Agentic AI Tutorial Using n8n | How To Build AI Agents With n8n | Agentic AI Course | Simplilearn

n8n is not just another automation tool. It is a platform already used by over 2 lakh people worldwide with 3,000 plus enterprise customers and it is helping teams move from simple automation to something far more powerful. That is agentic AI. Now, just think about this for a second. What if your workflow could do more than just follow steps? What if it could read an email, understand the problem, decide what matters the most, draft a response, update your tools, alert the right team, and keep the whole process moving automatically? Not just respond, not just automate, but actually think through the next step and act on it. That is what makes agentic AI so exciting. And the best part is it's working with n8n. You do not need a giant engineering team or some overly complex setup to start building it. You can create these smart workflows in a way that is visual, practical, and beginner-friendly. So, in this video, we are going to understand what agentic AI really means, why n8n is such a powerful platform, and how you can start creating your own smart AI workflow step by step. And trust me, once you understand this concept, you will never look at automation the same way again. Before we dive in, let me quickly walk you through what we are going to cover in this video. First, we will understand what agentic AI really is, why it is being seen as the next big evolution of automation. Along with that, we will also look at why n8n is such a powerful tool for building agentic AI workflows, specially because of its flexibility, integration, and no-code power. After that, we will move into the practical side and explore how to get started with n8n. We will also look at the interface, understand its core features, and see how you can integrate AI APIs like OpenAI GPT models, or even custom models into your workflow. Once the basics are clear, we will start building and see how to create your first agentic AI workflow in n8n. In this part, we will work through a useful example where AI helps with email analysis and smart responses. Then, we will take things one step further and look at the advanced agentic AI capabilities. This includes dynamic routing, conditional triggers, looping, and even memory functions that can make your workflows much smarter. We will also explore real-world use cases to understand where all of these become useful in real-life scenarios. Next, we will cover common issues and troubleshooting tips so you know what can go wrong while building agentic AI workflows and how to handle these situations properly. Along with that, we will also discuss best practices for scaling and securing your n8n automations. And finally, we will wrap up with next steps, useful resources, and ways you can start experimenting on your own. So that by the end of this video, you do not just understand agentic AI in n8n, but you actually feel ready to start building with it. Also, just a quick information, if you want to dive deeper and gain more knowledge about generative AI, I highly recommend you checking out this professional certificate program in generative AI, machine learning, and intelligent automation by IHFC, TIH of IIT Delhi, powered by Simplilearn. In this program, you will learn important skills like generative AI, machine learning, deep learning, NLP, and intelligent automation in a very practical way. The course is 11 months long and is delivered in a live, online, interactive format, so you can learn directly from the experts. You will also work on 12 plus industry projects, 165 plus guided exercises, and use 20 plus AI tools and libraries for hands-on learning. The program also gives you Microsoft course completion badges and trophies, which can help strengthen your professional profile. If you want to build strong AI and automation skills that are useful across industries, this program can be very good step for your career. So, if you are looking to grow in the world of AI and machine learning, this is a great program to explore, trust me. Do check out link in the description box below and in the pinned comments for more details. So, before we deep dive, there is a quick quiz question for you. And the question is, what is the main idea behind agentic AI? And your options are option A, it stores data in the databases. Option B, it can understand task and make decisions. Option C, it is only used for website design. Or the option D, it works only with automation tools. Let me know your answers in the comment section below and let's see who will give the right answer first. Now, without any further ado, let's get started. Let us begin with the core idea. Most of us already understand automation in simple sense. When a form is submitted, send an email. When a file is uploaded, notify the team. When a customer places an order, update the spreadsheet. That is useful, but it is still rule-based automation. Agentic AI takes things much further. Instead of only following fixed instructions, it can observe incoming information, reason through it, make decisions, choose the next best action, and continue moving towards a goal. That is why it feels more like an intelligent agent than a simple automated workflow. A very easy way to think about it is like this. Traditional automation is like a train running on a fixed track. While agentic AI is more like a smart driver who can look at the road, respond to traffic, take different turns, and still reach into the destination. That flexibility is what makes it so powerful. Now, where does n8n fit into this so well? Because n8n gives you a visual space where you can connect tools and logic, trigger actions, call AI models, route decisions, and build workflows that actually do meaningful work. You're not just building a chatbot here. You're building systems that can analyze, decide, and act. That is why n8n is such a strong tool for agentic AI. It is flexible, it integrates with a huge number of tools, and it gives you the simplicity of no-code or low-code building while still being powerful enough for serious automation. So, let me ask you something here. Have you ever wished an AI could do more than just give you an answer? Have you ever wanted it to actually help complete part of your work? Because that is exactly the shift we are talking about today. So, now let's begin