Repurposing content isn’t a new idea. But AI has made it dangerously easy to do it badly.
Most tools treat repurposing like slicing a pizza. They cut a blog into a few paragraphs, repackage it into a caption, and post it everywhere. Sounds efficient, right? Except what you end up with is flat, generic content that no longer feels like it was made for anyone — or by anyone.
These tools don’t understand intent. They don’t adapt tone for the platform. They don’t prioritize what made the original content powerful in the first place.
That’s why we stopped using repurposing tools — and started building repurposing assistants.
Each one is designed for a specific platform and format, trained on our tone of voice, and aware of our best-performing content. They don’t just copy and paste. They transform.
Because real repurposing isn’t just about distribution — it’s about strategy:
In this article, we’ll introduce you to our assistant stack — and show how each one helps us turn a single piece of content into a multi-platform presence that still sounds like us.
Let’s start with the one that does the heavy lifting: IDEA Repurposer.
You’ve written a killer blog post or recorded a podcast packed with insight — but now you’re staring at a blank LinkedIn post. This is where the IDEA Repurposer comes in.
It takes long-form content and fractures it into a series of punchy, strategic content fragments — each with a unique angle, tone, and intent.
The IDEA Repurposer breaks content down into four powerful repurposing buckets:
Instead of slicing the same idea four times, it reframes it four different ways — making it look and feel native to the platform it’s posted on.
We give it clear instructions, including:
The assistant is trained on our best posts and internal guidelines using OpenAI’s knowledge module. It references the types of hooks, structures, and formats that consistently perform — so each repurposed idea fits our audience and tone.
Once we’ve got hooks and angles, we can pass them to other assistants for formatting and expansion — like carousels or email storytelling.
Next: turning one of these fragments into a platform-native carousel with Carousel Craftr.
Swipable carousels are the new blog posts. They're visual, structured, and perfect for platforms like LinkedIn and Instagram.
But they’re not just text blocks broken into slides — they need rhythm, pacing, and design logic. That’s why we use the Carousel Craftr.
This assistant takes a single insight (often pulled from the IDEA Repurposer) and transforms it into a 7–20 slide framework that’s built to keep people swiping.
Each slide has a job. For example:
This structure works across industries — from thought leadership to storytelling to tactical tips.
We define:
Carousel Craftr uses our past carousel scripts as a reference via the knowledge module. It knows how we format titles, where we place CTAs, and what our visual pacing looks like.
This turns a single idea into a scroll-stopping piece of visual content — and once approved, we pass it to design or automation for graphics.
Next up: how we turn raw insights or stories into polished, voice-aligned LinkedIn posts with the LinkedIn Content Assistant.
Some of our best-performing content doesn’t start as a “post idea.” It starts as a story from a sales call, a newsletter line that hit a nerve, or a client win that teaches something deeper.
The LinkedIn Content Assistant turns these fragments into real thought leadership — not regurgitated tips.
This assistant takes raw input (like an email blurb, Zoom transcript, or Slack message) and turns it into a voice-aligned, opinionated post designed to:
It can work solo, or in tandem with the IDEA Repurposer — choosing a strong fragment and expanding it.
We use a structured prompt like this:
This assistant leans heavily on tone calibration. We embed our tone-of-voice quiz results and favorite post examples in the knowledge base, so it knows exactly what “on-brand” looks like.
We also update it weekly with:
Once a post is drafted, we send it through our Demanding AI Editor or manually polish it — then schedule.
Coming up next: the Newsletter Writer, which turns top-performing short-form content into relationship-building long-form.
Sometimes your best email ideas are already written — they just haven’t been turned into emails yet. A great LinkedIn post, carousel, or even a tweet thread can become a compelling newsletter with the right structure and tone.
That’s exactly what the Newsletter Writer is built for.
This assistant takes short-form wins and expands them into long-form, story-first emails that:
It knows how to craft an opening hook, develop a narrative, and wrap with either a prompt, insight, or offer.
We frame the assistant like this:
We train this assistant using high-performing past emails and a tone guide that captures the right balance of depth, wit, and vulnerability. We also include:
The Newsletter Writer lets us stretch short-form insights into long-form relationships — without sounding like a blog rehash or sales pitch.
Next, we’ll show you how we keep everything aligned across these assistants. Even when they’re working in parallel.
When you’ve got multiple assistants working across platforms and formats, the risk is inconsistency. One post sounds polished, the next feels robotic. One email hits hard, the next one rambles.
The key to solving this is a unified tone system.
Here’s how we keep all our assistants speaking in the same voice — even if they’re tackling different tasks.
Every assistant includes the same tone-of-voice description in its prompt. This includes:
We maintain a global banned-phrases list shared across all prompts, including:
These are the dead giveaways of generic AI. Removing them makes every assistant sharper.
Even though platforms vary, our formatting rules stay consistent:
Each assistant has its own flavor, but they follow the same structure, just translated into platform-native language.
Using OpenAI’s Knowledge module or Vector Store, all assistants pull from:
This ensures they reference the same ideas, use consistent examples, and stay on-message, no matter what they’re repurposing.
Next, let’s walk through how we use this system in real life — from one podcast to a full week of multi-platform content.
To bring this system to life, here’s how we repurpose a single podcast episode into a full suite of platform-native content — using our AI assistants to handle the heavy lifting.
This isn’t theory. It’s our actual weekly workflow.
We run the episode through a transcription tool like Descript or Riverside. Then we pull it into our assistant stack.
We paste the transcript into the IDEA Repurposer, which breaks it into:
Each one becomes a potential seed for the next assistants.
We choose the most visual insight and pass it into Carousel Craftr, which turns it into a slide-by-slide script:
This becomes a LinkedIn or Instagram post — ready for design.
Another fragment becomes a personal, thought-led post. This assistant makes sure it opens strong, stays tight, and reflects our founder voice.
The most emotional or story-based fragment goes into the Newsletter Writer. It’s expanded into a 250–300 word narrative with a personal hook, a business insight, and a CTA.
We send all drafts to the Demanding AI Editor (and then, manually review) for polishing. Then everything is scheduled using Publer.
Total Output:
Time to produce: ~45 minutes of review.
Impact: A full week of high-performing, on-brand content
Content repurposing isn’t about doing less, it’s about doing smarter. When you pair AI with clear roles, personalized prompts, and a shared knowledge base, you don’t just republish content… you reinvent it.
With the right assistants in place, you can:
This system doesn’t just save time. It expands reach without sacrificing depth or quality.
Want access to all the assistants we’ve shared — including the exact prompts, templates, and training we use internally?
👉 [Click here to get our AI Repurposing Assistant Stack] and start turning your content into a multi-platform growth engine.
Learn more about B2B Content Marketing:
