how to automate social media posts with make and chatgpt - Make and ChatGPT social media automation workflow

Proven Guide: How to Automate Social Media Posts With Make and ChatGPT (2026)

I wasted six hours manually copy-pasting tweets last month.

Last November, I spent an entire Sunday afternoon drafting, formatting, and scheduling posts across three different platforms. I was essentially acting as my own highly inefficient intern. That evening, I decided to figure out exactly how to automate social media posts with make and chatgpt once and for all. I wanted a system where I could type a raw thought into my phone, and an AI would polish it and post it automatically.

According to recent data published by Statista, the average internet user spends nearly two and a half hours daily on social platforms. As a solo creator, I simply cannot afford to burn that time doing manual data entry. I had previously tested several of the best social media management tools on the market. They were fine, but I wanted something totally custom and completely hands-off.

The Architecture: What You Need Before Building

Before we start connecting modules, you need to understand the basic architecture of this system. We are going to build a pipeline that takes a messy idea, turns it into professional copy, and sends it to the internet. You do not need to be a developer to do this. I am certainly not one.

First, you need a Make.com account. Make is the visual engine that connects all these different apps together. They offer a generous free tier, but the Core plan starts at $10.59 per month. I highly recommend upgrading to the Core tier. The free version restricts how often the automation can check for new ideas, which ruins the magic of real-time posting.

Second, you need an OpenAI API developer account. This is entirely separate from a $20/month ChatGPT Plus subscription. You will generate a secret API key and pay fractions of a penny per word generated. In my experience, running this workflow for a whole month rarely costs me more than $1.50.

Finally, you need a database to catch your raw brain dumps. I personally use Google Sheets because I can drop an icon on my phone’s home screen for instant access. com/best-ai-tools-for-google-sheets/”>best AI tools for Google Sheets, but keeping the spreadsheet dumb and letting Make handle the AI is much more reliable.

com/sites/bernardmarr/2023/10/24/the-future-of-productivity-how-ai-is-automating-the-mundane/” target=”_blank” rel=”noopener noreferrer”>Forbes highlight how intelligent automation saves small teams roughly 40 hours a month. I can confidently say this specific setup saves me at least ten hours every single week.

Let’s break down the exact five modules you need to drag onto your Make canvas.

1. The Data Source Trigger (Google Sheets)

STEP 1

Best for: Catching your raw ideas the moment you type them.

Pricing: Free (Included with any Google Workspace account).

When I first built this, I tried using a scheduled timer to check my spreadsheet once a day. It was terrible. Sometimes I wanted a thought posted immediately, and waiting for the daily sync drove me crazy. I eventually switched the trigger module to “Watch Rows”.

Now, the moment I type my rough idea into Column B and change Column A to “Ready”, Make instantly grabs it. Setting up the spreadsheet correctly is crucial. I use four columns: Status, Raw Idea, Platform, and Date.

Who should NOT use this: Creators who prefer complex relational databases like Notion over simple grid layouts.

Friction Point: Google’s OAuth connection inside Make occasionally drops its token. I have to re-authenticate my Google account every three months or the automation silently fails.

Pros
  • Instant trigger capability in Make
  • Accessible via native mobile app
  • Zero cost to scale up storage
Cons
  • Prone to accidental manual edits
  • Authentication drops occasionally
  • Poor handling of rich text formatting

2. The AI Engine (OpenAI Module)

STEP 2

Best for: Rewriting your messy notes into engaging, platform-specific copy.

Pricing: Pay-as-you-go (Approximately $0.002 per 1,000 tokens using gpt-4o-mini).

I spent an entire morning fighting with the output from this module. Early on, ChatGPT kept wrapping my posts in quotation marks and adding annoying hashtags like #MotivationMonday. It looked incredibly robotic. The secret is prompt engineering right inside Make. I use the “Create a Chat Completion” module and set the system prompt to: “You are an expert copywriter.

Rewrite the following raw notes into a punchy post. Do not use hashtags. Do not use emojis. ” That single change fixed everything.

Who should NOT use this: Anyone who refuses to learn basic API prompt writing. You cannot just click a button and hope it sounds like you.

Friction Point: The OpenAI developer dashboard now requires you to pre-load a minimum of $5 onto your account before it will even let Make authenticate the API key.

Pros
  • Dirt cheap token pricing
  • gpt-4o-mini is blazing fast
  • Highly customizable tone control
Cons
  • Requires upfront API credit balance
  • Occasional hallucinated formatting
  • Steep initial learning curve for API keys

3. The Traffic Cop (Make Router)

STEP 3

Best for: Splitting the automation path based on which platform you are targeting.

Pricing: Included in all Make plans (Starts at $10.59/mo for Core).

Before adding the Router module, I was sending the exact same block of text to both Twitter and LinkedIn. It was a disaster. Twitter posts would fail because they exceeded character limits, and LinkedIn posts looked entirely too short. I added a Router to split the path.

I right-clicked the connecting line and set up a filter: “If Column C says LinkedIn, go top path. com/make-vs-zapier/”>Make vs Zapier testing. It is far more intuitive.

Who should NOT use this: Users who are only looking to automate a single social media profile and do not need complex branching logic.

