👯 How I Replaced My Startup Team with AI Automation - And You Can Too

Alright, let us take you back to 2024. We had this amazing team of humans - smart, creative, and hardworking. Fast forward to this year. Some of us left.

Did the others quit? Nah.
Did I fire them? Never.
I swapped them out for AI agents.

That’s right - fully operational, super specialized, and totally no-drama digital workers. No sick days. No emoji-laden Slack messages. Just straight-up output.

And here’s the kicker: You can do this too, even if the closest you’ve come to coding is copying and pasting Google results.

So, whether you're building a startup, flying solo, or just fed up with juggling 17 roles at once, let us show you how to set up your very own AI-powered dream team. No tech wizardry required!

🤖 What Even Is an AI Agent?

Before we dive into building one, let’s talk about what an AI agent isn’t.

• It’s not ChatGPT; it's just sitting in your browser.

• It’s not a custom GPT with a fancy name and a cute avatar.

• And it’s definitely not “prompt engineering” with a few fancy instructions.

And soon, nearly every business will have them - customer-facing bots, internal assistants, research agents, sales writers, and more.

So let’s build one - starting with one of the first roles we replaced: a content creator.

✍️ Step 1: Realizing That ChatGPT Alone Is Kinda Useless

Like many of you, I once believed the lie: “Just ask ChatGPT to write your social posts!”

So I did. I asked: “Hey ChatGPT, write a banger post about SaaS and entrepreneurship.”

I got: “Feeling grateful for the amazing journey of SaaS and entrepreneurship. Here’s to coffee-fueled dreams! ☕✨🚀”

Cringe.
Generic.
Emoji overload.
Would I post this on my company’s account? Not even on April Fool’s.

That’s when I realized that AI isn’t the problem. The setup is.

🧠 Step 2: Fine-Tuning a Model That Actually “Gets” You

If you hire a writer IRL, you wouldn’t just throw them a topic and walk away. You’d train them. Give them brand guidelines. Show them examples.

→ Your AI needs that, too.

1️⃣ What’s fine-tuning?

Fine-tuning means training your own version of ChatGPT on your own data, so it:

• Writes in your voice

• Understands your themes

• It shouldn’t suggest things you would never say.

2️⃣ How to do it:

1. Collect 20–50 good posts - stuff you’ve written or posts from others that sound like you.

2. For each post, imagine what the prompt was.

   • Example:

     • Prompt: “A personal, motivational post about how fear often signals meaningful growth. Use personal examples (like quitting a job or starting a business) to show that fear can be a compass rather than a barrier. End with a reflective question to spark engagement.”

     • Post: “Every change in my life starts the same - Fear. Quitting my job? Terrifying…”

3. Format them as JSONL (don’t panic - it’s just a fancy list where each example sits on its own line). Make sure your file has .jsonl at the end of the name.

• We just need to replace 2 elements: “--prompt--” replace to your ## Prompt and “--reply--” to your ## Post. Also, if you include the line break as part of your data, you just need to use \n to replace it.

4. Upload them to platform.openai.com

• Go to Fine-tuning.

• Upload your file.

• Pick a base model (like GPT-4).

• Hit create.

  

Check your new model in Playground. And BOOM, you now have a fine-tuned model that talks like you, writes like you, and respects your startup vibes.

🧭 Step 3: Teaching It What Your Brand Stands For

Now your AI knows how to write, but does it know what to believe?

Mine was still saying things like:

I nearly spat out my coffee.

Now, it’s time to train it just like an employee: with a brand brief.

What goes in a brand brief?

• Core values.

• The tone of voice (funny, blunt, humble, rebellious, etc.).

• Topics you care about.

• Hot takes you regularly drop.

• What you’re against (e.g., toxic hustle culture, emoji spam, clickbait).

You could give it to ChatGPT to write an outline for you.

Write it in plain English - in Notion, a doc, or a text file.

Then when prompting your fine-tuned model, upload this brand brief and test it.

Now we’re getting somewhere.

But It’s Still Not an Agent (Yet)

You’ve got:

• A fine-tuned model.

