learn
beginner
Claude
ChatGPT
Gemini
Multi-platform
How to Use AI to Repurpose Content Across Platforms and Formats
A practical workflow for turning one piece of content into platform-ready posts for LinkedIn, Xiaohongshu, LINE, WeChat, and more using AI.
9 min read21 February 2026
content repurposing
social media
multilingual content
cross-platform
content marketing
How to take a single piece of content (article, talk, report, podcast) and turn it into 5-10 platform-specific outputs using AI
For marketers, founders, and content leads publishing across multiple platforms and markets, especially in Asia
You'll get a repeatable system, platform-specific prompts, and a worked example showing the full transformation from article to Xiaohongshu carousel
Works across Claude, ChatGPT, and Gemini with notes on where each performs best
Why This Matters
You wrote a 2,000-word article. It took you four hours. It lives on your blog. Maybe you shared it on LinkedIn with a one-line summary. And that's where it dies.
The content itself might be good enough to work on six different platforms, in three different formats, across two or three languages. But reformatting is boring, time-consuming, and feels like busywork. So it doesn't happen, and you've effectively built a house and only opened one room.
This problem is sharper in Asia-Pacific than anywhere else. If you're a brand or founder operating across the region, your audiences aren't sitting in one place. Your Singapore audience checks LinkedIn during lunch. Your Thai customers scroll LINE Official Accounts. Chinese consumers discover brands through Xiaohongshu carousels and Douyin clips. Japanese enterprise buyers read long-form on note.com. Each platform has its own format conventions, character limits, tone expectations, and language. Manually adapting content for each one is a full-time job. AI collapses that job into something a single person can manage in an afternoon.
Here's the process.
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The content itself might be good enough to work on six different platforms, in three different formats, across two or three languages. But reformatting is boring, time-consuming, and feels like busywork. So it doesn't happen, and you've effectively built a house and only opened one room.
This problem is sharper in Asia-Pacific than anywhere else. If you're a brand or founder operating across the region, your audiences aren't sitting in one place. Your Singapore audience checks LinkedIn during lunch. Your Thai customers scroll LINE Official Accounts. Chinese consumers discover brands through Xiaohongshu carousels and Douyin clips. Japanese enterprise buyers read long-form on note.com. Each platform has its own format conventions, character limits, tone expectations, and language. Manually adapting content for each one is a full-time job. AI collapses that job into something a single person can manage in an afternoon.
Here's the process.
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How to Do It
1
### Step 1: Choose your source content and identify what's reusable
Not everything in a long-form piece is worth repurposing. Before you start generating outputs, read your source content and mark the elements that can stand alone: a strong data point, a clear framework, a contrarian opinion, a practical checklist, a before-and-after example.
A 2,000-word article typically contains 4-6 of these standalone elements. Each one can become its own post on a different platform. You're not compressing the whole article. You're extracting the parts that work independently.
### Step 2: Map your target platforms and their format requirements
Write a simple grid: platform, format, length, tone, language. This becomes the brief you hand to AI. Being specific here prevents the most common failure mode, which is getting back a generic "social media post" that fits nowhere.
For example: LinkedIn (text post, 800-1,200 characters, professional but conversational, English). Xiaohongshu (carousel, 6-8 slides, 50-80 characters per slide, casual and visual, Simplified Chinese). LINE Official Account (message, 500 characters max, friendly and direct, Thai). Each platform gets its own brief.
### Step 3: Create a master context block you can reuse across prompts
Write a paragraph that summarises your source content, your brand voice, and your audience for each market. Paste this at the top of every repurposing prompt. It sounds tedious, but it saves you from repeating yourself in every prompt and keeps outputs consistent.
Include: what the original content is about (2-3 sentences), who you're talking to (be specific), your brand voice guidelines (short and concrete, not "engaging and dynamic"), and any constraints (word limits, compliance requirements, topics to avoid).
### Step 4: Generate platform-specific outputs one at a time
Don't ask AI to produce all platform versions in a single prompt. The quality drops badly when you ask for five different outputs at once, because the model tries to be efficient rather than genuinely adapting for each platform.
Run one prompt per platform. Give it the source content, your context block, and the specific format requirements for that platform. Ask for one output and iterate on it before moving to the next platform. Each generation takes 30-60 seconds. The quality difference versus batch generation is worth the extra minutes.
