Create Your Own AI Agent for Free with No Code

Introduction: The Future of Content Creation is Here

In today’s fast-paced digital world, content is king—but creating it consistently can be time-consuming and exhausting. What if you could automate the entire process? Imagine having an AI-powered content generator that runs every hour, creates posts tailored to your niche, style, and audience—and even lets you monitor everything through a sleek dashboard?

Thanks to no-code platforms like Make , this is now possible. In this comprehensive guide, we’ll walk you through how to create your very own AI content agent from scratch—without any coding skills required. You’ll learn how to set up an automated system that generates LinkedIn posts, articles, or social media updates on demand, all while giving you full control via a custom user interface.

By the end of this article, you’ll have:

• A fully functional AI agent
• A database to store generated content
• A live dashboard to manage and share posts
• And all of this done for free using Make and other open-source tools

Let’s dive in!

Why Build an AI Agent for Content Generation?

Before we get into the technical steps, let’s understand why building an AI agent for content generation makes sense :

1. Consistency : Your AI agent can run every hour, ensuring fresh content is always ready.
2. Personalization : By feeding it your profile, niche, and templates, the agent learns your voice and style.
3. Scalability : Easily expand the agent to generate content across multiple platforms like Twitter, Instagram, blogs, and more.
4. Cost-Efficiency : Use free tools and APIs to automate what would otherwise require human effort or paid services.
5. Data Tracking : Store and analyze all generated content in a database, allowing you to refine strategies over time.

Now, let’s break down the step-by-step process of building your own AI content agent using Make , one of the most powerful no-code automation platforms available today.

Step 1: Sign Up for Make and Access the AI Agent Feature

To begin, head over to Make.com and sign up for an account. Thanks to a special offer, you can access the Pro plan for one month for free —this will give you access to advanced features like AI agents, unlimited scenarios, and integrations.

Once logged in:

1. Navigate to the AI Agents section under the “New” menu.
2. Click “Create an Agent” to start building.

This is where the magic begins.

Step 2: Connect an AI Model to Your Agent

An AI agent is essentially a language model (like Gemini, GPT, or Claude) combined with a set of tools. Let’s connect your preferred AI model first.

1. Click “Add Connection” under the AI model section.
2. Choose your provider: OpenAI, Anthropic, Mistral, Cohere, or Google’s Gemini.
3. Enter your API key (you can get one from the provider’s website).
4. Select the specific model version (e.g., Gemini Flash).
5. Name your connection (e.g., “Gemini 2”) and save.

You’ve now connected your AI brain to the agent!

Step 3: Define Your Agent’s Role and Goal

Next, give your agent a clear purpose. For example, if you're targeting LinkedIn, name your agent something like:

LinkedIn Creative Post Generator

Then, define its goal in the system prompt :

“Your task is to generate engaging LinkedIn posts based on user-defined templates, YouTube insights, and personal brand guidelines.”

We’ll refine this later, but this gives the agent a starting point.

Step 4: Create Tools for Your AI Agent

Tools are what allow your agent to interact with the outside world. In Make, these are called scenarios , and they act as functions your agent can call when needed.

Here are the five essential tools we’ll build:

🔧 Tool #1: Read Template Pack (Google Docs)

This tool allows the agent to pull in pre-written content templates.

1. Go to Scenarios > Create New Scenario .
2. Search for Google Docs and select “Get content of a document” .
3. Connect your Google account and choose a template file.
4. Add a Return Output module to make the content accessible to the agent.
5. Save and activate the scenario.

📝 Scenario Name: Read Template Pack

🔧 Tool #2: Get User Profile (Google Docs)

This helps the agent understand your personal brand, tone, and target audience.

1. Repeat the above steps, but select a document containing your personal profile , including:
   • Niche
   • Target audience
   • Branding rules
   • Tone of voice
   • Core values/philosophy

📝 Scenario Name: Get User Profile

🔧 Tool #3: YouTube Search

This tool allows the agent to search YouTube for trending topics in your niche.

1. Create a new scenario.
2. Search for YouTube and select “Search videos” .
3. Set parameters like query input and max results.
4. Return output so the agent can read the results.

📝 Scenario Name: YouTube Search

🔧 Tool #4: YouTube Transcript Reader

After finding relevant videos, the agent needs to extract their transcripts.

1. Create a new scenario.
2. Use YouTube > Get transcript .
3. Input a video ID and return the full transcript.

📝 Scenario Name: YouTube Transcript Reader

🔧 Tool #5: Save Generated Posts (MongoDB)

Finally, store all generated content in a database for tracking and publishing.