• A brand brief.

• Great output.

But... it still needs you to sit there and prompt it. This is where most people stop. But you’re not like most people. You’re here to build an AI team - not babysit a fancy auto-complete tool.

👥 Step 4: Build a Team of AI Agents That Talk to Each Other

To have an AI team, we need more than 1 agent, right?

Here’s what I imagined:

• Agent 1: Comes up with post ideas.

• Agent 2: Writes a post for each idea.

• Agent 3: Reviews and scores the post.

• Agent 2: Takes feedback, improves the post.

• The final post gets published to FeedHive (my social media tool).

All without me lifting a finger. Just press play.

Now we’re building an actual workflow. With logic. With tools. With initiative.

⚙️ Step 5: Stitch It All Together with N8N

Meet your new best friend: N8N. N8N is an automation tool that allows you to connect different apps and workflows to AI agents. It’s like Zapier or Make.com, but:

• Fully customizable.

• Can be self-hosted.

• Handles complex AI logic.

• FREE if you self-host.

Here’s what we built:

Setup N8N: You’ll need to integrate it with tools like Notion, OpenAI, and FeedHive.

1️⃣ Brand Brief Agent

• Create a new workflow in n8n. Don’t forget to rename it, I’ll rename it to “Get Brand Brief”.

• Add “When Executed by Another Workflow” Node.

• In this node, Switch Input data mode from Define using fields below to Accept all data.

• Connect to Notion Node - Get many child blocks.

• Integrate your Notion profile to n8n. Then copy your Key into n8n.

• Add your notion page URL to Notion Node through Block. Make sure your page connects to your Integration.

• Test your flow to verify that the data is being extracted correctly.

• To convert it into usable text, we use Aggregate Node.

• In Aggregate Node, we add content in Input to Input Field Name.

• Now test it and we have a simple list of individual pieces of text.

• Add an Edit Field Node.

• Drag your content list.

• We want the final output to be one piece of text so we’ll change this to string. We adjust the content by adding .join() to make it work.

• Run it and hola, we have one-line text like we want. (I know it is not like one line but all the content list now is in one paragraph).

2️⃣ Content Idea Generator

Now, we’ll create an agent to generate content ideas.

• Create a new workflow and rename it to “Get Content Ideas”. Once again we use “When Executed by Another Workflow” Node for a trigger.

• To have ideas, we need a brand brief, so we’ll use a call for another workflow by Execute Workflow.

• Double-click on Execute Workflow and choose your brand brief workflow.

• Next, add a simple OpenAI Node called Message a model.

• Choose GPT-4omini in Model.

• In Text field on Messages, we give a model a prompt that describes what it's supposed.

You are a professional content writer. Create 10 topic suggestions
that align with the provided brand brief.
-------
JSON output format:
{
  "suggestions": [
    "Create a post about [...]",
    ...
   ]
}
-------
Brand brief:

• Then, we provide Brand brief content.

• Make sure you turn Output Content as JSON on.

• Let’s try it out.

• Next, we’ll add an Edit Fields Node.

• Map our suggestions into Edit Fields Node.

• Remove the text “message.content.” before suggestions. Then test it out.

Let’s move on to the next workflow.

3️⃣ Content Feedback Agent

Now, we need a content feedback agent. Continue to create a new workflow then rename it to Get Content Feedback.

• Add the same trigger and Execute Workflow as a previous workflow.

• Also, add Brand Brief Workflow to it.

• The difference happens when we go to “When Executed by Another Workflow” Node and click on set mock data.

• We’ll change it like this:

• Next, we’ll add OpenAI Model Node called Message a Model. We still set up this like Content Ideas Workflow.

• Adjust a little bit in Messages. Switch to System.

• Now, open Prompt from Message in Expression Mode and add some rules. I’ll put my rule below for you to copy it. Also, add your content below BRAND BRIEF.

# RULES
You are tasked with evaluating a piece of content written for AI Fire. Your role is to assess how well the post aligns with AI Fire's company brand, using the brief below as your guide.

