Beyond Zapier and Make: Meet N8N

Automation platforms have been evolving rapidly, and just when you thought Make had perfected what Zapier started, N8N enters the scene to change everything again. For business leaders who've felt disconnected from their automation processes, this episode might be the breakthrough you've been waiting for.

N8N isn't just another automation tool—it's the first platform that bridges the gap between technical capability and business understanding. Finally, non-technical leaders can actually see and comprehend what's happening in their AI workflows, ending the black box mystery that has plagued automation for years.

In this episode, Alane and Micah explore why N8N stands apart from Zapier and Make, diving deep into its visual workflow capabilities and advanced AI agent development features. They discuss the unique challenge of training developers to shift from traditional logic-based programming to AI-agent thinking, and why this mindset change is crucial for successful implementation.

Key insights include how vector databases work with AI agents, the importance of visual workflows for business leaders, and practical examples of how to structure company documentation for AI access. Whether you're a CEO trying to understand what's possible or a technical leader planning your next automation strategy, this episode provides the clarity needed to move forward confidently.

In this episode, you'll learn:

• How N8N combines the best features of Zapier and Make with cutting-edge AI capabilities
• Why visual workflows finally make automation understandable for non-technical leaders
• The training challenges developers face when shifting to AI-agent development
• Real-world examples of vector databases and structured data for AI agents
• How to bridge the communication gap between technical teams and business leadership
• Practical steps for implementing N8N in your organization

This isn't about replacing your current tools—it's about understanding what's now possible when you combine visual workflows with intelligent AI agents in one powerful platform.

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Transcript

0:00:00 - (Alane): Welcome to Automate youe Agency. Every week we bring you expert insights, practical tips and success stories that will help you streamline your business operations and boost your growth. Let's get started on your journey to more efficient and scalable operations.

0:00:18 - (Micah): So Alane, it was February of this year where we did an episode of make vs Zapier. It is now the beginning of June, has not been very long since we did that episode and we need to introduce our listeners to a new platform called N8N. It's the letter N, the number 8, the letter N. Not my favorite name to say over audio or zoom or anything.

0:00:51 - (Alane): What did you just say?

0:00:54 - (Micah): The what? However, naming aside, it is an amazing platform. It would compete with Zapier, it would compete with Make. It is a little bit a league of its own because it's again, just like Make. You know, our opinion took some of the best things of Zapier, made it better, made it easier to work with, made it more visual, all of that kind of stuff. N8N takes this to the next level. Getting the best parts of Zapier. We're getting the best parts of Make. This is actually open sourced so you can self host this technology that of course requires some advanced knowledge, but it also is cloud hosted just like make and Zapier.

0:01:38 - (Micah): What makes N8? I can't even say it, Alane. What makes N8N stand apart is that there's kind of a few different things. One, routing or being able to build more advanced automations is right at the tips of your fingers more capable than the other two. So that's a huge piece. Two, there's a code block which Zapier has a code block. It's a little cumbersome. This is a code block that can use JavaScript or Python.

0:02:10 - (Micah): What makes this so important is the third standout thing with N8N is that they've been a leader in the game for, for building AI agents. And so we've shifted a bunch of our production to N8N for these reasons. And what that means is we can build more advanced automations. We can write code that takes complex data and simplifies it down and then we can send that simplified structured data to an AI agent. I know that sounds technical and confusing, but there is immense power in that.

0:02:46 - (Alane): So whenever we're. Because I'm not a technical person and so what I like when I look at an N8N sequence is it's so clean and you can see where the AI agent is operating, what access it has. You know, in our previous episode we were talking about having access to company information. So an AI agent, you can see where it has ability to access that information, whether it's in a Google Drive or SharePoint or something like that.

0:03:15 - (Alane): But then also, hey, if it's not there, then you can also incorporate where it's finding things through other AI like OpenAI or anthropic or something like that, where it's able to pull too. And for a non technical person you're still able to understand what is happening if you need to.

0:03:33 - (Micah): I think that's interesting you bring this up Alane. I wasn't even going down this path at all in my mind about it but, but you're absolutely right. One of the things that I know when we first started prototyping stuff in N8N I would they have a note capability and so you can almost like frame sections of the workflow in, in the notes with headers and descriptions and lists. So anybody technical, non technical, can look at this, it's color coded and go, oh, that's what this part of the workflow does. That's what this agent does. That's what that agent does.

0:04:12 - (Alane): And why I think it's so helpful when you're looking at that. If you are the decision maker bringing a technology like this in and it's a black hole to you, then you, it's harder to understand. Well, what could I have an AI agent do? What is an AI agent? I know when AI agents first came about and this wasn't in, this was last at the end of last year and I was joined in some webinars to learn about it and I was actually coming to you like Micah, we've got to learn what this AI agent stuff is.

0:04:40 - (Alane): And it was so people had a hard time articulating it. I was doing these webinars, I'm like, they, they're just not really explaining what it is and how it works. And for a non technical person to watch that and go I don't see where we can use this. It wasn't until we started building it internally and I could see, oh, an AI agent is like almost like a person sitting right there and it's going to access the docs here and it's going to have access to AI and then it's going to outp this way and we can put a chat bot on top of it. So an interface so it can chat with it. Then I'm like okay, now I got it. Now I understand a hundred different ways we could implement this in our company right now.

0:05:18 - (Alane): And that's why I think it's great for non technical people to view this so that it's not a black hole. They have a, an understanding. They don't need to go and build it themselves. I'm not going into N8N and building anything.

0:05:31 - (Micah): Yeah, I wouldn't recommend it.

0:05:32 - (Alane): No, I'll go into Zapier and make and dabble, but I'm not doing anything too complex. But I can now understand how it works enough to say this is what I need team. This is the access that I have. This is a Google Drive folder with these assets said can you go build this for me? And that I think is a key piece of this when you are in the leadership position saying I want these things and need to be able to know well what's possible.

0:05:58 - (Micah): I think so. Let me, let me frame what you just said and I think I'm having a bit of an epiphany on why, why we wanted to record this episode first of all and even say like we're not being paid by N8 N8N doesn't even know probably who the hell we are. But not until this episode. But essentially what, what you're saying, Alane, and what I, what I'm saying is it has all the technical capabilities to do to build whatever we want, but it has an interface that allows the non technical side of the business to not make it a black, black box or a black hole.

0:06:43 - (Micah): It can be visible, clear and understood on both sides. Toss my whole glasses off here. But it can be understood on both sides of the company. The technical and the development side and the leadership, non technical side that needs to understand what's going on, how does this work and most importantly, how do we take this technology and where does it apply to the rest of the business? Because just think back on, on all the development conversations that we've ever had with any developer in our entire careers and I think the people listening can probably relate to pieces of this, which is I want to do X.

0:07:24 - (Micah): You're going to get two types of developers. No way. That's too hard or 100% we can do that. And it doesn't matter which direction you go, it's still a shit show the entire time you're developing this out. And then the only output is either an interface that makes sense after a ton of work. But no non developer is going to look at code and go, yeah, I think that's exactly what we need. That's perfect. Yeah, I know how to apply this code to other parts of the business.

0:07:57 - (Micah): Like it just doesn't happen.

0:07:58 - (Alane): I don't know how to read Python, I don't know how to read JavaScript. You know those.

0:08:03 - (Micah): And it creates that disconnect.

0:08:06 - (Alane): Yeah, exactly. But I can understand what that innate in workflow is doing. And I actually put that in my speaking engagements because I want to empower people to understand that you just need to have the knowledge of what's available so you know what to do to implement. That doesn't mean you implement. I don't need to be the one to go and do these things. But you know what's capable. So you can go to the people that do know how to do it and say, I want this end result.

0:08:32 - (Alane): I have these assets. Because if you say, I'd like for a chatbot to access my FAQ docs and be able to answer it, okay, great. Where do you have those? Well, I have them in 85 different places. Okay. If you understand how an AI agent works, then you need, you know, I need these all in a place so the AI agent knows where to go. So even these like small little things, by just seeing what it looks like, helps you develop what it. What do I need to gather? What do I need to do so that it can get clean and done by an AI agent?

0:09:06 - (Micah): Yeah, yeah. I think this is not where I expected this episode to go, but I think this is such a super important one. Just let's bring attention to a new technology that will help people listening to this podcast episode, of course, to this whole recognition that the games change, that non, non tech roles can look at this and go, I understand it. When has that ever happened? Never in the past. And so this is, this is super, super interesting because we're also, I would say this crosses over with the non tech understanding of using AI in general. Just chatting with Claude, chatting with ChatGPT, getting answers, brainstorming ideas, taking a bunch of emails and documents and shoving it into a project and then having a chat with it.

0:09:59 - (Micah): Fine, let CEOs do this, let VPs do this, let's get this, get this out. And then we got to get back to the systemization piece of this, which is what we're talking about with N8N.

0:10:11 - (Alane): Mm. You know, the, the way that I look at N8N is when AI came out mainstream, came out three years ago, and everybody was like, oh my gosh, I'm gonna just use it to automate my business. And it just really wasn't there as a technology. And using N8N, we can't necessarily automate everything in your business, but it gets a whole lot closer, especially with merging what documents you already have with also supplementing with what's available in AI.

0:10:43 - (Alane): And you are able to do a lot more. I remember chatbots. Can I have a chatbot answer questions? Well, what do you have documentation for? That's still a key piece. You still need to have the documentation there. But yes, we can do that. And that is a really simple workflow to build where the AI agent can access those things.

0:11:05 - (Micah): So, you know, this is going to get a little technical, but just as an example, in N8N, we can create one workflow that analyzes an entire Google Drive set of documents. It will automatically create embeddings, which is basically chunks of the data from these documents, and it'll save it to a vector database, which is a database type that AI agents can access. At that point, you have a workflow that you can just point at a folder in Google Drive and go, hey, save all this to a vector database.

0:11:42 - (Micah): Then you can build an AI agent, an N8N that goes, hey, what's in this vector database? I can query it and I can answer questions. Whether I'm part of a workflow that's running every day or coming from a chat interface, it doesn't matter. Whatever the trigger is, it goes to the agent, that agent goes to the database, pulls the information it needs and starts taking action, which can then lead to other actions. So I want to, I know I'm not giving you a break to, to talk or reply to that right now, but I want to. I think there's this thread here that just popped into my mind of there's this, there's this whole like maybe a misnomer, I would say, of, wow, look at all the stuff we can do chatting with chat, GPT or Claude. If we imagine that's happening across a 20 or 30 person team, we're back to the world of mayhem.

0:12:42 - (Micah): Everybody's doing different prompts, everybody's saving documents, saving projects differently. Even if you have a team account, it's craziness.

0:12:51 - (Alane): Mm.

0:12:52 - (Micah): The world of standardization, systemization and streamlining operations in the AI age is N8N building simple workflows that do the same thing over and over and over, predictably, so that the systems can operate and help run the business and structure and streamline the business that way that the teams then leverage.

0:13:16 - (Alane): Yeah, and I want to point out that where you mentioned, like JavaScript and Python, you know, where we can have these code languages in there as well, or these coding blocks that this is very much is still a very technical thing for building powerful AI agents. I hear a lot like, oh, I created N8N and I created agents. I'm like, oh, do you code? No. Well, that's great. You can play around, but you're really at a superficial level of what an AI agent is capable of.

0:13:50 - (Alane): And you want to have a developer that understands vector databases. I mean, Micah, if you asked me to build a vector database, I don't even know what you're talking about. And you throw that term around all the time at the office like, oh, we need a vector database. Great, go do that, whatever that might be. But there's these things where we are talking about a database. And a database can look different. It could be a Google Drive folder, but it could also be an airtable, like a spreadsheet kind of thing.

0:14:19 - (Alane): So where it's pulling data from can look different. And a developer understands those types of databases. What needs to be there to pull things from? And so if you really want a powerful N8N AI agent sequence, then you do want to have a developer. The other side of this maika and I wanted you to talk to it is that there's so much training that needs to be involved for building an N8N because it is such a new technology.

0:14:48 - (Alane): Developers are used to building old school and there's sometimes a gap between N8N and yes.

