Make.com has recently introduced a powerful new feature: AI agents. These intelligent helpers are currently in public beta, so if you don’t see them in your account yet, you can apply for access. But if they are already available to you, it’s time to explore what they can do and whether you really need them..

In this article, we'll walk you through what AI agents are, how to set them up, how to integrate them with your workflows, their benefits and limitations.

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🤖 What Are AI Agents?

AI agents are like smart assistants that can think for themselves - up to point. Unlike traditional tools or modules which follow strict rules, AI agents can make decisions based on your instructions and context. 

You can define:

• What tasks they can do
• What tools they can use
• What data to consider when making a decision

Think of them as autonomous task managers capable of making decisions and managing complexity in real time.

These agents live on a global level in your Make.com team, meaning once you set them up, you can use them across different scenarios.

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⚙️ How to Set Up an AI Agent in Make.com

To get started with AI agents, you can follow these simple steps:

1. Choose or Create an Agent

You start by selecting an agent from the AI Agent module. This can be reused across multiple scenarios.

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2. Give It Tools (Sub-Scenarios)

These tools are other Make scenarios the AI agent can call on. For example:

• “Run Research” tool
• “CRM Management” tool
• “Create Google Doc” tool

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Each of these tools can be described clearly so the AI agent knows when to use them.

🔧 Pro tip: Be sure to describe the tool well—what it does, when to use it, and what input it requires.

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3. Set Up Your Main Agent Prompt

This is the "brain" of your agent. Include:

• A detailed description of its role
• Example tasks
• Rules and steps it should follow
• Sample outputs (e.g., Slack block format)
• Fallback instructions for error handling

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4. Link It to a Trigger (e.g., Slack Bot)

In the demo, a Slack message triggers the AI agent. It reads your message and decides what to do based on your prompt and tools

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🧪  Example: AI-Powered Slack Assistant

Let’s say you ask Slack, “What are the most common pain points Make.com users face?”.

The workflow may look like this: 

1. Your Slack message triggers the webhook.
2. The webhook sends your query to the AI agent.
3. The agent checks its tools and calls the “Knowledge Base” scenario.
4. It fetches the relevant info, formats it as a Slack message, and sends it back.

The agent identified:

• Data loss
• Debugging challenges
• Complex error handling
• Confusing data types

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🔄 How AI Agents Work Behind the Scenes 

Make.com lets you structure these interactions through sub-scenarios with specific input/output configurations. You can pass:

• Thread IDs for context
• Email addresses
• Custom text instructions

And even return structured outputs in formats like JSON, numbers, text, dates, etc.

This creates a very dynamic flow, similar to how webhooks pass data and wait for responses—but more advanced.

📝 Turning AI Responses into Blog Posts 

Let’s level it up. You could ask the agent: “Can you enhance that answer using web search and turn it into a 1000-word blog article?”

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Here's what happens next: 

1. The AI agent calls a research tool (e.g., connected to Perplexity).
2. It fetches fresh info from the web.
3. It summarizes and formats the response.
4. You can then instruct it: “Create a Google Doc.”
5. It calls another tool that generates a Google Doc using HTML.
6. The doc is saved to your Google Drive and linked back to Slack.

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‍📂 Error Handling Like a Pro

Sometimes, the AI won’t return results in the expected format (e.g., Slack blocks). When that happens:

• Add an error handler module.
• Set it to catch failed outputs.
• Use a raw text fallback response.

This ensures you always get a reply, even if it's not perfectly formatted.

🔍 Other Use Cases for AI Agents in Make

AI agents can do much more:

✅ Manage Calendars: Aggregate events from multiple calendars into a single view or JSON file.

✅ Prioritize Leads: Check if a new email sender is an existing client or lead. Prioritize hot leads automatically.

✅ Track Project Status: Request updates like: “Show me all completed projects this month.” The AI agent will pull data from your project management tool and summarize it.

✅ Client Updates on Autopilot: Send regular client updates by summarizing completed tasks in a project and generating a short update.

💡 AI Agents vs AI Workflows: When to Use What?

You don’t always need an AI agent. Sometimes, a simple AI-enchanced workflow is faster, more reliable and easier to maintain. 

Here’s a short comparison between the two:

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For teams new to AI automation, workflows provide more predictable results. Agents shine in more fluid environments.

 🎯 Tip: Start with AI workflows. Add agents later if needed.

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🚀 Key Takeways

Make.com's AI agents are powerful, flexible and rapidly evolving. But like any tool, they are only as useful as the problem they’re solving. Now is the perfect time to explore their potential and apply them where they truly make a difference.

As the technology matures, we can expect further enhancements and updates to the AI agent module.

Start small and expand as your workflow grows.

If you are curious to learn more, check out our Make Simplified Community - currently 100% free for a limited time. Get access to premium automation courses, customs apps and a lot more resources.

We’re here to help you master automation - with or without AI agents.

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