needed. Platforms like n8n simplify this by providing built-in integrations for tools like Google, Slack, and Reddit. If a direct integration isn’t available, custom HTTP requests allow you to connect almost any public service. This flexibility means you spend less time on setup and more on using information, automating updates, and triggering actions whenever you need. The clarity of APIs (what’s possible) paired with the structure of HTTP requests (how it’s done) fuels faster, easier, and more consistent workflows.

Practice Exercise

1. Try out your new knowledge by imagining you want your agent to send you daily weather updates by email.
   Find an API that offers weather data, like OpenWeatherMap, and look for the function “Get Weather.”
2. Think through what data you’d want to request (your city, date, etc.) and how you would send an HTTP GET request for it.
3. Imagine the API’s response (weather info in data form) and how your agent formats that into a readable email.

Reflection: How would this setup differ if you wanted to send (POST) custom information to an app instead of just pulling (GET) data? What would change in your request and response?

Course Context Recap

You’re now wrapping up the core concepts needed to build your own AI agent. This lesson introduced APIs and HTTP requests—the primary way agents connect with outside information and tools. Previously, you learned what agents are and how they operate. Up next, you’ll combine these pieces and actually build out your first functional agent step-by-step. Keep going to see how these ideas look in action and deepen your confidence working with agent technologies. If you want to master agent building, continue through the full course for practical skills and project-ready examples.