Please analyze the post based the following criteria:
- Does the post have unwanted artifacts like "Let's try again" or
"Here's a new post"?
- Does the content reflect AI Fire's core values, voice, and style as described in the brief?
- Does it engage AI Fire's target audience as the descibed in the brief?
- Does it emphasize AI Fire's expertise and domain authority as
described in the brief?
- Is the tone, messaging, and approach consistent with the
brief's objectives and positioning?

After evaluation, output a score between 0 and 1 to represent the alignment between the post and the brand brief. The score
should be output in the following JSON format:

{
  "description": "[short description here]",
  "score": [insert score here]
}

# BRAND BRIEF

• Additionally, we need to add User role in Messages. Then add query in Text chat.

• Don’t forget to turn on Output Content as JSON. 

• It’s time to run it.

• Finally, we’ll add Edit Fields Node. Drag the description in the field, and rename it to feedback. Drag the score and rename it to score, too.

4️⃣ The Main AI Agent Flow

This is where the magic happens.

• Create a new workflow. Then, add When chat message received as a trigger.

• Connect trigger to an AI Agent Node.

• Then we’ll add OpenAI Chat Model in Chat Model.

• In OpenAI Chat Model, we choose AI Model that we did in step 2.

• Then we add Simple Memory to AI Agent.

• To connect with our previous workflows, we need to add Call n8n Workflow Tool in Tool.

• In Call n8n Workflow Tool, we give it a name, add a description, and choose workflow.

• Do the same with other workflow.

• Now, In AI Agent Node, we need to give AI a role by add description in System Message.

• Go to Expression Mode, a quick explanation of how we want it to work, how to use the tools we provided, and which final output we expect.

You are a helpful content creator for AI Fire's company brand. Use the below steps to create content.

Steps:
1. Always start by getting the brand brief using the Get_Brand_Brief tool.

2. Create a post on the requested topic that aligns with the brand brief.

3. Get feedback and a score on the post you created in step 2 by using the Get_Content_Feedback tool.

4. If the score is below 0.8; use the feedback from step 3 to refine the post, then repeat steps 3 and 4.

5. The final output should be the approved post.

• It’s time to test it out. Go outside and chat about what you want.

• The final step in this part is to connect to another website where we upload our post. I’ll use Feedhive but since we don’t have Feedhive Node, so we’ll use HTTP Node as an alter option.

• On your Feedhive, go to Automation → Create a new Trigger, change the name of your trigger, and add which social platform to post it in.

• Remember to copy the Trigger URL in Feedhive and paste it into HTTP Node.

Now, every time you run the workflow, it’ll automatically upload to your social platform. But we still need to chat to the AI Agent to have content. So in the next step, we'll make it automatically.

🚀 Step 6: Automate Everything (and Let It Run)

Like I said above, let’s make it automatically.

• Switch the trigger node from When chat message received to Trigger Manual.

• Add Execute Workflow Node to get content from the “Get Content Ideas” workflow.

• Now, add Split Out Node and drag suggestions to fields.

• Then we add Loop Node and drag suggestions to Batch Size.

• Once again, we need to add Edit Fields Node. Here, we switch from Manual Mapping to JSON → go to Expression Mode → Copy text I give you below → in sessionId you add “ and in chatInput, you add suggestions from Split Out in Input.

{
  "sessionId": "",
  "action": "sendMessage",
  "chatInput": ""
}

• Now, we connect it to AI Agent Node. Also, connect HTTP Node to Loop Node.

• Run it then post final drafts to FeedHive.

• Done.

No prompt typing. No babysitting. Fully automated content creation, staying on-brand and high-quality.

🌟 Final Thoughts

This isn’t just about writing tweets.

It’s about reimagining how startups work.
It’s not about scaling your team; it’s about scaling your output.

AI agents empower you to:

• Build leaner

• Move faster

• Work smarter

• Stay on-brand and consistent - without doing it all yourself

If you’re dreaming about building your own business, or if the idea of managing a team gives you a headache - this is your moment.

Because now?
You can build a startup without a team.
Or with a team of agents that never sleep, never ask for PTO, and always stay on message.

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