I built an AI Content Agent that 3X my engagement in 30 Days (Full n8n Workflow)

Join me as chat I with The Boring Marketer as we demonstrate a complete n8n workflow automation that can save content creators 10-15 hours weekly by scraping top-performing content, generating new content ideas, and publishing to social. The system uses N8N to orchestrate multiple AI tools that research, write, and even create images for posts, with an optional human review step before publishing. Build an AI Content Automation in n8n: https://www.gregisenberg.com/ai-content-automation Timestamps: 00:00 - Intro 01:58 - Why use this Content AI Agent 03:05 - Demoing the n8n workflow 03:33 - Explanation workflow stages 04:52 - Appify for content scraping 05:57 - Researching Viral Content 06:59 - Content curation and Idea generation 11:47 - Overview of OpenRouter for accessing multiple LLMs 13:23 - Claude 3.7 Sonnet for content creation 14:23 - Prompting Tips 18:05 - Demo of the human review/posting process 22:33 - Get free workflow template Key Points: • The workflow uses N8N to automate content creation by scraping top-performing content from YouTube and X (Twitter) • The system processes this data through various LLMs (including Claude and OpenAI) to generate original content ideas • The workflow can automatically create and publish LinkedIn posts with minimal human intervention • Tools mentioned include Appify (for scraping), OpenRouter (for accessing multiple LLMs), and Claude 3.7 Sonnet (for writing) LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ BoringMarketing — Vibe Marketing for Sale: https://www.thevibemarketer.com Startup Empire - a membership for builders who want to build cash-flowing businesses https://www.startupempire.co FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND THE BORING MARKETER ON SOCIAL X/Twitter: https://x.com/boringmarketer LinkedIn: https://www.linkedin.com/in/jadickerson/

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:00Greg Isenberg?

  What if you can automate your marketing team with AI agents and just have content on autopilot? I know, it sounds like it's out of the future and I was skeptical too, but I had Mr. Vibe Marketing on the pod again to break down and share his entire N8N workflow with how to create content on autopilot that actually gets likes and comments. So, you know, in this episode, he gives away all the sauce. Then at the end, he actually gives away all his prompts and his template for doing it. God bless him. Like this video right now on YouTube.

• 0:40Greg Isenberg?

  Comment because this is an incredible episode where you'll learn how to become a vibe marketer and start automating and running your business on autopilot. Enjoy the episode.

• 1:02Greg Isenberg?

  We got the boring marketer, Mr. Vibe Marketing, back on the podcast. He's going to teach us a workflow today. What are we going to learn?

• 1:11Speaker 01

  Today, we're going to learn some basics of how to use N8N. We're going to find some data around a niche or a topic. We're going to feed that into some really smart LLMs and then we're going to produce some content and even automatically publish it on a platform. So you're going to see an end-to-end automation that hopefully is going to save you somewhere around 10 to 15 hours a week.

• 1:34Greg Isenberg?

  And is it really going to save me 10 to 15 hours a week? Or you're just saying that?

• 1:37Speaker 01

  It's saving me time. So in this use case, I'm going to show you a LinkedIn workflow. I spend most of my time on X and I actually hate creating content for LinkedIn. So, you know, as much as I can use AI to help me with that process, I try to do that. And we'll see, we'll see how it works.

• 1:56Greg Isenberg?

  Okay. If I actually use this workflow, what is the potential outcome of that? Like, why should I even care about this?

• 2:07Speaker 01

  Yeah, the outcome is that you're going to be able to test content angles, hooks, and topics way faster. So instead of like going, getting a subpar result just from opening up Claude or ChatGPT, this is going to get a lot of context, a lot of information, and it's going to create top performing content based off of that. It's even going to create an image for you and it's going to post automatically. Now, oftentimes, AI isn't quite there to just push a button and go end to end and post for you. I recommend doing that to test things out. I've heard you talk about this a little bit, too. Sometimes you'll throw out a tweet, you'll see if it catches, or you'll even use like maybe a secret account and then you'll delete it. So I'll do the same thing.

• 2:49Speaker 01

  I've been doing that actually for the past couple hours on LinkedIn. So you'll be able to test, you'll be able to refine, but I threw in a step here so that if you want, you can actually edit the content before you put it live as well.

• 3:04Greg Isenberg?

