How to Build an AI Agent That Writes Your LinkedIn Posts

TLDR: Posting on LinkedIn usually means hours of research, drafting, and editing. You can replace that with an AI agent built in n8n, Make.com, or Zapier. The agent scrapes YouTube videos and X posts, transcribes them, validates ideas with Perplexity, and drafts a post in your style with Claude or GPT. It then generates an image, sends the draft to MS Office or Google Docs for approval, and publishes with one click. The result is a researched, voice-authentic LinkedIn post produced in minutes instead of 10–15 hours a week. **Disclaimer: This post is naturally written**

Most professionals trying to stay visible on LinkedIn run into the same wall: content research eats their week. Hours vanish into YouTube, Twitter, and endless drafts that never sound quite right. With platforms like n8n, Make.com, or Zapier:  simply tools that link apps together without coding, you can build an AI agent to handle this. Think of the agent as a content brain you set up once. You define its job, give it the right tools, and it runs the steps automatically.

How it Works

So you type in a topic like “tourism marketing tactics.” The agent scrapes the top YouTube videos and relevant X posts, then transcribes the videos into text. It compiles everything into one dataset: raw context that would have taken you hours to collect. Next, it feeds that material into a writing model like Claude or GPT, alongside samples of your own posts and tweets. Because it knows your voice, the draft it produces reads like you, not the rubbish fluff you see on Linkedin currently.

Before it finishes, the agent validates ideas with Perplexity via OpenRouter to pull facts and examples. It then uses an OpenAI image model to create a simple visual. The result: post plus image and it lands in MS Teams, or Google Docs, for your approval. If it looks good, you click once and it’s published to LinkedIn.

Topic in, researched post out.

How to test this manually

Before wiring it into an agent, try the process manually:

1. Collect material. Pick five to ten YouTube videos on your topic. Use a transcript tool to copy the text.
   
2. Add your voice. Export your last 20 LinkedIn posts and 10 tweets into the same file. This is your “voice pack.”
   
3. Generate a draft. Paste both into Claude or GPT with the instruction: “Write a LinkedIn post in my style using this material. Include relevant statistics.”
   
4. Check the facts. Run claims through Perplexity via OpenRouter. Replace anything shaky.
   
5. Create a visual. Prompt an OpenAI image model: “Minimal LinkedIn graphic, square, headline: ‘Tourism marketing tips that work in 2025’, clean, no stock photos.”
   
6. Review once. Drop the draft and image into Slack, MS Teams, or Google Docs. If it fits, publish manually.
   

That’s the workflow: scrape, transcribe, validate, draft, image, review, publish.

Once you see the output, you’ll understand why automating the same steps saves ten to fifteen hours a week.

Why context REALLY matters

Most people open ChatGPT, type “Write me a LinkedIn post,” and get generic filler. The problem isn’t the AI:  it’s the lack of context.

This process fixes that because the model is fed:

Transcripts from 30 videos,
Social posts already performing on X,
Your own writing samples (emails, recordings).
That’s why the draft sounds like you and stands out from the total rubbish on Linkedin.

To make it work, you need to give the AI your voice pack your last 20 LinkedIn posts, your best tweets, even transcripts and emails. Without that, you’ll get bland text. 

How to build the agent

Now you know how to do it manually - build an AI agent with a no-code tool.

• Trigger. Start when you type a topic keyword.
  
• Research. Apify scrapes YouTube and X, then transcribes the videos.
  
• Idea generation. Claude or GPT analyses the dataset for patterns and hooks.
  
• Validation. Perplexity via OpenRouter checks the ideas and pulls in supporting stats.
  
• Drafting. Claude 3.7 Sonnet writes a LinkedIn-ready post in your style.
  
• Image. An OpenAI model creates a simple graphic.
  
• Review. The draft and image arrive in Slack, MS Teams, or Google Docs.
  
• Publish. One click pushes it to LinkedIn.
  
• You still approve the post, but everything else runs alone.

 Here's how it works. Say you want a post on “tourism marketing tactics.”

1. The agent collects 20–30 top YouTube videos, transcribes them, and adds recent X posts. Claude reviews the combined text and finds angles like local destination campaigns, video-first promotion, or budget-saving tactics for small operators.
2. Perplexity validates those angles with stats and examples. Claude then drafts the post in your style, weaving in the research and your tone. An OpenAI model creates a square graphic with a headline like “Tourism marketing tips that still work in 2025.”
3. The draft and image arrive in MS Teams or Drive for your sign-off. One click later, the post is live.

From your input to published content, the research, validation, drafting, and design were handled by the agent.

What you get back

Most of us waste a day or more every week researching and writing LinkedIn content. This agent strips that out. You keep control at the approval step. Everything else data collection, validation, writing, image creation, publishing is automated.

And it doesn’t take coding to build. With our No Code / Low Code solutions, we connect the parts for you: Claude or GPT for drafting, Perplexity for validation, OpenAI or ImageFX for images, Teams for review, and LinkedIn for publishing. The result is a ready-to-run content AI agent that turns hours of grind into a five minute check.

FAQ

Q: Do I need to code?
A: No. Tools like n8n, Make.com, and Zapier are drag-and-drop. You’re connecting steps, not writing code.

Q: Why not just use ChatGPT?
A: Because prompts alone give you generic fluff. This agent works because it has context: video transcripts, live social posts, your voice pack, and validated stats.

Q: How much time does it really save?
A: Once it’s running, most people gain back ten to fifteen hours a week.

Q: Is this only for marketers?
A: No. Anyone who needs a credible and simple content creation experience - consultants, SME owners, public sector leads can use it.

Q: Where does approval fit?
A: The draft always lands in Slack, MS Teams, or Google Docs first. You review before anything publishes.