### Step 5: Adapt for language and cultural context, not just translate
This is where most AI repurposing falls apart. Translating your English LinkedIn post into Thai and posting it on LINE is not repurposing. It's lazy translation, and your audience will feel it.
Each market has different reference points, humour norms, formality expectations, and content preferences. A post referencing "Q4 planning" might resonate on LinkedIn Singapore but mean nothing to a Xiaohongshu audience in China. Tell AI what to localise, not just what to translate. Swap references, adjust examples, change the framing to match what that specific audience cares about.
### Step 6: Add the platform-native elements AI can't do well
AI produces the text. You add the parts that make it feel native to the platform: the right hashtags (research these yourself, don't trust AI's suggestions blindly), the image or carousel design, the emoji patterns that are normal on that platform (heavy on Xiaohongshu, lighter on LinkedIn, almost mandatory on LINE), and any interactive elements like polls or question stickers.
For Xiaohongshu specifically, the cover image and first two slides determine whether anyone reads the rest. AI can write the slide copy, but the visual layout and aesthetic need to match what performs on the platform. Look at what's trending in your category before you design.
### Step 7: Build a repurposing template you can run repeatedly
After your first round, save your best-performing prompts as templates with placeholders for the source content. A monthly article should become 8-12 pieces of platform-specific content within two hours, not two days. The system only pays off if you use it consistently.
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Not everything in a long-form piece is worth repurposing. Before you start generating outputs, read your source content and mark the elements that can stand alone: a strong data point, a clear framework, a contrarian opinion, a practical checklist, a before-and-after example.
A 2,000-word article typically contains 4-6 of these standalone elements. Each one can become its own post on a different platform. You're not compressing the whole article. You're extracting the parts that work independently.
### Step 2: Map your target platforms and their format requirements
Write a simple grid: platform, format, length, tone, language. This becomes the brief you hand to AI. Being specific here prevents the most common failure mode, which is getting back a generic "social media post" that fits nowhere.
For example: LinkedIn (text post, 800-1,200 characters, professional but conversational, English). Xiaohongshu (carousel, 6-8 slides, 50-80 characters per slide, casual and visual, Simplified Chinese). LINE Official Account (message, 500 characters max, friendly and direct, Thai). Each platform gets its own brief.
### Step 3: Create a master context block you can reuse across prompts
Write a paragraph that summarises your source content, your brand voice, and your audience for each market. Paste this at the top of every repurposing prompt. It sounds tedious, but it saves you from repeating yourself in every prompt and keeps outputs consistent.
Include: what the original content is about (2-3 sentences), who you're talking to (be specific), your brand voice guidelines (short and concrete, not "engaging and dynamic"), and any constraints (word limits, compliance requirements, topics to avoid).
### Step 4: Generate platform-specific outputs one at a time
Don't ask AI to produce all platform versions in a single prompt. The quality drops badly when you ask for five different outputs at once, because the model tries to be efficient rather than genuinely adapting for each platform.
Run one prompt per platform. Give it the source content, your context block, and the specific format requirements for that platform. Ask for one output and iterate on it before moving to the next platform. Each generation takes 30-60 seconds. The quality difference versus batch generation is worth the extra minutes.
### Step 5: Adapt for language and cultural context, not just translate
This is where most AI repurposing falls apart. Translating your English LinkedIn post into Thai and posting it on LINE is not repurposing. It's lazy translation, and your audience will feel it.
Each market has different reference points, humour norms, formality expectations, and content preferences. A post referencing "Q4 planning" might resonate on LinkedIn Singapore but mean nothing to a Xiaohongshu audience in China. Tell AI what to localise, not just what to translate. Swap references, adjust examples, change the framing to match what that specific audience cares about.
### Step 6: Add the platform-native elements AI can't do well
AI produces the text. You add the parts that make it feel native to the platform: the right hashtags (research these yourself, don't trust AI's suggestions blindly), the image or carousel design, the emoji patterns that are normal on that platform (heavy on Xiaohongshu, lighter on LinkedIn, almost mandatory on LINE), and any interactive elements like polls or question stickers.
For Xiaohongshu specifically, the cover image and first two slides determine whether anyone reads the rest. AI can write the slide copy, but the visual layout and aesthetic need to match what performs on the platform. Look at what's trending in your category before you design.