  All right, let's rock.

• 3:05Speaker 01

  All right, so I have this color coded here so that we can separate this out in stages. And again, I want to try to give people some actionable tips so that they can go and build a workflow. And I'm also going to give away the code for this workflow so that people can go and download it after they watch the show. They can upload it in the Innate Inn and have a really nice starting template to go and make their own. So let's dig right in. So basically, what I have here is a whole area that's going to analyze YouTube and X for different topics. So what I will do is open up a chat down at the bottom of the screen here.

• 3:50Speaker 01

  If you see that, and all I need to do actually is I just need to enter in a topic. So we're talking about innate in today. I post some content on that as well. So let's just put innate in. So it takes that keyword essentially. And now what it's doing is it's going over to YouTube and it's scraping the top videos on YouTube for my topic. So it's going out there and finding, you know, 20 to 30 videos that have a high degree of engagement. It's also doing the same thing on X. It's actually going to my account. It's looking for posts around workflow automation and AI. So right now it's, it's processing this.

• 4:32Speaker 01

  And what it's going to do after it finds YouTube videos and posts on X about innate in is it's going to actually watch all the videos and transcribe those for me. So I'm going to have all the content from the top YouTube videos around innate in. And then I'm going to have a number of topics from X as well.

• 4:52Greg Isenberg?

  And you're using Appify, right?

• 4:54Speaker 01

  I'm using Appify, yeah. So Appify is an awesome platform. Basically, if you want to go and scrape anything on the internet, you want to scrape Instagram, you want to scrape Amazon, you want to scrape TikTok, you want to scrape YouTube or X. They have like open sort of APIs that you can access with an Appify and plug them into your workflow to go and process that data. So that's what these HTTP requests are. Basically, they're just calling that Appify API. And in this one, I picked a YouTube one and have a couple of instructions in there. And then this one, I have one for X as well. Okay, so it's scraping right now. And then what it's going to do is it's going to

• 5:38Speaker 01

  put all this data together in essentially one big text block. So it's going to have a bunch of transcribed YouTube videos with the hooks, the titles, the content, and it's going to have some X posts as well. So it's going to bring all those together and merge them into basically one big block of text. So this is kind of my research phase. Here, I'm just kind of going out and I'm making sure I have enough context to go and feed my LLMs in the next step. So whatever niche, go ahead.

• 6:09Greg Isenberg?

  Which, by the way, this is the step that any savvy content creator is going to take when they're creating content. Right? They're going to see what else is out there. How are people positioning it? And where's my opportunity?

• 6:25Speaker 01

  Yeah, that's right. And, you know, to do this research manually, like you would have to spend like 24/7 online. If you want to unplug and actually have a life, it makes sense to have like robots and AI doing this stuff for you. So, yeah, I mean, like, instead of, you know, starting from scratch or whatever, go and find things that are already performing. And, you know, doing that for content, that's similar to doing things like trying to create a startup idea or something like that, too. You know, you want to find things that are already working so you can sort of shortcut that and take those learnings and make it your own. Okay, so after we get all of this data from YouTube and X, we're going to do another step here.

• 7:07Speaker 01

  So we've got this big block of text that includes all that video information and stuff. And now I have an agent. And this is a content idea generator. And it plugs into an OpenAI LLM. And what it's going to do is it's going to go and look at that big block of text. It's doing it right now. And it's going to scan through there and it's going to find fresh angles and content ideas for us that aren't just replicating what we researched. So I don't want to go and just like copy people's content. I just want to use that as inspiration and then come up with my own ideas. So that's what this step right here is doing.

• 7:46Greg Isenberg?

  And when you say come up with your own ideas, you mean AI coming up with the ideas for you?

• 7:50Speaker 01

  Yeah, that's right. So in here, that's right.

• 7:54Greg Isenberg?

  To be clear, you don't want to do anything. You want to set up the workflow.

• 7:58Speaker 01

  Yes.

• 7:59Greg Isenberg?

  And hang out on the beach.

• 8:00Speaker 01

  In true vibe marketer fashion. That's exactly what I'm doing. Yeah. So I have a prompt in here. I'm just saying like, using all of this content that I'm giving you, create a list of actionable content ideas that are strictly related to marketing. So if you remember, my, my keyword that I entered in the chat was in a in. Now that could include a lot of stuff. It could include things on like automating email replies or sales tasks or whatever. So I want to look at those, but then I want to extract ideas for marketing, for how I can kind of repurpose that and come up with some fresh angles. So here, um, you know, for a title, I want it to be short and clear.

