How to Use Make.com AI Agents for Automation

Make.com introduces AI agents as a new way to build autonomous workflows that reason, act, and collaborate across your existing scenarios, tools, and data sources. This how-to guide walks you through the core concepts, setup steps, and best practices so you can start using AI agents effectively in your automation projects.

What Are Make.com AI Agents?

AI agents in Make.com are autonomous problem solvers that combine large language models, tools, and memory to complete tasks for you. Instead of designing every step manually, you describe the goal in natural language and the agent figures out how to reach it.

In practical terms, an AI agent can:

Understand instructions in plain language
Access tools and apps you connect in your Make.com workspace
Reason step by step to choose the best actions
Collaborate with other agents or scenarios
Learn from past runs through memory and context

These capabilities make AI agents ideal for complex workflows that would otherwise require multiple scenarios and detailed logic.

How Make.com AI Agents Work

Make.com AI agents sit on top of the platform’s existing automation engine. They extend traditional scenarios by adding reasoning and decision-making powered by large language models.

At a high level, an agent works in four stages:

Instruction: You give the agent a task or objective using natural language.
Planning: The agent breaks the goal into steps and identifies which tools or scenarios to use.
Execution: The agent calls tools, triggers scenarios, and interacts with data.
Reflection: The agent checks results, adjusts its approach, and can store relevant information as memory.

Because agents work with the same modules, data stores, and apps you already use in Make.com, they are a natural next step if you maintain existing scenarios and want more autonomy.

Prerequisites to Start With Make.com Agents

Before you configure an AI agent, ensure you have the following in place inside Make.com:

An active Make.com account and access to the latest features
Familiarity with scenarios, modules, and connections
Access rights to any apps, APIs, or data sources you want the agent to use
Clear use cases where autonomous decision-making will add value

Having a few well-structured scenarios ready will help you understand how agents can orchestrate existing workflows.

Step-by-Step: Creating an AI Agent in Make.com

Use the steps below as a general blueprint for creating an AI agent inside Make.com. Interface labels and options may evolve, but the overall flow is consistent.

Step 1: Define the Agent’s Purpose in Make.com

Start by describing what the agent should do and what success looks like.

Identify one focused process, such as lead qualification, customer support triage, or content drafting.
Write a short mission statement in plain language. For example, “Handle incoming support emails, categorize them, and trigger the right scenario for each category.”
List the data sources, tools, and scenarios the agent will need to access in Make.com.

This definition will later become part of the system instructions for the agent.

Step 2: Configure the Agent in Make.com

Once you know the purpose, configure the agent’s basic settings.

Create or open the relevant workspace in Make.com.
Navigate to the AI or agents section where new agents are managed.
Click to create a new agent and provide:

Name: A clear, functional name (for example, “Support Router Agent”).
Description: A short explanation of what the agent does and which scenarios it coordinates.
System instructions: Concise guidance on tone, constraints, and responsibilities.

Keep the description and instructions tightly aligned with your mission statement to avoid inconsistent behavior.

Step 3: Connect Tools and Scenarios

The strength of an AI agent in Make.com comes from the tools and scenarios you connect to it.

Identify existing scenarios that perform atomic tasks, such as sending emails, updating a CRM, or generating a document.
Expose those scenarios to the agent as callable tools where supported.
Ensure each scenario has clear input and output data structures so the agent can reason about them.
Link any external apps (email, CRM, ticketing, databases) using the standard Make.com connections.

Think of this step as building the toolbox that the agent will use to achieve its goals.

Step 4: Configure Memory and Context

Effective agents in Make.com benefit from memory, allowing them to improve across runs or maintain context inside a long task.

Decide which data points matter over time, such as user preferences, past interactions, or important IDs.
Configure the agent to read and write from a data store, table, or other persistent storage supported in Make.com.
Limit stored data to what is necessary for quality and compliance.
Design prompts and instructions so the agent retrieves and updates memory intentionally, not excessively.

With the right memory strategy, the agent can personalize actions and avoid repeating the same clarifying questions.

Step 5: Test the Agent in Make.com

Testing is essential before you trust an AI agent with live data or customers.

Run the agent in a safe environment with test data.
Observe how it chooses tools and which scenarios it invokes.
Check logs and outputs carefully to ensure that the agent follows your instructions.
Adjust system prompts, tool descriptions, and scenario inputs based on what you learn.
Repeat until the agent behaves consistently across a variety of test cases.

Make incremental changes and document what you adjust so you can track improvements over time.

Step 6: Deploy and Monitor

After successful testing, you can deploy the agent in Make.com to work with real data.

Connect the agent to the production versions of your scenarios and apps.
Set up monitoring and alerts to track key metrics such as success rates, failure types, and response times.
Review agent activity regularly to identify new optimization opportunities.
Update instructions and tools as your processes evolve.

Monitoring is not optional. AI agents are powerful, and oversight ensures that power is used responsibly.

Best Practices for Make.com AI Agents

To get reliable, high-quality outcomes from agents in Make.com, follow these best practices:

Start small: Limit the first agent to one clear use case instead of many unrelated tasks.
Write precise prompts: System instructions should be explicit, including constraints, style, and forbidden actions.
Modularize scenarios: Keep scenarios small and well-defined so the agent can combine them flexibly.
Document tools: Provide short, accurate descriptions for every tool or scenario the agent can call.
Protect sensitive data: Restrict what the agent can access and log, following your security policies.

These practices help you maintain control while benefiting from autonomy and flexibility.

When to Use Make.com Agents vs. Traditional Scenarios

Not every process needs an AI agent. In Make.com, you can often use a straightforward scenario and achieve excellent results.

AI agents are useful when:

The path to the goal is not fixed and can change based on context.
You need natural language understanding or generation as a core step.
Many tools or scenarios must be coordinated dynamically.
New edge cases appear frequently and are hard to anticipate with rigid logic.

Traditional scenarios are often better when:

The process is stable and rule-based.
Inputs and outputs are predictable and structured.
Compliance or audit requirements favor deterministic flows.

Evaluate each use case and choose the lightest approach that still meets your needs.

Further Resources on Make.com AI Agents

To deepen your understanding of AI agents in Make.com, review the official documentation and examples provided by the platform. The article that inspired this guide is available at this Make.com AI agents resource, which explains how agents build on the core automation engine.

If you need consulting or implementation support for Make.com AI agents, you can explore expert automation services at Consultevo, a site focused on advanced workflow and integration projects.

By combining the power of AI agents with your existing automations in Make.com, you can move from static workflows to adaptive systems that reason, act, and evolve with your business needs.

Need Help With Make.com?

If you want expert help building, automating, or scaling your Make scenarios, work with ConsultEvo — certified workflow and automation specialists.

Get Help