How to create workflows without writing a single line of code? That’s the power of n8n, a visual automation platform where you simply drag nodes onto a canvas, connect them, and hit run.
The best part? At $60/month, n8n’s Pro plan is significantly more affordable than Zapier’s $253/month Team plan, while offering 10,000 executions and unlimited users. Unlike other automation tools, n8n also gives you the unique advantage of self-hosting, perfect for businesses with specific security requirements.
What makes n8n particularly powerful is its ability to incorporate AI agents as nodes, combining AI-driven steps with traditional programming for efficient, real-world workflows. These AI agents build on Large Language Models (LLMs) that generate text by predicting the next word.
In this step-by-step guide, we’ll walk you through creating your first n8n workflow, from understanding the five main types of nodes (Trigger, Action, Logic, Code, and AI Agent) to building complex automations that save you time and resources. Whether you’re looking to create simple document workflows or sophisticated AI-powered systems, we’ve got you covered.
Understanding n8n and Its Core Concepts
n8n stands as a powerful workflow automation platform that has evolved far beyond its original purpose. Initially developed to help developers avoid repetitive tasks like setting up environments and configuring credentials [1], this tool has rapidly gained popularity due to its visual node-based interface and flexible connectivity options.
What is n8n, and how does it compare to Zapier or Make
n8n differentiates itself from competitors through its unique approach to automation. Unlike Zapier or Make, n8n offers complete data sovereignty through self-hosting capabilities [2], making it especially attractive for security-conscious organizations. Furthermore, n8n features a pricing model based on workflow executions rather than per-operation billing [3], which can be substantially more cost-effective for complex automations.
When comparing these platforms, several key differences emerge:
- Pricing efficiency: For some automations, n8n can be 1000 times more cost-efficient compared to Zapier or Make [1].
- Technical flexibility: n8n provides advanced customization through JavaScript/Python coding capabilities [2].
- Feature accessibility: There is no feature gate on core functionality in n8n—no premium nodes exist, allowing all users to build complex workflows regardless of their pricing plan [1].
One of n8n’s most compelling advantages is its execution-based pricing model. Instead of charging per operation, n8n counts a single run of your entire workflow as one execution, regardless of complexity or data volume [3]. This creates a more predictable cost structure, especially for workflows that would require thousands of operations in other platforms.
Types of nodes: Trigger, Action, Logic, AI Agent
At the core of n8n are nodes—the fundamental building blocks that perform various functions within your workflow. These nodes fall into several key categories:
- Trigger nodes: These initiate workflows in response to specific events or conditions [4]. Examples include webhook triggers that listen for HTTP requests, polling triggers that check for new data, and scheduled triggers that run at specific times [5].
- Action nodes: These perform specific tasks like fetching and sending data, or processing information [4]. They represent the actual work being done in your workflow.
- Logic nodes: These control the flow of your automation with conditional branches, loops, and other programming constructs.
- AI Agent nodes: These integrate with LLMs via LangChain, providing prompt management, context memory, and tool usage capabilities [6]. n8n offers nearly 70 dedicated AI nodes for building complete backends for chatbots, assistants, and RAG workflows [1].
Notably, n8n supports a wide range of AI models, including OpenAI, Anthropic, Mistral, and HuggingFace, or even custom model endpoints, including self-hosted LLMs [1].
Is n8n open source? Overview of n8n plans
n8n is fair-code distributed under the Sustainable Use License and n8n Enterprise License [7]. This source-available approach means you can access the entire codebase on GitHub, self-host the platform, and extend it with your own nodes and functionality.
The platform offers several flexible plans:
- Self-hosted (Community Edition): Free with unlimited workflows and executions, but you manage hosting, backups, and updates yourself [8].
- Starter plan: Starting at $24/month with 2,500 workflow executions and managed hosting on n8n infrastructure [8].
- Pro plan: Starting at $60/month with 10,000 executions, role-based access control, and an insights dashboard [8].
- Enterprise plan: Custom pricing with unlimited executions, advanced developer tools, audit logs, SSO, and dedicated support with SLA [8].
Each plan scales according to execution needs rather than limiting users or features, making n8n an adaptable solution for teams of any size.
Building a Simple Automation Workflow
Let’s dive straight into building your first practical workflow in n8n – a Gmail to Slack notification system that alerts you whenever important emails arrive.