Friction Point: Dragging and arranging the connection bubbles between multiple paths can be incredibly finicky if you are working on a small laptop screen.

Pros
  • Visual mapping is easy to read
  • Unlimited branching possibilities
  • Built-in error fallback routes
Cons
  • UI gets cluttered with 5+ routes
  • Filter logic requires exact text matches
  • Consumes more operations on your plan

4. The Professional Outlet (LinkedIn API)

STEP 4

Best for: Pushing your expanded, professional ChatGPT copy directly to your feed.

Pricing: Free to use with a standard LinkedIn account.

Getting the LinkedIn module to work seamlessly was surprisingly frustrating at first. ” I wanted to map an image URL from my spreadsheet, but the API kept rejecting my Google Drive links. I eventually realized you must format the image URL as a direct download link, not a viewing link.

Once I fixed that mapping issue, the generated posts started landing perfectly on my timeline.

Who should NOT use this: Creators whose primary audience relies exclusively on visual-first platforms like TikTok or Instagram Reels.

Friction Point: LinkedIn API security tokens expire automatically after 60 days. You will get a sudden error message and have to manually click “Reauthorize” in Make every two months.

Pros
  • Native formatting support
  • No algorithm penalty for API posting
  • Can target company or personal pages
Cons
  • Strict 60-day token expiration
  • Media attachments are tricky to map
  • No support for PDF carousel uploads

5. The Micro-Blogger (Twitter/X Module)

STEP 5

Best for: Firing off short, punchy insights without opening the distracting X app.

Pricing: Free tier available (X Basic API costs $100/mo for heavy volume).

Honestly, I almost abandoned this final step. When Twitter changed their API access rules last year, my original Make connection completely broke for three days. To fix it, you have to ensure you are selecting the “Create a Tweet (v2)” module in Make, not the legacy version.

Once I swapped that out and mapped the OpenAI output text into the content field, it worked flawlessly. I use a specific ChatGPT prompt on this route to ensure the text never exceeds 280 characters.

Who should NOT use this: Casual users unwilling to navigate the highly restrictive and confusing X Developer Portal to get their keys.

Friction Point: Automating threads is nearly impossible on the free tier. You are strictly limited to single-post text and image outputs unless you pay $100 a month.

Pros
  • Instant publication speed
  • Excellent for high-volume posting
  • Supports basic media attachments
Cons
  • Developer portal is a nightmare
  • Thread automation is paywalled
  • API limits are incredibly strict

Component Breakdown 📊

If you are confused about what each piece of this stack does, I put together a quick summary table. Each component handles a very specific job in the pipeline.

ComponentRole in WorkflowStarting PriceFree PlanRating
Make.comThe connecting brain$10.59/moYes (1,000 ops)4.9/5 ⭐
Google SheetsRaw idea storageFreeYes (15GB limit)4.8/5 ⭐
OpenAI APICopywriting engine$5 minimumNo4.7/5 ⭐
LinkedIn APIProfessional postingFreeYes4.2/5 ⭐
X (Twitter) APIMicro-blog posting$100/mo (Basic)Yes (Strict limit)3.5/5 ⭐

Frequently Asked Questions

How to automate social media posts with make and chatgpt without paying a fortune?

The trick is to use the correct API models. Do not use GPT-4 for simple social media rewriting. Use gpt-4o-mini instead, which costs pennies per thousand tokens. Combined with Make’s $10.59 per month Core plan, the entire system should run for under $13 a month.

Do social platforms penalize content posted via an API?

In my testing, I have not seen any measurable penalty on LinkedIn or Twitter when using their official APIs. The algorithm cares about engagement and dwell time, not the scheduling tool you used. If your AI-generated copy is boring, it will fail regardless of how it was posted.

What happens if the AI generates a terrible post?

This happens occasionally. To prevent bad posts from going live, you can add an approval step. Instead of routing directly to LinkedIn, route the output to a private Slack channel or a Drafts folder in Google Sheets. You can manually approve it before it publishes.

Is Zapier a better choice for this workflow?

Not for this specific use case. If you are wondering what is Zapier good for, it excels at simple two-step triggers. But for routing logic where one spreadsheet row needs to be split into custom formats for three different social networks, Make is significantly cheaper and visually easier to manage.

My Final Verdict on How to Automate Social Media Posts With Make and ChatGPT 🥇

Honestly, building this system was one of the highest-ROI tasks I completed this year. Learning exactly how to automate social media posts with make and chatgpt completely removed the friction of content creation for my one-person business. I no longer dread formatting text for different character limits. I just type raw thoughts into my phone, and the pipeline handles the rest.

If you are a solo freelancer or founder, this setup is a no-brainer. The Make Core plan combined with OpenAI’s API is practically an unpaid intern. Just remember to lock down your ChatGPT system prompts so you do not accidentally publish an essay loaded with robot emojis.

Get Smarter Tools Author

Written by Giorgi Sakandelidze

I independently test and review software tools to help fellow solopreneurs find the exact right solution. My hands-on testing process covers real-world freelance use cases, pricing accuracy, and genuine limitations — not recycled vendor marketing copy.

Learn about my review methodology →

🕒 Last updated: 2026-06-02 — We update our reviews whenever tools change pricing or features.

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