by understanding how we can set up our n8n account. So, now we will learn how to set up our first n8n workflow. For this, we need to go to the official website of n8n. So, open your default web browser and go to your n8n website. So, this is the official website of n8n. Here, you can either sign in or get started. So, I'm clicking on get started. Here, you need to give your company email. So, give it. And click on submit. You will receive the verification email, so verify this. So, when you will log in, this interface will appear. And it is a home page for n8n website. Initially, you will be having a default mode, but I will suggest you going to the dark mode. For this, you can click on settings, personal, and from here, you can enable your dark theme. So, it is having system default, light theme, dark theme. I will suggest selecting dark theme. Now, go back. Now, you can see your 14 days free trial has started. So, you can easily create as many as workflows as you can in these 14 days. So, here and now, we will first learn how to create your first workflow. So, you can add manually like from clicking here, add your first step, or you can even build using AI. But firstly, we will start creating manually. So, click on this add first step. First of all, uh now, we will give the name for our project, then we'll give the name for our workflow. So, from here, on this plus icon, you and you can click on project. And from here, you can give the name for your project. And from here, you can give the name for your workflow. Now, we will create our first workflow. And it is where all the magic happens. So, first, we will create our trigger node. You must be unaware about what a trigger node is. So, let me explain it to you. You can think it as your blueprint for your automation. It is basically a step where your workflow will begin. So, it is just giving like the trigger to start the working of your workflow. So, trigger is basically an event that will start your workflow. So, a workflow won't run on its own unless you manually start it. So, it is just like the launch button or the alarm bell for your automation. So, when a certain event happens or a condition is met, the alarm goes off and the workflow kicks in. So, let's click it. So, what triggers this workflow? We have different triggers here. You can see on the board. Trigger manually, on app event, on a schedule. Uh it runs when you want to do a flow every day, hour, or a custom interval. It is very important if you want to give a periodic workflow. You can even trigger your workflow on a webhook call, on form submission, on chat messages, and there are many other ways to trigger your workflow. But for our example, we will begin by creating on chat message trigger. So, this runs the flow when the user sends a chat message for the AI nodes. So, let's click on it. Here you will see parameters and settings on the left side. You can even make our chat publicly available by clicking on this. Here you can copy-paste this chat URL, which you can use further. Here we have the authentication. So, basically there are three types of authentication, basic auth, So, it is highly recommended to use any of the authentication, but as of now I'm using none. Just to show the main functionality of N 10, I'm ignoring this. And here you can give the initial message. Let's suppose we can customize our message by giving our name. I'm giving my name, that is Stuti. So, this is the initial message. We can keep it as expression also, and we can keep it in the fixed format also. So, initially I'm keeping it in the fixed format. You can even add different fields, like allow file uploads, allowed file mime types, input placeholders, load previous sessions, custom chat styling, and many more. So, as of now I'm adding custom chat styling. Now I will test our chat. See, here our trigger node has been successfully created, which says when chat message received, this particular node will activate. Here you can see when I will hover on this, you will see three icons. This indicates it will execute this step. This icon will help you deactivate this node. And this icon will help you delete this So, let's execute this node. So, on left-hand side, you can see the chat option. Here we can type our message. Let's suppose I type hey. See, the node has successfully executed, and the output has came on the screen as hey. So, this node has been successfully initiated and started. Now we'll be doing our next step, that is adding AI agent node. Click on this. Click on AI. And then you will find many AI nodes here, like AI agent, Anthropic, Google Gemini, Guardrails, Ollama, Open AI, and so so many AI nodes. As of now, I'm clicking AI agent. Here you can see on the left-hand side parameters and settings. Here you can see the source of the prompt as connected chat trigger node. You can even select as defined below, but as of now we are using as connected chat trigger node. And we will click on execute step. But it says an error, a chat model sub node must be connected and enabled. So, there is a problem with this AI node, and I'll show you what is the problem. When we go back, we have forgot to add the chat model in this. So, in AI agent, first we need to add chat model, then memory, and then tool. So, first of all, I will explain you chat model, and then one by one I'll explain you the other both. So, click on this chat model that you will connect with your AI agent. So, here are many chat models available, like Anthropic chat model, Azure, AWS, Deep Sea, Google Gemini, Grok model, and many more. As of now, for my example, I'm using Google Gemini model. Because uh it is free to access. We can easily access it using free API key. That is why I'm using Google Gemini chat model. You can click on this. And then you will need to create the new credentials. So, you need to click here, create new credentials. And here you will have to add your API key, that is Google Gemini API key. So, from where you will find this key? So, follow along. Click on Google Gemini API key. Go on Google AI Studio API key. Here you will find the API key section under dashboard. And here you can create These are all the API keys previously created. So, create your API key. Give the name to your key. I'm giving my name. Here you can give your project name to connect it with successfully. Then create the key. Then the key will appear. See. Here