What is n8n? n8n is a low-code automation tool ➢ It allows you to build tools as workflows (super powerful!!) Automating workflows: ➢ Increased Efficiency ➢ Time & Cost Savings ➢ Scalability ➢ Improved Data Handling ➢ Enhanced Customer Experience Why Should You Learn n8n? ➢ Empowering Non-Developers with AI Automation ○ You don’t need to know how to code ➢ Access to 300+ Built-In Integrations ○ Google apps, Microsoft apps, Slack, X, etc. ○ String them together… infinite possibilities ➢ Connect to Almost Any Tool ○ Extend Using APIs, Webhooks, and Custom Code Part 1: Getting Started: 1.
Set Up n8n 2.
The Interface Set Up n8n Self-Hosted Cloud Control & Flexibility Ease of Use Data Ownership Availability & Reliability Cost Security Installation & Maintenance Data Handling Customization How to Choose: Self Hosted if… ➢ You need full control over your data and infrastructure ➢ You want to fully integrate n8n deeply within other on-premise systems ➢ You are comfortable handling server management Cloud if… ➢ You prefer simplicity ➢ Quick setup and reliable hosting ➢ You’re okay with paying a subscription for a managed service ➢ You don’t mind data being handled by a third-party provider n8n Interface ➢ Workflows, Nodes, and Executions Workflow - The recipe Nodes - Each step, each ingredient Execution - When an order comes in ➢ Walkthrough of the Editor Interface ➢ Accessing Community & Templates Part 2 Core Concepts: 1.
Types of Nodes 2.
Building Your First Workflow (Example) ➢ Trigger Nodes ➢ Data Transformation ➢ Action Nodes ➢ Logic Nodes Trigger Nodes What They Do ➢ These tell n8n when/how to start the workflow Types: ➢ Manual, Scheduled, On Chat, On Event, Called by Another Workflow , etc.
Action Nodes What They Do ➢ The “doers”, they perform specific tasks Types: ➢ Send Email, Create Record, Make API Request, Get Text Messages, Set Calendar Event, etc.
Data Transformation Nodes: What They Do ➢ Change or process the data flowing through Types ➢ Set: Add fields, change values, reduce data ➢ Aggregate: Combines data into a single output ➢ Merge: Combining data from two sources Logic Nodes What They Do ➢ Conditional decision makers Types: ➢ If: True or False ➢ Switch: Routes data based on condition ➢ Wait: Pauses until a condition is met Building Your First Workflow: Example Workflow: Automatically Process and Summarize Customer Order Part 3 RAG and Vector Databases: 1.
What is RAG?
2.
What are Vector Databases?
3.
Building a simple RAG AI Agent Retrieval-Augmented Generation (RAG) Powerful technique that combines two approaches.
Helps AI models provide more accurate and relevant answers.
Retrieval ➢ Retrieves relevant information from external sources Generation ➢ AI uses this information to generate an answer Why RAG Matters No Guessing ➢ AI Assistant ○ It’s not gonna make up an answer based on training data ○ More reliable and up-to-date information What are Vactor Databases?
RAG needs a way to store and retrieve data efficiently.
Vectors ➢ Data stored in “vectors” ➢ Numerical database that represents the meaning of words, text, etc. ➢ Relevant information quickly Embedding Data to Data Loading ➢ Handles data coming in to pass it off to a text splitter Text Splitting ➢ “Chunks” up the text for more efficient retrieval ➢ Character, Recursive Character, Token Building an RAG Ai Agents Example Workflow: Chatting with an Agent for information about Nike earnings Part 4 Expanding Agents: 1.
Building Workflows as Tools 2.
Showcasing Examples The Power of Custom Tools 1.
AI Agents Can Use Them 2.
Tools Can Be Reused and Combined 3.
Scaling Part 5 API & HTTP Requests 1.
APIs, Endpoints, Calls 2.
HTTP Request 3. n8n Examples APIs Application Programming Interface: ➢ Think of it as the bridge that allows two different software programs to exchange information API Endpoint The specific address (URL) for our request API Call The request you make to an API HTTP Request The method used to send the API call over the internet What is an HTTP Request?
Talking to other websites or services GET ➢ Get data, asking for information POST ➢ Send data, sending information How Do API Calls & HTTP Requests Work Together?: HTTP Request is how you make an API Call.
API The service you’re talking to API Endpoint The Kitchen API Call The request HTTP Request The mechanism used to deliver the request Part 6 The Final Part: 1.
Error Workflows 2.
Best Practices 3.
Next Steps Best Practices: ➢ Keep Your Workflows Organized ➢ Use Sub-Workflows for Reusability ➢ Implement Error Handling ➢ Optimize for Scalability Next Steps: ➢ START BUILDING ➢ Explore Advanced Templates ➢ Experiment with New Integrations ➢ Build and Share Workflows n8n Masterclass Congratulations! ❓ Frequently Asked Questions (Q&A) Q: What is n8n and why is it important?
A: n8n is a powerful open-source, low-code automation tool that lets you build scalable, logic-based workflows.
It integrates with 300+ apps and services like Google, Slack, X, and custom APIs—making it ideal for anyone looking to automate without writing code.
Q: Do I need to know how to code to use n8n?
A: No. n8n is fully visual and logic-based.
If you’ve ever used tools like Zapier or built formulas in Notion, you’ll feel right at home.
Q: What can I automate with n8n?
A: Nearly anything: Lead gen follow-ups Slack or email notifications YouTube/Instagram posting AI content workflows APIs and AI chat agents Even querying RAG agents with vector databases Q: What’s the difference between Cloud and Self-Hosted n8n?
A: Self-hosted: Gives full control over data, better for developers or enterprise needs.
Cloud: Great for beginners who want an easy, secure, and reliable start.
Q: What are Nodes and Workflows in n8n?
A: Workflows = The complete automation blueprint.
Nodes = Each step (action, condition, API, transformation).
Executions = Each time a workflow runs in real-time.
Q: What is RAG and how does it work in n8n?
A: RAG (Retrieval-Augmented Generation) enhances AI by connecting it to real-time, external data.
You can use n8n to build RAG agents that fetch documents from a vector database, chunk and embed them, and give context-aware answers with GPT models.
Q: What are vector databases and why do they matter?
A: Vector databases store “meaning” of data numerically.
This allows AI agents to retrieve relevant documents by semantic similarity — crucial for accurate RAG responses.
Q: What are APIs and how are they used in n8n?
A: APIs are like bridges between tools.
In n8n, you can use HTTP Request nodes to make GET, POST, PUT calls to nearly any service on the internet—giving you unlimited automation flexibility.
Q: What are the best practices for building in n8n?
A: Keep workflows modular and clean Use sub-workflows for reusable logic Add error-handling branches Optimize for scale: fewer nodes, efficient triggers, caching where needed Q: What should I do after learning the basics?
A: Start building real-world use cases Explore advanced AI integrations Try using custom GPT models Connect to CRMs, webhooks, databases Join the n8n community and share your flows AI Prompt Builder - Complete Setup Guide My Tech Stack – Tools I Use Within My Agency AI Prompt Builder