1. Create a new scenario.
2. Use MongoDB integration (or Google Sheets, Airtable, etc.).
3. Set up a collection and define fields like:
   • Post text
   • Timestamp
   • Status (Published/Draft)
   • Platform

📝 Scenario Name: Save Generated Post

✅ Once all five tools are created and activated, go back to your agent and add them under the Tools section. Be sure to write clear descriptions so the agent knows when to use each one.

Step 5: Refine the System Prompt

This is arguably the most important part of your agent’s setup. The system prompt defines the exact workflow the agent should follow.

Here’s a sample 10-step system prompt for a LinkedIn post generator:

“Follow these steps to generate a high-quality LinkedIn post:

 

1. Read and understand the user profile and niche.
2. Generate relevant YouTube search queries based on current trends.
3. Use the YouTube search tool to find top-performing videos.
4. Select the best video based on engagement metrics.
5. Extract the video transcript using the transcript reader.
6. Analyze the transcript to extract a compelling idea.
7. Retrieve the template pack and select the most suitable format.
8. Combine the idea and template to craft a unique post.
9. Ensure the post aligns with the user’s voice and branding.
10. Save the final post to the MongoDB database for review.”

Click “Save” once you’re happy with your instructions.

Step 6: Run and Schedule Your AI Agent

Now it’s time to test your agent:

1. Go to Scenarios > Create New Scenario .
2. Search for “Make AI Agents” and select “Run an Agent” .
3. Choose your newly created agent (e.g., “LinkedIn Creative Post Generator”).
4. Click “Run” and watch the agent execute each step.

You’ll see logs showing how it used each tool, extracted data, and generated a post.

Once confirmed working, schedule the agent to run hourly or daily using Make’s scheduler feature.

Step 7: Build a Custom Dashboard to Monitor Your Agent

To view and manage the content your agent generates, you need a user interface (UI) .

Since we saved our posts in MongoDB , we can build a simple web app to display them.

🛠️ Option 1: Use Bolt to Generate UI Code

Bolt is an AI tool that can generate a full Next.js application from a prompt.

Use this prompt:

“Generate a Next.js dashboard that connects to a MongoDB database at ‘mongodb+srv://username:password@cluster.mongodb.net /mydb’ and displays all documents in the ‘posts’ collection. Each document has the following structure:

 

json

 

 

 

1

2

3

4

5

 

⌄

{

"post": "string",

"timestamp": "date",

"status": "draft/published"

}

 

 

 

 

Include buttons to view, copy, delete, and publish posts.”

Once generated, download the code and run it locally using:

You’ll have a clean, responsive dashboard like this:

🛠️ Option 2: Export and Customize in VS Code

Export the project and open it in Visual Studio Code . You can then customize the UI further, add filters, sorting, export options, and even integrate with LinkedIn’s API to auto-publish posts.

Step 8: Optimize for SEO and Deployment

Now that your AI agent is generating content and storing it in a database, here’s how to optimize everything for maximum impact:

✅ SEO Optimization Tips:

• Use keywords like “AI content generator,” “no-code AI agent,” “automated LinkedIn posts” throughout the article.
• Write meta titles and descriptions that include your main keyword.
• Use headers (H1, H2, H3) to structure your content clearly.
• Internal link to related blog posts or tools (e.g., Make, Bolt, MongoDB).
• Add image alt text with keyword-rich descriptions.

📈 Performance Optimization:

• Compress images before uploading.
• Use a CDN for faster loading.
• Cache static pages where possible.
• Minify CSS/JS files.

🚀 Deployment Options:

• Host your dashboard on Vercel or Netlify for free.
• Deploy the backend to Render or Railway .
• Use GitHub Pages for static documentation or landing pages.

Conclusion: Your AI-Powered Content Machine Is Ready

Congratulations! You’ve just built a fully autonomous AI content generator using no-code tools. This system will help you scale your content production, maintain consistency, and focus more on strategy than execution.

Whether you’re a solopreneur, marketer, or agency owner, this AI agent can become a powerful asset in your toolkit.

So, what are you waiting for? Start building your own AI assistant today and unlock the future of content creation.

Keywords & SEO Suggestions

🔑 Main Keyword:

• AI content generator

🎯 Secondary Keywords:

• No-code AI agent
• Automated LinkedIn post generator
• Free AI content tool
• Make AI agent tutorial
• Content automation without coding

🧭 LSI Keywords:

• AI writing assistant
• Auto-post generator
• AI marketing tool
• Content creation automation
• Smart content generator

Final Thoughts

This article provides a complete roadmap to building an AI-driven content engine without writing a single line of code. With the right tools and a bit of creativity, you can automate nearly any repetitive task in your workflow.

Stay tuned for more tutorials on AI automation, no-code development, and smart marketing strategies!