Create a Gmail to Slack notification flow
Building automated connections between email and messaging platforms remains one of the most useful workflow applications. For many teams, email notifications in Slack help centralize communications and ensure important messages aren’t missed. This simple yet powerful workflow demonstrates core n8n capabilities while delivering immediate practical value.
I’ll walk through creating a workflow that monitors your Gmail inbox and sends notifications to Slack when specified emails arrive. This approach helps teams centralize notifications from various apps into Slack, streamline communication, and automate routine tasks across different platforms.
Set up Gmail trigger and Slack action
First, let’s configure the Gmail Trigger node:
- Create a new workflow in n8n by clicking the “+” icon
- Add a Gmail Trigger node as your starting point
- Authenticate with your Google account when prompted
- Set the node to trigger on “Message Received” events
- Configure your poll time – how often n8n checks Gmail for new messages
Remember that Gmail doesn’t actually send n8n information when you receive an email. Instead, n8n uses polling to periodically check for new messages. You can set this anywhere from every minute to once daily, depending on your urgency needs.
Next, add and configure your Slack node:
- Connect the Gmail Trigger to a new Slack node
- Authenticate with your Slack workspace
- Under “Resource,” select “Message”
- For “Operation,” choose “Send”
- Select your target channel or user
- Configure your message text, incorporating email details from the Gmail node
The Slack node offers extensive capabilities beyond simple messaging. You can archive channels, create public or private channels, get channel histories, invite users, and manage messages with various operations.
Add filters to customize behavior
The Filter node appears in approximately 65% of production workflows for good reason – it prevents irrelevant data from flowing through your automation. Adding filters between your Gmail and Slack nodes allows you to:
- Process only emails with specific criteria
- Prevent notification overload
- Create different handling paths for different email types
To add a filter:
- Insert a Filter node between your Gmail and Slack nodes
- Configure conditions based on email properties like:
- Sender email address
- Subject line keywords
- Read/unread status
- Label presence
For example, you might set up a condition to only process emails from specific domains or containing keywords like “LEAD” in the subject. This prevents your Slack channel from being flooded with notifications.
Filtering early in your workflow prevents unnecessary processing, saving execution time and computational resources. For workflows processing thousands of records daily, effective filtering can reduce execution time from 45 minutes to under 5 minutes.
Beyond simple Gmail to Slack notifications, consider expanding this workflow with AI summarization, categorization, or routing to different channels based on content analysis. These advanced features showcase n8n’s extensibility while maintaining the simple drag-and-drop interface that makes workflow creation accessible.
Designing AI-Powered Workflows
Beyond basic automation, n8n’s AI capabilities open up powerful possibilities for creating intelligent workflows. With its no-code interface, even users without AI expertise can build sophisticated AI applications that connect to hundreds of services.
How to create AI workflows in n8n
Creating AI workflows in n8n starts with understanding the core building blocks. At the heart of AI functionality is the AI Agent node, which serves as the brain of your workflow. This node can listen for inputs (typically from a trigger), process information, and generate intelligent responses or actions.
The process of building an AI workflow follows four fundamental steps:
- Create an AI Agent node as your workflow’s intelligence center
- Connect a language model to power your agent’s reasoning
- Add memory to maintain context across interactions
- Incorporate tools to extend your agent’s capabilities
What makes n8n particularly valuable for AI workflows is its ability to mix deterministic automation steps with AI to increase reliability. You can implement error handling, add human approval steps, and create fallback logic in case AI actions don’t go as planned.
Use AI Agent node with OpenAI or Gemini
n8n supports multiple AI providers, with OpenAI and Google Gemini being among the most popular options. Setting up either is straightforward:
For Gemini:
- Add an AI Agent node to your canvas
- Click “Chat Model” and select “Google Gemini Chat Model”
- Authenticate with your Google AI API key
- Select your preferred model (Gemini 1.5 Pro, Gemini 1.5 Flash, etc.)
For OpenAI:
- Similarly, add the AI Agent node
- Select “OpenAI Chat Model” under the Chat Model option
- Authenticate with your OpenAI credentials
- Choose your preferred model (GPT-4, GPT-3.5, etc.)
The integration allows full control over model parameters, system prompts, and output formats, giving you flexibility to create precisely tailored AI experiences.