we have created our credentials, our name, and our project number and name. So, from here we can copy our API key. We will go back to our website. And we will paste it here. Then at the section of allowed HTTP request domains, we will select all. You can even select specific domains or none, but all selecting is highly recommended. Then click on save. See, credential successfully created in N 10 demo. So, we can cross this. Now we will go on this AI agent. And here we will select define below. And rather than giving fixed expression, we will give this expression. We will give the prompt as What What is the date today? And using these curly braces, we can give the date format. So, this is how the output will come, the result format. What is the date today? And that the date time format. So, this is how we can add the chat Let's execute this step. See, the node executed successfully. Now we will go back to our canvas. See, this is how uh the connection will look on the screen. You can even customize it according to your own preference, the way you like it. You can do it. See, on the screen, when we will execute this node, the output has came on the screen as the date you provided is March 19, 2026. That is the today's date. When we will pass this message, see, the node is being executed. Based on the timestamp you provided, the date is March 19, 2026. So, this is how the output has came on screen. Now let's go back. Click on AI agent. And keep it back as connected chat So, that it can work seamlessly with all the prompts we give, not just a specific prompt regarding the date. And then again execute this step. Node executed successfully. Go back. Let's suppose here we give another message as The number is 10. Just wait for a while. The output has came as okay, 10. Let's suppose I again give this as like this. What is the number? So, here you can see on the screen that it is not able to guess the memory. The AI agent has successfully forgotten the number of the previous chat we had with it. Where we have given the number as 10, but it has successfully forgot it. That means it cannot save the previous memory. But we want our previous chats, right? So, that we can connect our conversation as we do with the chat GPT. So, for this, we have another concept here, that is memory. So, now we will add memory to our AI agent, so that it can easily remember our previous chats. Let's suppose I'll click on this. Here are different types of memory supported by AI agents, like MongoDB chat memory, Postgres chat memory, Zata, and many more. But for beginners, it is highly recommended to use simple memory. Here you will find different parameters, like session ID, which is like connected chat trigger node here. You can even use at defined below, but as of now I'm keeping it as connected chat trigger. Here the session key is being provided from the previous node. Keep it as it is. And the context window length, which is five. It means how many past interactions the model received as context. The last five conversation we had with it. So, now let's get back. See, the memory has been added to our AI agent. Let's suppose I give again the number Let's run this. And check the output. Workflow executed successfully. See here on the screen, when we give the command What is the number? It recollects from the memory and gave the output on the screen as the number is 10. Because it has this memory now. It has saved at least the five chat in his memory. So, this is how we can add Google Gemini chat models, like different chat models and memory to your AI agent. Now, we will learn how to add tools. So, click on this tool. So, here we have different types of tools like AI agent tool, N8N workflow tool, code tool, HTTP request tool, MCP client tool, and many more. I want to click I repeat. I want a Gmail tool so that it can automatically draft an email for me. It will be a real-world use case for you how you can automatically draft a Gmail using N8N workflow. So, let's see here. Let's suppose we write Gmail. Gmail tool, click on this, then this interface will appear. Here you need to set the credentials. So, click on this credential part. So, because I have already connected with my Gmail, it is showing list This is showing it like this that account is connected. So, just to show you again, you need to sign in with your Google. That's it. In your connection, sign it with your Google. You can choose any of your accounts. I'll choose my account. So, here in your case, it will ask your login ID password, and then it will connect your N8N with your Google account. Mine is already connected. So, it is showing like this. In your case, it will get automatically connected to your N8N project. I'll click continue as of now. See. And here, under allowed HTTP request domains, it's highly recommended to click on all. And then we'll save. Now, here we need to give tool description that is we'll set it automatically based on the resource and operation. You can even set manually as the description, but here we are setting automatically. Here the resource will be I guess we are drafting a message, so we'll draft a message. Then operation is we are getting a message, let's suppose, so we'll click on get message. This is the draft ID. You can even add other options, which is attachment prefix and download attachments. So, as of now we'll ignore this. You can even add Now, we will go on our AI agent. And we will give it as define below. And here we will give our prompt user Hey, we are offering discounts. And the source for prompt user is define below means it's customized. Now, we will execute this node, and this node has been executed successfully. Here we will go back to our canvas, and you can see our email node has been connected to your AI agent, which says get a message in Gmail. And we have already connected our Gmail account with N8N demo, so we will see the message. Let's go back here once again. See here, in define below, I have given the another message as Hey there, your workflow name is offering discounts. So, this will come as your message as a draft message in your Gmail. So, you can automatically draft your message or send your email to many numbers of people you want to share. You can even add other options like system message, max iterations, return immediate steps, enable streaming, batch processing, and many more. As of now, we are