• 8:40Speaker 01

  When it comes up with a content idea, I want to have a scroll stopping idea for my hook to pull people in. And then, um, I want it to suggest like the optimal format for this content. And then it needs to come up with an angle as well. So it needs to have like a unique point of view around how marketers can scale their efforts using AI and leveraging in a in for their workflows. Few other instructions. So avoid like too much technical jargon and technical topics. I'm kind of framing like who this content is for, uh, for the AI to come up with some ideas for my audience specifically.

• 9:18Speaker 01

  And, uh, you know, it's kind of going through and it's also looking at sort of my top performing X posts so that it can identify how I'm talking, uh, what sort of themes I'm using and stuff like that. So combining all this is going to give us a really powerful data set to go and create the right type of content for my audience.

• 9:36Greg Isenberg?

  And did you come up with this yourself?

• 9:39Speaker 01

  Yeah, like all these prompts and stuff. Yeah, yeah. So I'll come up with like, you know, an initial prompt and then I'll take it and I'll go over to like ChatGPT or Manus or Claude and I'll say, hey, improve this prompt. Here's what I want to achieve. And then I'll place in like some examples of content that I want this entire workflow to kind of create. So this goes back to like, you know, two, two things that I always talk about with AI. It's like know what questions to ask and know what good looks like. So if you have sort of a baseline prompt, you can go and use AI to improve your prompt, which is a step that I often use for all of these different types of agent nodes here. It did that. Looks like it came up with

• 10:20Speaker 01

  the ideas in the background. And then, once I have the ideas, you know, something that often resonates on social is having some specific like facts, trends and sources to back up the claims. I also don't want the model to completely like hallucinate and just come up with like random stuff that doesn't make any sense. So in this step, I have a research agent and I'm using perplexity here to go out and find some use cases that people have actually talked about with some real stats. I'm identifying some trends and insights, marketing use cases, ideas that are happening in the industry, stats, frameworks,

• 11:02Speaker 01

  or case studies that we can reference, popular opinions. So I'm just getting as much data as I can around these marketing angles with workflow automation and AI so that I can feed them into my content agent.

• 11:15Greg Isenberg?

  Makes sense. I'm just so excited to see what the output is going to be. Like, if this actually could do what it says it could do, then this is like a billion dollar workflow.

• 11:28Speaker 01

  Yeah. And there's also some startup like concepts we can talk around about this for how to like leverage it to create businesses. I think that this is like an interesting backbone to like, you know, power a consulting business or a freelancing business or really optimize, you know, agency operations or something like that as well. All right, so one note here on the research agent, another helpful tool to call out is OpenRouter. So oftentimes in a workflow, I try to use the best LLM or the best model for each specific task. So for research, I've got like perplexity right here. I've got OpenAI over here. I've got Claude over here later in the workflow that we'll look at.

• 12:12Speaker 01

  But OpenRouter allows me to access all of these models with one node. So if you open it up, you can see that I've got perplexity sonar selected here. But if I wanted to use any other model, you can just select them from this interface rather than going to Claude and getting an API key or perplexity and getting an API key. This makes it a lot easier to integrate these models when you actually build these things out.

• 12:41Greg Isenberg?

  And it's one price, right?

• 12:43Speaker 01

  Yeah, one price. Here it is. It's just, you know, one thing that you subscribe to and then you can access all the different models in a really easy to use way.

• 12:52Greg Isenberg?

  And just to be clear, we're not involved in Appify, OpenRouter, N8N. We're just showing you how to use the tools.

• 12:59Speaker 01

  Yep, yep. So after it sort of identifies the ideas and it does the research, it's going to sort of like merge those together again. And then it's going to feed it into a LinkedIn content agent. Now you can replicate this for basically any channel, but since I struggle with LinkedIn and I've been trying to figure it out, we're going to talk about LinkedIn today. So I have this agent node here again. And when I create content, I like to use Claude 3.7 Sonnet. You probably have used that as well.

• 13:33Greg Isenberg?

  The best writing right now as of recording this is the best writing LLM that exists.