Add memory and tools for smarter agents
Memory is crucial for creating contextually aware AI workflows. Without it, your agent will treat each interaction as brand new, forgetting previous conversations. n8n offers several memory options:
- Simple Memory: Stores the last few interactions in the instance running n8n
- MongoDB Atlas Vector Store: For more sophisticated, long-term memory storage
- Window Memory Buffer: Maintains context during chat sessions
Moreover, what truly elevates n8n’s AI capabilities is the ability to give agents access to tools. Tools are connected nodes your agent can call during execution to perform actions like fetching weather data, searching databases, or sending messages. This allows your AI to interact with real-world systems and data sources.
With 500+ pre-built integrations, your AI agents can trigger, act, and complete tasks across hundreds of services—creating workflows that not only think but also do.
Scaling with Modular and Reusable Components
As workflows grow more complex, modular design becomes essential. Breaking down large, monolithic workflows into smaller, interconnected sub-workflows makes your automations easier to understand, maintain, and scale. This approach allows you to build once and reuse many times—transforming how you create workflows in n8n.
Use Execute Workflow node for sub-flows
The Execute Workflow node serves as the cornerstone of modular design in n8n. This powerful node enables one workflow to call another, passing data between them and receiving results in return [9]. Instead of creating one massive workflow with dozens of nodes, you can split functionality into dedicated sub-workflows:
- Create a separate workflow for a specific function (like data validation)
- Add an Execute Sub-workflow Trigger node as its starting point
- Configure the input data mode to define what information the sub-workflow requires
- In your main workflow, add the Execute Workflow node to call this sub-workflow
This approach provides significant benefits, as you can test each component independently. If a specific part fails, you only need to debug the small sub-workflow rather than troubleshooting the entire system [9].
Create reusable logic blocks
When designing workflows, watch for repetitive patterns that could become reusable components. If you find yourself copying the same group of nodes more than once, that logic belongs in a separate sub-workflow [10]. Some excellent candidates for modularization include:
- Data validation routines
- Notification systems
- API authentication sequences
- Logging mechanisms
For example, rather than implementing the same error handling logic across multiple workflows, create a dedicated “Error Logging” sub-workflow that can be called whenever needed.
Add notes and naming conventions for clarity
Documentation provides crucial context that explains the “why” behind your workflow logic. n8n’s Sticky Notes feature lets you add comments directly on the workflow canvas [9]. Place notes at the beginning of logical sections to explain complex parts or document data structures.
Additionally, clear naming conventions make workflows instantly understandable. Instead of generic names like “HTTP Request,” rename nodes descriptively—such as “Get User Data From API” [9]. For workflows themselves, use names that describe their purpose, like “Sync New Customer Contacts to Postgres DB.”
These documentation practices aren’t just helpful for team collaboration—they’ll also save your future self considerable time when revisiting complex workflows months later.
Testing, Debugging, and Going Live
After building your workflow, thorough testing becomes crucial before deploying it to production. n8n offers powerful tools to streamline this process and ensure reliability.
Use pinned data and logs for debugging
Debugging complex workflows becomes straightforward with n8n’s data pinning feature. This lets you save output data from a node and use it for future test executions without repeatedly requesting data from external systems. To pin data, simply run your node and click the “Pin data” button in the output panel. This saves time and prevents consumption of API rate limits during testing.
For deeper troubleshooting, n8n provides comprehensive execution logs. These logs show if workflows succeeded or failed, along with execution times. Access workflow-specific logs via the Executions tab or view system-wide logs through the Overview section.
Handle errors with fallback nodes
Protect your automations by setting up error handling with the Error Trigger node. This creates dedicated workflows that execute automatically when other workflows fail. These error workflows can send notifications via Slack, email, or SMS, helping you respond quickly to issues.
Save and activate your automation
Once testing is complete, activate your workflow by toggling the “Inactive” switch to “Activated” in the top navigation bar. Before activation, configure Workflow Settings, where you can set timezone preferences, execution retention policies, and timeout limits. Remember that pinned data is only used during development and won’t affect production executions.
Conclusion
N8n stands out as a powerful, versatile workflow automation platform that truly democratizes automation for beginners and experts alike. Throughout this guide, we’ve explored how this innovative tool lets you create complex workflows without writing a single line of code. The drag-and-drop interface, combined with affordability at just $60/month compared to Zapier’s $253/month, makes n8n an excellent choice for businesses of all sizes.