leaving this. See here, our node get executed Just to check this, we'll go back to our Gmail account, which we connected with our project, and see whether the draft mail has been created or not. See, when we'll come back on our Gmail, in draft section, you can see it has drafted a message which says, Hey there, my workflow three is offering discounts. So, this is how you can connect different nodes with your AI agent and make it work. So, it has executed all the three nodes successfully, where we have connected first the chat model, then we have assigned memory, and then we have assigned a tool. And in our case, we have used a common example of Gmail. You can even use example of weather APIs. You can connect the tool uh the online tool, weather tool, to connect and see how it works with weather. And you can even uh work with form responses. For example, for initial level, for beginners, I've just shown an example how to connect an email tool with your AI agent, and it has worked flawlessly. So, this is how we can create workflows in our N8N website. And I will highly recommend you exploring different features of N8N because it is very, very interesting. Trust me. Don't just sit and don't just practice this much. Explore on your behalf. Try adding more nodes. Try adding more tools. See how it reacts with other tools. Once your free trial gets ended, you can even upgrade now. So, click on this. You can choose any of your plans. There are three plans as of now. So, in first plan, that is starter, it is around 24 euros monthly. Here you will get like 2.5k workflow executions and active workflows, infinite active workflows. This all you will receive in your starter plan. One shared project, five concurrent executions, unlimited users, one-day workflow history, and so on. In your second plan, which is pro plan, it will cost you around 60 euros monthly, and you will get around 10k workflow executions and infinite active workflows. Three shared projects, 20 concurrent executions, seven-day insights, admin roles, global variables, and what not. And here's the enterprise plan, which is ideal for businesses. So, uh choose according to your requirement, and practice as much as you can in these 14 days. Trust me, you will enjoy working with N8N. Of course, in the real world, things do not always work perfectly on the first attempt. And when AI is involved, troubleshooting becomes even more important. One common issue is weak prompting. Sometimes the workflow seems fine, but an AI input or the output is poor because the instruction given to the model is too vague. Instead of just saying analyze this email, it is much better to clearly ask for the intent, urgency, summary, next action, and response draft in a structured format. Better prompts always lead to better outputs. Another issue is output format. If the AI returns a messy block of text, your workflow may struggle to use that result in the next step. That is why structured outputs are so valuable. Whenever possible, ask for clearly separated fields or machine-readable formats so the workflow can continue smoothly. Now, the third issue. It's overtrusting the AI. This is always a big mistake. AI can be helpful, but it should not be blindly trusted in every situation. Sensitive tasks should always include validation, confidence checks, fallback routes, or human approval. The AI should support decision-making, not take complete control without supervision. Now, scaling is another challenge. A workflow that works perfectly with five tests may run into troubles when handling hundreds and thousands of requests. That is why you need clean logic, proper logging, controlled retries, and thoughtful API usage. Security also matters a lot. If your workflow handles personal or business-sensitive data, you need to protect credentials, avoid exposing private information unnecessarily, and follow safe data-handling practices. In short, the best workflows are not just smart. They are also stable, secure, and well-structured. So, where do you go from here? The best advice is simple. Start small, but start. Do [snorts] not wait until you know everything. Do not wait until your workflow idea becomes perfect. Begin with one useful problem. Maybe automate email. Maybe build a lead routing system. Maybe create a smart summarization workflow. Then slowly improve it. Add decision-making. Add memory. Add conditional triggers. Add human approval. Add better prompts. Add more integration. That is how real learning happens. One of the best things about N8N is that it allows you to experiment quickly. You can build something, test it, break it, improve it, and learn from the process. And that is exactly how you grow in this space. Also, do not build alone. Explore communities. Watch how others design. Study examples, and share your own ideas. Agentic AI is not just a passing trend. It is becoming a major shift in how people think about automation. The sooner you begin exploring it, the sooner you will start building a real advantage for yourself. So, today we did not just learn about another tool. We talked about the whole new way of thinking. A way where automation is no longer limited to fixed rules and where workflows can start understanding, deciding, and acting with intelligence. That is what makes Agentic AI so powerful and that is why AnyTime is such an exciting platform to build with. Because once you combine AI with workflows, you're no longer just automating tasks. You can create systems that can actually help you work smarter. And this is just the beginning. The people who learn this now are not only learning a tool for today, they are learning a skill for the future. The future where intelligent workflows will become a part of every business, every team, and almost every digital process around us. So, do not just watch this video and move on. Take one idea from it, build one workflow, test one use case because your first Agentic AI system does not have to be perfect. It just has to begin. And who knows, the workflow you all start building today in AnyTime might become the smartest digital teammate you have tomorrow. So, this is the end of our today's video. If you have any doubt or any questions, ask them in the comment section below and our team of experts will reply to you as soon as possible. I'll see you in the next video. Till then, keep learning and keep growing with Simply Learn.