• 13:39Speaker 01

  Exactly, exactly. And Claude, when you give it the context and the data, it's so powerful. Like if you arm it with enough context, it can come up with some pretty incredible things.

• 13:51Greg Isenberg?

  Yeah, I think the problem is people don't give it enough context and then they're like, this is garbage.

• 13:57Speaker 01

  Exactly, exactly. Yeah, most people, you know, they're opening up Claude or something like that. They're entering in a prompt and then it spits something out and they're like, "I don't like this." Well, you know, you're not going and scraping like all the top performing YouTube videos, tweets, analyzing your own account for brand voice and stuff like that, and then feeding it into the model. So you really need to, you know, power it with tons of data and tons of context to get the most out of it. So a few little prompting tips that I have in the LinkedIn post agent here. I'm including a brand voice. So, you know, AI uses a lot of fluff. It might still use a little bit of fluff at the end here, but I'm trying my best to give it some

• 14:37Speaker 01

  guardrails. Write with authentic expertise and direct communication. Be confident and straightforward. Don't be overly formal or academic. Speak directly to the reader. Avoid like corporate jargon and marketing speak, you know, a bunch of stuff like that. And I've just sort of like, through trial and error, you know, listed these different sort of brand guidelines out.

• 15:01Speaker 01

  And then a few other things. It's taking the research here. This is that JSON output, which is basically just a big block of text, all the context that I have created, and create a narrative-driven post that gives readers actionable insights and takeaways that will impact their business in positive ways. And then only use data if it's relevant. And don't pick topics around like AI marketing tools blindly. Like, make sure it's tied to the context of what we're talking about. All right. So another thing that AI always does, it always wants to add hashtags and emojis. So I make sure to like include the instructions like, "Don't use hashtags," you know, things like that in here. And then I give it a format for

• 15:43Speaker 01

  how I want the output to be. So title, content, things of that nature. And then if you look down at the bottom... I've got more instructions where I'm kind of framing the LLM here. So you're a LinkedIn content strategist and conversion copywriter. I always include something around like direct response or conversion copywriting when I'm using AI to create content. Otherwise, it creates sort of like kind of brand fluff type stuff. And I really want it to like lead people through a journey. I wanted to have a strong hook. I wanted to build interest, desire, give some actionable value, and then maybe a clear call to action at the end.

• 16:22Greg Isenberg?

  Good tip.

• 16:23Speaker 01

  Yep.

• 16:24Greg Isenberg?

  I would also say you didn't include it, but what are those dashes that AI always puts?

• 16:32Speaker 01

  M dashes.

• 16:33Greg Isenberg?

  M dashes. I would say like, don't have any M dashes.

• 16:38Speaker 01

  Yes, M dash overload on the internet right now. And like, when people see that, they know it's AI too.

• 16:43Greg Isenberg?

  Exactly. And that's a turn off, right?

• 16:46Speaker 01

  Big time. Yeah, yeah, yeah. Big time turn off. You know, you want to make it feel as authentic as possible. And sometimes AI does a pretty good job. Other times you need to get in there and edit a little bit, which we'll, we'll get to as well. So yeah, just some more instructions, like some writing guidelines and things like that. You know, often when I'm trying to create prompts for content, I'll like, look at some of your content, how you write. I'll, I'll feed in some stuff that I've created and some other creators that I really like. And, uh, you know, especially when it comes to like B to B content. You know, you need to be more like a creator. That's really kind of the future there. All right, so let's get out of that. And so it's created our LinkedIn post.

• 17:30Speaker 01

  And it's put it into a Google Doc here that you can see. Okay. And then we're working on creating an image for our posts as well. So this uses the OpenAI Image Gen model that I'm sure everyone has tested. And you can do crazy things like dynamic prompts depending on, you know, the topic of the post and stuff like that. But for our purposes, purposes today, I'm just prompting it to create a 3D image communicating an AI system or, you know, something like that to keep it simple. Okay, so right now, we're in the human in the loop step. So you know, a lot of people don't want to just straight up publish content directly from a model.