0:14:57 - (Micah): So this man, way to bring up a topic. Alane. This is super interesting because, you know, this was one of the struggles that we've had is as we scale, who do we hire to help build these so that we can train them to help build these for our clients? And at first it was like, oh, let's get people operationally minded because they're building systems. And I think that works to a degree. With Zapier and a sonic ClickUp in Monday and even a little bit into make it does not work.

0:15:33 - (Micah): As we're entering in this new era, what you were just talking about with the technology choices and vector databases really comes down to optimization and knowledge of techniques. So do we have an AI that can summarize SOPs and save it as an index in an airtable base? Is that the right direction we should go? Do we just give it them? Do we just give them a Google Drive folder? Do we need to save everything to a vector database?

0:16:03 - (Micah): Do we need code that takes an API call response and narrows it down into structured data and simplifies everything so that the AI agent gets exactly what it needs versus giving all of that data to the AI agent and having it sorted out, there is huge differences not only in cost, time, efficiency and end result predictability that all of that comes into play. So then getting back to who does this, we've actually found that hiring people with more of a development technical background for this provides the best results.

0:16:42 - (Micah): With one caveat. Up until N8N and AI agents became mainstream this year, every bit of development known to man was logic based. If or then do this, do that, switch statements for loops, all the logic operators that we have within programming, that's out the window for AI agents. So one of the big training elements that we see as such a big issue is that people with a strong development background come in and they try to write the logic, they try to recreate the logic as if they were programming and code even outside of just visually in tools like N8N and Make.

0:17:32 - (Micah): When the reality is the agent can handle all of that. It can handle the logic if you build it correctly. So now we've got the. These two sides of the spectrum where it's like, are we relying on the agent too much or are we relying on the agent too little? This is where having somebody that knows what they're doing is of the utmost importance to get this stuff done correctly for your business.

0:17:56 - (Alane): Yeah. And you know, whenever I'm talking to companies or speaking engagement, I really focus on this as a piece of it because you have to train. And it is a different way for a developer to think. And they aren't coming out of the box knowing that even if they've worked in development for 20 years that they. So what we're looking for is an eagerness to learn that they're excited about the new technology and that they are adaptable.

0:18:26 - (Alane): Because if you can't adapt, then you, you're going to keep trying to do it the old way. And so when you're, if you're an organization looking to start building N8N workflows, then you need to be working with a technical person that is training themselves if you're trying to do it yourself. Because we're having, we're constantly training, we're constantly doing knowledge shares because this is what we do.

0:18:49 - (Alane): So we've got all kinds of use cases and examples and templates. Templates and just training video like we, when we hire a new person, they go through a whole training on this and then we do weekly training to continue cultivating this. Not thirst for knowledge because it is changing and we do need to stay up to date.

0:19:10 - (Micah): Absolutely, absolutely. I think that's probably the biggest takeaway from this episode that I would say, Alane, is check out N8N. Can you make stuff in N8N? Yes, you probably can. I'm still not going to pronounce that correctly as I'm trying to say it fast. N8N. But are you. Are you going to be paying extra? Is it performing the way you want? Are you going to get frustrated? Are you going to spend too much time piddling around with this stuff?

0:19:39 - (Micah): Like anything in business, if you have somebody that knows what they're doing, it's going to work faster. You need to stay focused on your business. Whether you're trying to do it yourself, there is a learning curve. It's worth it. Or if you want to stay focused on your business, hire a team that knows what they're doing.

0:19:58 - (Alane): And Micah and I have a new mastermind coming out where we are talking about these concepts, where we're helping owners stay on top of this technology. So if you're interested, shoot us a note.

0:20:10 - (Alane): Thanks for listening to this episode of Automate youe Agency. We hope you're inspired to take your.

0:20:15 - (Alane): Business to the next level.

0:20:16 - (Alane): Don't forget to subscribe on your favorite podcast platform and leave us a review. Your feedback helps us improve and reach more listeners. If you're looking for more resources, visit our website at biggestgoal.ai for free content and tools for automating your business. Join us next week as we dive into more ways to automate and scale your business. Bye for now.