### Step 7: Build a repurposing template you can run repeatedly
After your first round, save your best-performing prompts as templates with placeholders for the source content. A monthly article should become 8-12 pieces of platform-specific content within two hours, not two days. The system only pays off if you use it consistently.
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What This Actually Looks Like
The Prompt
I'm repurposing the article below into a Xiaohongshu carousel post (6 slides). The audience is Chinese entrepreneurs and product managers interested in Southeast Asian tech and business trends. Platform requirements: - 6 slides, each with a headline (under 15 characters in Chinese) and body text (40-60 characters per slide) - Slide 1 is the hook. It needs to stop the scroll. Use a surprising stat or counterintuitive claim from the article. - Slide 6 is the CTA. Ask readers to save/follow, not to visit an external link (Xiaohongshu penalises external links). - Tone: informative but casual. Use the language style common on Xiaohongshu for business/tech content, not formal news Chinese. - Include 2-3 relevant emoji per slide (Xiaohongshu convention). - Write all content in Simplified Chinese. Do NOT just summarise the article slide by slide. Pick the single most interesting angle and build the carousel around that. Source article: [PASTE ARTICLE]
Prompts to Try
Prompt 1: Platform-Specific Repurposing (Any Platform)
Repurpose the article below into a single [PLATFORM] post. Target audience: [DESCRIBE SPECIFICALLY] Language: [LANGUAGE] Format: [FORMAT - e.g., text post, carousel, thread, message] Length: [CHARACTER/WORD LIMIT] Tone: [SPECIFIC TONE DESCRIPTION - not just "professional"] Rules: - Don't summarise the article. Pick the single most compelling angle for this specific audience and platform. - Match the conventions of [PLATFORM]. Study how top posts in [CATEGORY] look on this platform. - If writing in a non-English language, write natively for that market. Don't translate English phrasing. Use local references and examples where appropriate. - End with a CTA that fits the platform's culture (e.g., "save this" on Xiaohongshu, "share your experience" on LinkedIn). Source article: [PASTE ARTICLE]
What to expect: A single platform-native post that reads like it was written for that platform, not adapted from somewhere else. Works well across all major AI tools. Claude handles voice and tone adaptation best. Gemini is useful when you need it to reference current platform trends.
Prompt 2: Extract Reusable Elements from Source Content
Read the article below and identify every element that could work as standalone content on social media or messaging platforms. For each element, list: 1. The element type (statistic, framework, checklist, opinion, example, quote, how-to step) 2. A one-sentence summary 3. Which platforms it would work best on and why 4. Suggested format for that platform (carousel slide, text post, infographic data point, short video script hook, etc.) Only include elements that genuinely stand alone. If someone read just that element with no other context, would it still make sense and provide value? Article: [PASTE ARTICLE]
What to expect: A structured list of 4-8 content elements with platform recommendations. This is your repurposing roadmap. Run this before writing any individual platform posts. Works equally well on Claude and ChatGPT.
Prompt 3: Localise, Don't Translate
I have a LinkedIn post written in English for a Singapore professional audience. I need to adapt it (not just translate it) for [TARGET PLATFORM] in [TARGET MARKET/LANGUAGE]. Changes needed: - Rewrite in [LANGUAGE], using native phrasing and sentence structures (not translated English) - Replace any Western-centric examples or references with equivalents relevant to [TARGET MARKET] - Adjust the tone to match [PLATFORM] conventions in [MARKET] - Adapt the CTA to what works on [PLATFORM] - Adjust the format to [PLATFORM REQUIREMENTS - e.g., character limit, carousel format, emoji conventions] Original English LinkedIn post: [PASTE POST]
What to expect: A culturally adapted version, not a translation. The output should feel like it was written by someone who lives in that market and publishes on that platform regularly. Claude handles this well for Chinese and Japanese. Gemini performs strongly for Thai, Vietnamese, and Bahasa Indonesia thanks to its training data breadth.
Common Mistakes
Batch-generating all platform versions in one prompt.
People paste an article and ask for "a LinkedIn post, a tweet thread, an Instagram caption, and a Xiaohongshu carousel." The model treats it like a factory line and the outputs are all bland adaptations of the same summary. One prompt per platform, every time.
Translating instead of localising.