• 18:16Speaker 01

  You know, sometimes, like we talked about, we're not quite there yet. So you know, I work in Slack all the time. Most people that are in startups and marketing probably do. So what's going to happen at this stage is it's actually going to send me a link to the Google Doc in Slack. And I will just show you my Slack because I think this is a pretty cool step. All right. Yep, and there it is. I have a Slack channel set up here where I'm getting these triggers or these Google Docs from InnateN. So if you open one up, it's sent me a draft and I'm able to open up this completed post in a Google Doc. So let's just go through it a little bit. So it says, "Three ways to scale your marketing without hiring another team."

• 19:01Speaker 01

  Pretty decent, sounds actionable. And it's got kind of a personal narrative here. So I've spent years juggling marketing tasks that could have been automated. The breaking point when my team missed campaign deadlines because we're buried in repetitive work, that machines could handle. Then I discovered InnateN and it kind of goes through some different ways that you can use it for your marketing efforts. So here it's got automate your content distribution pipelines, which funny enough, that's what we're talking about right now. Sort of taking a topic and coming up with a completed final post that is ready to publish.

• 19:36Greg Isenberg?

  You know, you know what really works well on LinkedIn is photos of yourself. So I think that if I were to do this workflow, what I would do, and tell me if I can do this, create a Google Drive folder with, call it 50 pictures of myself in different poses. You can even use AI to create some of those.

• 20:00Greg Isenberg?

  And then just say, pick a random photo and attach it to the content. Is that possible?

• 20:05Speaker 01

  Yeah, I think it is. You know, when I was, when I was experimenting with this earlier, I was opening up my LinkedIn. And this is one that I actually published. If you look at Slack, you can see this approve button. And if I click that, this is going to post right over to, to my LinkedIn. So, um, you know, this is what happened when I did it earlier. It created this post and then the image generation created this image. Now, to your point, um, I think like a personal photo would resonate a lot more. It would feel more natural. It would feel less AI. So yeah, you could store those in a Google Drive and you could probably just have it randomly select from that folder and pair it up with the post here.

• 20:51Speaker 01

  So point is though, you know, you can do all of this research. You can get a highly relevant post. You can even create the image. You can have this fully formatted and in one button, uh, you can, you can publish directly to whatever social platform you want.

• 21:06Greg Isenberg?

  And the most important point is these are validated social posts. These are not social posts that you have no idea if they're going to get a like or a comment because it scraped YouTube, because it scraped X and it's got all that data. The chances of you creating content that's going to resonate with people is probably 10 or 50x.

• 21:30Speaker 01

  Yeah, absolutely. So remove the guess, the guesswork and yeah, use like real validation, uh, from things that have already performed and then just make it your own. You know, like you don't have to guess and you can test multiple of these to see which ones work if you want. The ones that you don't like, you can delete them. You can double down on the ones that get some good early data. And then you can even, you know, go and use it for other channels as well.

• 21:53Greg Isenberg?

  Anything else you wanted to tell folks?

• 21:56Speaker 01

  I thought this was kind of funny. So someone actually commented like such a solid example and, uh, you know, they liked the post and I was like, now the question is, did AI write it? So I think that this passed the Turing test. So pretty valuable, uh, little workflow here.

• 22:13Greg Isenberg?

  Very cool.

• 22:16Greg Isenberg?

  Dude, always a pleasure having you on the pod, spilling the sauce. You could have kept this to yourself, but you didn't. You came on here and shared it for free, so I appreciate that. I am going to include where to find The Boring Marketer on X and YouTube for more content like that. Anything else you want to plug?

• 22:35Speaker 01

  Yeah, one quick note. So, a lot of people need like a solid starter workflow that they can upload into innate and without having to go through the logic and trying to build all this out. So, I'm going to share a JSON file that has this complete workflow. You can download the file, you can upload it into innate and you can make it your own and start learning. Like, the best way to just get a handle on all this workflow stuff is playing around with it, tinkering, you know, seeing what kind of output you get and then trying to optimize it based on the data that you're getting. So, we'll share the link, but it's templates. dot the vibe marketer.com slash Greg and people just enter their email. We'll send that over to you and you can get started like right away.

• 23:20Greg Isenberg?

  And it's free?

• 23:21Speaker 01

  It's totally free. We're just going to give it away. We're going to give the sauce.

• 23:24Greg Isenberg?

  All right. I appreciate, I appreciate you.

• 23:27Speaker 01

  Of course. Thanks for having me, Greg.

• 23:28Greg Isenberg?

  All right. Later.

• 23:30Speaker 01

  See ya.