Scan time: 2-3 min / Read time: 5-7 min
Hey rebel solopreneurs 🦸♀️🦸♂️
Most content creators manually rewrite the same post for different platforms.
Smart ones turn one LinkedIn post into Twitter, newsletter, and audience-specific versions in 60 seconds.
⛳️ Why this works
Before you cross-post, you need versions. Different tones for different platforms.
Without them? You copy-paste the same LinkedIn post to Twitter. Same formal tone. Same 3-paragraph structure. Feels off. Gets ignored.
Manual rewriting? 20-30 minutes per platform. And you're still guessing which tone works where.
Here's the thing…
Each platform is like a different radio station.
LinkedIn wants professional and polished. Twitter wants punchy and sarcastic. Your newsletter wants storytelling and depth. Facebook wants casual and relatable.
You're stuck broadcasting the same LinkedIn tone everywhere. But your Twitter audience tunes out formal language. Your newsletter readers skip copy-pasted social posts.
If you only write in one voice, you're missing 80% of your audience across platforms.
The Post Multiplier fixes this. It's one master prompt that instantly shows you how your post should sound on every platform.
Tones. Authors. Goals. Demographics.
You paste your LinkedIn post once. AI generates 28 variations. You scan the tables. You grab the punchy version for Twitter. The storytelling version for your newsletter. The ESL-friendly version for global followers.
You turn one post into 28 platform-optimized versions. Bingo.
Turns out, adapting beats copy-pasting every time.
Let's see how Emma figured this out:
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Emma is a productivity coach. Posts on LinkedIn 4 times a week.
But here's her problem.
After 7 months and 112 LinkedIn posts, Emma wanted to expand to Twitter and her newsletter. Same content. Different platforms.
She'd write a LinkedIn post. Professional. 3 paragraphs. Polished.
Then copy-paste it to Twitter. Read it. Felt way too formal for Twitter.
Tried to make it punchier. Rewrote it. Lost the key message.
Tried again. Made it sarcastic. Now it didn't sound like her.
Should she keep it professional? Or go casual? Or add humor?
45 minutes rewriting one post for Twitter. Still didn't feel right.
Then the newsletter version. Needed more depth. More storytelling. Another 30 minutes rewriting.
2 hours total. One LinkedIn post adapted for 2 other platforms. Exhausting.
Emma was tired of this. She needed her LinkedIn posts to work everywhere. Without spending 2 hours per post manually adapting them.
Then Emma found something. A framework from creators running multi-platform empires.
A system called "The Post Multiplier."
It explained exactly why manual cross-platform adaptation was eating her time. And how to see 28 platform-ready versions of any post in 60 seconds.
Emma decided to follow these steps:
Step 1: See her LinkedIn post in 6 different tones (pick the punchy one for Twitter) Step 2: See it written by 7 different authors (find the storytelling voice for newsletter) Step 3: See it rewritten for 6 different goals (test action-oriented vs persuasive) Step 4: See it adapted for 6 different demographics (create ESL-friendly version)
🎯 Step 1: Emma saw her LinkedIn post in 6 different tones
Emma opened ChatGPT/Claude (her AI sidekick).
She had a solid LinkedIn post about productivity. Professional. Polished. 280 words.
But she wanted to post it on Twitter too. Twitter needed punch. Sarcasm. Edge.
But wait. Manually rewriting 280 words into Twitter voice? That's 30 minutes minimum. And she'd probably lose the core message trying to force a different tone.
She needed to see what this post would look like in multiple tones. Then pick the best one for Twitter.
Here's what she tried:
The tone variation table prompt:
You are my personal "post multiplier."
I am going to give you a social media post. Then you are going to rewrite it in 6 different "tones."
- More formal
- More serious
- More sarcastic
- More optimistic
- More pessimistic
- More lighthearted
Here are the steps:
1. Rewrite the post in each tone
2. Store the output in a table
Here is the table output:
- Column headers: tone, rewritten post
- Rows: each of the tones I listed
- The first row should be the original post
- The "tone" for that one should be "Original post"
---
INPUT:
[Paste your LinkedIn post, tweet, or social content here]
The AI sidekick returned a table with 7 rows.