Running your English post through translation and posting it on a local-language platform produces content that reads like a translated document. Your Thai LINE audience doesn't think in English sentence structures. Tell AI to write natively for the market, with local references and phrasing.
Trusting AI's hashtag suggestions.
AI generates plausible-looking hashtags that often have zero actual usage or are wrong for the platform's current algorithm. On Xiaohongshu especially, trending hashtags shift weekly. Research hashtags manually on the target platform before publishing.
Repurposing the whole article instead of extracting the best bits.
A 2,000-word article doesn't compress into a good 200-character post. The best repurposed content takes one angle, one data point, or one opinion and builds a complete short-form piece around it. Ask AI to identify the standalone elements first (see Prompt 2), then generate outputs from those.
Ignoring platform-specific formatting conventions.
A Xiaohongshu carousel with no emoji looks wrong. A LINE message over 500 characters gets truncated. A LinkedIn post without paragraph breaks is unreadable on mobile. Specify format rules in your prompt. Don't assume AI knows what "a good Xiaohongshu post" looks like.
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Tools That Work for This
Claude- Best for tone adaptation and culturally-aware localisation, especially into Chinese and Japanese. Handles long source content well. No web access, so you supply the source material and platform context.
ChatGPT (GPT-4o)- Strong at following structured formatting instructions, which matters when you're specifying character limits and slide counts. The custom GPT feature lets you save repurposing instructions so you don't re-enter them every time.
Gemini- Useful when you need current platform context (trending formats, recent algorithm changes) since it can access Google Search. Performs well for Southeast Asian languages.
Canva- Not AI in the traditional sense, but once you have carousel copy from AI, Canva's templates are the fastest path to a designed Xiaohongshu or Instagram carousel. The Magic Write feature can also help tighten slide copy.
PromptAndGo.ai- If you're running the same repurposing workflow monthly, storing your platform-specific prompts with variables for the source content saves the setup time that makes people abandon the process after week two.
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Frequently Asked Questions
Start with two or three where your audience actually spends time. Posting on eight platforms poorly is worse than posting on three well. For most Asia-Pacific businesses, that's LinkedIn plus one or two regional platforms relevant to your market (Xiaohongshu, LINE, WeChat, or whatever fits your audience).
It does a reasonable job if you give it specific instructions and examples. Telling AI "write for Xiaohongshu" is too vague. Telling it "use the casual, emoji-heavy style common in Xiaohongshu tech/business content, with 40-60 characters per carousel slide and a save-focused CTA" produces much better results. Feed it one or two examples of posts you like from the platform if you can.
No. Repurpose the ones that contain standalone insights, data, or frameworks. If an article is purely narrative or opinion without extractable elements, it might work as a LinkedIn post but won't break down into a carousel or a messaging platform post. Be selective.
Include a short brand voice guide (3-5 bullet points covering tone, vocabulary, and what to avoid) in your context block and paste it into every prompt. It won't be identical across platforms, because it shouldn't be. Your LINE message should sound different from your LinkedIn post. Consistency means recognisable values and personality, not identical phrasing.
Only if you have someone who can review the output before it goes live. AI produces fluent text that can still miss cultural context, use awkward phrasing, or get the tone wrong. A native speaker spending five minutes reviewing an AI-generated post catches problems that could take weeks to damage your reputation. Budget for review, or stick to languages you or your team can quality-check.
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Next Steps
Pick your best-performing article from the last three months. Run the element extraction prompt (Prompt 2) to identify what's reusable. Then generate one output for one platform using Prompt 1. Once you see the quality, you'll know whether to expand to more platforms or refine your prompts first.
For guidance on writing the source articles themselves, see [INTERNAL LINK: How to use AI to write long-form articles]. If you're doing multilingual content across the region regularly, [INTERNAL LINK: How to use AI for multilingual content and translation across Asian markets] covers the language adaptation side in more depth.
Want to customise these prompts for your specific use case? PromptAndGo.ai can optimise any prompt for your platform and audience.
For guidance on writing the source articles themselves, see [INTERNAL LINK: How to use AI to write long-form articles]. If you're doing multilingual content across the region regularly, [INTERNAL LINK: How to use AI for multilingual content and translation across Asian markets] covers the language adaptation side in more depth.
Want to customise these prompts for your specific use case? PromptAndGo.ai can optimise any prompt for your platform and audience.