Summary  
This chapter explains how to create and configure AI agents natively within an automation platform by designing clear, role-based prompts and integrating them into workflows using built-in modules instead of manual HTTP requests.

General domain of usage  
Social media content generation

AI agents are used in Make to transform input data into meaningful output. Common use cases include processing, cleaning, summarizing, classifying, and generating content.

### What Changed in Make

Make now includes a native **AI Agents** feature (currently in beta).

**Before**

* HTTP requests;
* API keys;
* External model endpoints;

**Now**

* AI agents are created directly inside **Make**;
* Easier setup;
* Cleaner scenarios;
* Tighter integration with existing modules;

This agent will be connected to the RSS workflow built earlier.

### Prompting Basics (Quick Reminder)

AI does not infer intent well. It follows instructions.

**Good prompting means**

- Clear role definition;
- Explicit input description;
- Specific output requirements;
- Clear constraints;


Assume the model knows nothing beyond what you tell it.

Note

What is the most important factor for getting reliable output from an AI agent in Make?

Learn how to build powerful, real-world automation systems using Make.com and AI. Start with the fundamentals of scenario building and flow control, then master data handling, functions, APIs, and webhooks. Move into advanced workflows that combine RSS feeds, AI agents, and multimedia processing to create intelligent content pipelines. Finish by assembling a complete automation system, managing AI outputs, and exploring expansion ideas for scaling your workflows.

Learn the core foundations of Make.com automation, including platform basics, scenario building, AI-assisted workflow creation, integrations, and multi-path data routing logic.

Learn how Make stores and processes data, master built-in functions, work with arrays, and apply logic helpers to transform and control information inside your workflows.

Explore how APIs and webhooks work in Make, including sending requests, receiving data, and building real-time automation scenarios.

Learn how to combine RSS feeds with AI agents in Make to collect, process, and transform content into fully automated, intelligent workflows.

Explore how to design multimedia automation workflows, assemble a complete AI-driven content system, manage generated outputs, and plan future expansion paths.

Using AI Agents in Make

What Changed in Make

Prompting Basics (Quick Reminder)