Original post at the top. Then 6 tone variations:
Formal version was even more professional (too stiff for Twitter)
Sarcastic version had bite and edge (perfect for Twitter)
Optimistic version emphasized possibility (good for motivational content)
Pessimistic version highlighted risks
Lighthearted version felt playful
Serious version carried weight
Emma scanned the table. The sarcastic version. That's the Twitter version. Punchy. Direct. Different enough from LinkedIn.
Generation time: 45 seconds. Not bad.
Completion moment: Emma had her Twitter-ready version. Same core message. Perfect platform fit.
✍️ Step 2: Emma saw her post written by 7 different authors
Emma had the Twitter version (sarcastic, punchy). Now she needed the newsletter version.
Her newsletter readers wanted depth. Storytelling. More narrative flow than a quick social post.
She wanted to see how different authors would write this same post. Seth Godin for simple frameworks. Malcolm Gladwell for narrative depth. Ryan Holiday for stoic clarity.
But she couldn't channel 7 different writing voices on her own. Each author had their own secret sauce. Rhythm. Word choice. Narrative style.
Should she copy Seth Godin's simple frameworks? Or Malcolm Gladwell's storytelling? Or Hemingway's brutal directness?
She had no clue which would work for her newsletter audience.
The problem? Emma couldn't see how each author would actually write it. Just guessing wasn't enough.
But if she could see all 7 versions side by side, she could spot which style fit her newsletter.
Here's what worked:
The author voice table prompt:
You are my personal "post multiplier."
I am going to give you a social media post. Then you are going to rewrite it in 7 different "authors"
1. Gary Vaynerchuk
2. Seth Godin
3. Tim Ferriss
4. Malcolm Gladwell
5. James Clear
6. Ryan Holiday
7. Ernest Hemingway
Here are the steps:
1. Rewrite the post in each author's voice
2. Store the output in a table
Here is the table output:
- Column headers: author, rewritten post
- Rows: each of the authors I listed
- The first row should be the original post
- The "author" for that one should be "Original post"
---
INPUT:
[Use the post from above]
The AI sidekick returned 8 rows.
Original post. Then 7 author variations:
Gary Vee's version was direct and aggressive (too punchy for newsletter)
Seth Godin's had simple powerful frameworks (great for clarity)
Tim Ferriss's focused on tactical execution
Malcolm Gladwell's had narrative depth (perfect for newsletter storytelling)
James Clear's was habit-focused and systematic
Ryan Holiday's carried stoic wisdom
Hemingway's was brutally simple (too sparse)
Emma loved Malcolm Gladwell's version for the newsletter. More story. More depth. More engaging for a 3-minute read.
She grabbed that style. Crushed it.
Generation time: 60 seconds.
Completion moment: Emma had her newsletter version. Same core idea. Perfect narrative flow for long-form.
🎯 Step 3: Emma saw her post rewritten for 6 different goals
Emma had the Twitter version (sarcastic) and newsletter version (storytelling). Now she wanted to test which approach drove the most clicks on LinkedIn.
Should this post be persuasive? Action-oriented? Informative? Descriptive?
She tried to make it more action-oriented. Added a CTA. Read it again. Felt too pushy.
Tried to make it persuasive. Added power words. Read it again. Too salesy.
Which goal should drive this post for A/B testing? She kept rewriting. Each attempt took 10 minutes. Still couldn't decide.
20 minutes. Three failed rewrites. Zero clarity.
The problem? Emma couldn't see which goal would actually drive clicks. Just guessing which approach worked.
But if she could see all 6 goal versions at once, she could A/B test the top 2.
Here's what she did:
The goal-based rewrite prompt:
You are my personal "post multiplier."
I am going to give you a social media post. Then you are going to rewrite it with 6 different "goals."
1. More concise
2. More emphatic
3. More humorous
4. More descriptive
5. More persuasive
6. More informative
7. More action-oriented
Here are the steps:
1. Rewrite the post for each goal
2. Store the output in a table
Here is the table output:
- Column headers: goal, rewritten post
- Rows: each of the goals I listed
- The first row should be the original post
- The "goal" for that one should be "Original post"
---
INPUT:
[Use the post from above]
The AI sidekick returned a table with 8 rows.
