AI automation
Content repurposing: 1 article → ~10 posts
In short
From a single blog article or video transcript, a good prompt turns out around ten platform-ready social posts – free with ChatGPT, pasted in and reviewed manually. It becomes fully automatic with Make.com plus AI and a scheduling tool like Buffer: every new article is then turned into posts and scheduled all by itself.
Free
- Copy the article or transcript.
- Paste it into ChatGPT with the prompt below.
- Review the output, tweak slightly, post manually.
- Optionally create matching graphics in Canva.
Here is my article: [TEXT]. Create 4 LinkedIn posts, 3 X posts and 3 Instagram captions from it. Keep my core messages, adapt tone and length to each platform, 3 fitting hashtags each.
Limits: No automatic posting, everything triggered manually.
Premium / Automated
- Create a scenario in Make, trigger: new blog post (RSS) or new row in Google Sheets.
- The AI module inserts the article and generates the posts (same prompt).
- Hand the result to Buffer or Publer and schedule it.
Here is my article: [TEXT]. Create 4 LinkedIn posts, 3 X posts and 3 Instagram captions from it. Keep my core messages, adapt tone and length to each platform, 3 fitting hashtags each. Output the result as JSON with the fields platform, text, hashtags.
Added value: Runs fully automatically with every new post, including scheduling.
Frequently asked questions
I only have a few articles – is it still worth it?
Yes, especially then. Repurposing squeezes a lot of visibility out of little source material: one good article yields posts for two to three weeks. You can even reuse the same content later, because social feeds are short-lived.
Won't all the generated posts look the same?
Only if the prompt is too generic. Specify tone and length per platform and have core messages rephrased instead of copied. A short manual polish per post (1–2 minutes) makes the difference.
Do I need coding skills for the automated variant?
No. Make.com works like a construction kit: the trigger (new blog post) and blocks (AI, Buffer) are clicked together. The first scenario takes some learning, but then runs permanently on its own.