Additionally, n8n’s self-hosting capabilities provide unmatched data sovereignty, especially important for organizations with strict security requirements. The platform’s execution-based pricing model delivers predictable costs regardless of workflow complexity, thus saving substantial resources compared to per-operation billing models.
What sets n8n apart, undoubtedly, is its seamless integration of AI capabilities within standard workflows. By combining AI agents with traditional nodes, you can build intelligent systems that not only automate tasks but also make decisions and analyze data. These AI-powered workflows, alongside modular design principles, create scalable solutions that grow with your business needs.
Testing and debugging features such as pinned data and comprehensive logs ensure your automations run smoothly before deployment. Therefore, you can confidently build, test, and activate workflows knowing they’ll perform as expected in production environments.
Whether you’re creating simple notification systems or sophisticated AI-powered applications, n8n provides all the tools needed to streamline your business processes. Have a project in mind? Contact us to discuss how we can help you implement custom n8n workflows tailored to your specific requirements.
Remember, automation isn’t just about saving time—it’s about freeing your team to focus on creative, high-value work while letting n8n handle the repetitive tasks. Start building your first workflow today and experience firsthand how this powerful platform can transform your business operations.
Key Takeaways
Master n8n’s visual workflow automation to eliminate repetitive tasks and build powerful integrations without coding knowledge.
• n8n costs 70% less than Zapier ($60 vs $253/month) with execution-based pricing instead of per-operation billing • Build workflows using five node types: Trigger, Action, Logic, Code, and AI Agent for complete automation control • Create modular workflows with Execute Workflow nodes to build reusable components and scale efficiently • Integrate AI agents with OpenAI or Gemini to add intelligent decision-making to standard automation workflows • Use pinned data and comprehensive logs for thorough testing before activating production workflows
n8n’s unique combination of affordability, self-hosting capabilities, and AI integration makes it ideal for businesses seeking data sovereignty while building sophisticated automations. The platform’s execution-based pricing model provides predictable costs regardless of workflow complexity, making it especially valuable for teams running multiple complex automations daily.
FAQs
Q1. How do I create a basic workflow in n8n? To create a basic workflow in n8n, start by determining your goal, then add a trigger node to initiate the workflow. Next, connect action nodes to perform specific tasks. Use logic nodes to control the flow, and finally, test and activate your workflow. Remember to name your nodes descriptively for clarity.
Q2. What are the main types of nodes in n8n? n8n uses five main types of nodes: Trigger nodes to start workflows, Action nodes to perform tasks, Logic nodes to control flow, Code nodes for custom scripts, and AI Agent nodes to integrate artificial intelligence capabilities. Understanding these node types is crucial for building effective automations.
Q3. How does n8n compare to other automation tools like Zapier? n8n offers several advantages over tools like Zapier, including more affordable pricing ($60/month vs $253/month for comparable plans), self-hosting options for data sovereignty, and an execution-based pricing model. n8n also provides advanced AI integration capabilities and doesn’t restrict access to premium nodes.
Q4. Can I integrate AI into my n8n workflows? Yes, you can integrate AI into n8n workflows using the AI Agent node. This node supports various AI providers like OpenAI and Google Gemini. You can add memory to maintain context and incorporate tools to extend your AI agent’s capabilities, allowing for intelligent decision-making within your automations.
Q5. How can I debug and test my n8n workflows? n8n provides several tools for debugging and testing workflows. Use the data pinning feature to save node outputs for repeated testing without consuming API calls. Comprehensive execution logs help identify issues, and the Error Trigger node allows you to set up dedicated error handling workflows. Always thoroughly test your workflow before activating it for production use.
References
[1] – https://blog.n8n.io/make-vs-zapier/
[2] – https://www.digidop.com/blog/n8n-vs-make-vs-zapier
[3] – https://n8n.io/pricing/
[4] – https://docs.n8n.io/workflows/components/nodes/
[5] – https://www.linkedin.com/pulse/n8n-triggers-from-test-production-zacharia-kimotho-3utjf
[6] – https://docs.n8n.io/integrations/builtin/cluster-nodes/root-nodes/n8n-nodes-langchain.agent/tools-agent/
[7] – https://github.com/n8n-io/n8n
[8] – https://www.lindy.ai/blog/n8n-pricing
[9] – https://www.hostinger.com/tutorials/n8n-best-practices
[10] – https://www.optimizesmart.com/modularizing-n8n-workflows-build-smarter-workflows/