Original post. Then 7 goal variations:
Concise version cut straight to it (too short, lost context)
Emphatic version had punch (good option)
Humorous version made people smile
Descriptive version painted a picture
Persuasive version drove emotion (good for clicks)
Action-oriented version was a clear CTA (best for conversions)
Emma spotted two winners. The persuasive version for clicks. The action-oriented version for conversions.
She'd A/B test both on LinkedIn. See which performed better.
Generation time: 50 seconds.
Completion moment: Emma had 2 LinkedIn test versions ready. Data would show which goal drove better results.
👥 Step 4: Emma adapted her post for 6 different demographics
Emma had Twitter (sarcastic), newsletter (storytelling), and LinkedIn A/B tests (persuasive vs action). But 40% of her followers had English as a second language.
Her posts used American idioms. Cultural references. Slang. These confused her ESL audience.
Should she simplify everything for ESL? Or keep it sophisticated for native speakers? Or write two versions?
She tried writing one ESL-friendly version. Avoided idioms. Made it clearer. Read it again. Felt dumbed down for her native English audience.
Each demographic version took 12 minutes. After three attempts, she still didn't know how to balance audiences.
35 minutes. Three demographic versions. Still unclear which to use where.
The problem? Emma was writing blind. She couldn't see how each demographic would actually receive the same post.
Turns out, if she could see all 6 demographic versions side by side, she'd know exactly how to adapt for each audience.
Here's what worked:
The demographic adaptation prompt:
You are my personal "post multiplier."
I am going to give you a social media post. Then you are going to rewrite it for 6 different "demographics."
1. For 3rd graders
2. For 8th graders
3. For a college student
4. For a busy 40-year-old mom
5. For an 80-year-old who reads slowly
6. For an audience where English is a second language
Here are the steps:
1. Rewrite the post for each demographic
2. Store the output in a table
Here is the table output:
- Column headers: demographic, rewritten post
- Rows: each of the demographics I listed
- The first row should be the original post
- The "demographic" for that one should be "Original post"
---
INPUT:
[Use the post from above]
The AI sidekick returned a table with 7 rows.
Original post. Then 6 demographic variations:
3rd grader version was super simple (too basic)
College student version was casual and relatable
Busy mom version was efficient and practical
80-year-old version was slow and clear
ESL version avoided idioms and slang (perfect for global audience)
Emma's global followers? 40% ESL. The ESL version nailed it. Clear. Simple. No confusing American references.
She'd post that version on platforms with high international audiences.
Generation time: 55 seconds.
Completion moment: Emma had her ESL-friendly version. Same message. Zero confusion for global followers.
🚀 Emma's results after 6 weeks
Before:
Time to adapt one post for multiple platforms: 2+ hours
Platforms posted on: LinkedIn only
Versions created: 1-2 manual rewrites max
Cross-platform reach: 2,400 followers (LinkedIn only)
After:
Time to adapt one post for all platforms: 10 minutes
Platforms posted on: LinkedIn, Twitter, Newsletter, Facebook
Versions created: 28 variations per post
Cross-platform reach: 8,900 followers (combined)
Her process now:
Write original LinkedIn post (5 minutes)
Run 4 table prompts in same chat (3 minutes)
Review 28 variations (2 minutes)
Pick best versions per platform (Twitter: sarcastic, Newsletter: storytelling, ESL: simplified)
Schedule all platforms (3 minutes)
Total time: 13 minutes. Not 2+ hours.
Her AI sidekick generates 28 platform-ready versions in under 3 minutes. Bingo.
🧩 Your turn
Copy all 4 prompts into your AI sidekick. Run them in the same chat.
Paste your LinkedIn post (or any social content) into Prompt 1. Your AI sidekick shows you 6 tone variations. Pick the punchy one for Twitter.
Then Prompt 2 runs with the same post. You see 7 author versions. Pick the storytelling one for your newsletter.
Then Prompt 3. You see 7 goal-based versions. Pick 2 to A/B test on LinkedIn.
Then Prompt 4. You see 6 demographic versions. Pick the ESL-friendly one for global followers.
Total generation time: 3 minutes. Time to pick your platform versions: 2 minutes.
That's it, my fellow outliers!
Yours 'turning your expertise into income 10x faster' Vijay peduru 🦸♂️