You are likely ignoring the biggest free focus group on the internet because you think it doesn’t apply to your business.
But that is exactly how you miss out on trends before they go mainstream. I just saw this incredible post from an AI professional who revealed a hidden technical workflow that turns Reddit threads into high-performing LinkedIn content. The methodology goes far beyond simple scrolling; it involves a clever URL hack and a dual-AI processing system that I honestly hadn’t thought of using before.
The JSON Backdoor Strategy
Most people browse Reddit via the app or website, looking at the user interface. However, the creator of this workflow points out that there is a much richer layer of data sitting right underneath the surface. The expert explained that by simply adding .json to the end of any Reddit URL, you bypass the visual interface entirely and access the raw data of the thread.
Why does this matter? Because copying text from a screen is messy and often misses context like reply hierarchies or upvote ratios. When this innovator copies the raw JSON metadata, they are capturing the entire conversation structure—every complaint, every rebuttal, and every enthusiastic agreement—in a format that Large Language Models (LLMs) can digest perfectly. It transforms a messy forum thread into a structured database of human sentiment. This savvy professional then uses two different AI models, Grok and Claude, to process this data in stages, ensuring that the final output isn’t just a summary, but a strategic asset.
💡 Phase 1: Mining for Pain with Grok
The first step in the author’s process is all about extraction and analysis. They recommend using Grok for this specific task. The goal isn’t just to summarize what people are talking about; it is to identify the specific "pain, limitations, and needs" hidden within the user comments. The JSON data provides the raw material, and Grok acts as the miner sifting for gold.
This expert emphasizes that you need to be specific with your instructions. You aren’t asking the AI to write a post yet; you are asking it to analyze the psychology of the thread. By feeding the JSON into the model, the creator extracts the exact frustrations that real people are expressing. This eliminates the guesswork from content creation. Instead of wondering what your audience struggles with, you have a direct transcript of their complaints.
The original poster provided this specific prompt to get the job done:
"Here’s the JSON of a Reddit conversation around: \"[REDDIT POST TOPIC]\". Extract the pain points, make 5 viral hooks (2 lines in one hook) on the same.
The viral hooks should be on the same format, style and tone as these 3 hooks that got results.
///Hook 1
[paste a good hook example]
///Hook 2
[paste a good hook example]
///Hook 3
[paste a good hook example]
JSON: [REDDIT META DATA]"
📌 Phase 2: The LinkedIn Ghostwriter (Claude)
Once the pain points are identified, the workflow shifts to content generation. The LinkedIn user suggests moving over to Claude for this phase. Claude is often praised for its nuanced writing capabilities and ability to mimic specific tones, which makes it ideal for drafting the final social media copy. The strategy here is "few-shot prompting": providing the AI with examples of what success looks like so it can replicate the structure without copying the content.
The author’s prompt instructs Claude to act like a ghostwriter. The key instruction is to match the structure, pacing, and formatting of proven viral posts. This includes specific stylistic choices like short lines, plenty of whitespace, and listicle formats. By combining the raw pain points extracted by Grok with the stylistic templates fed into Claude, the creator generates content that is both topically relevant and formatted for high engagement.
Here is the prompt the expert designed for this step:
"Act like a LinkedIn ghostwriter who writes posts that get saved + shared.
Goal: Create 5 LinkedIn posts on the new topic.
Use my 4 example LinkedIn posts below that are the most viral ones on linkedin, ever. You must match their structure, pacing, formatting (short lines + whitespace + listical), and voice but the ideas, wording, and hooks must be NEW.
Rules:
- Each post starts with a strong 2-line hook.
- Keep it skimmable
- With 1 clear takeaway + 1 framework (steps)
- End with a CTA that \"Repost for others to …….\"
- No fluff, no generic advice, no repeated angles across posts.
- Do NOT copy phrases or lines from the examples.
Here are the 4 example posts (study them first):
///Example Post 1
[PASTE POST]
///Example Post 2
[PASTE POST]
///Example Post 3
[PASTE POST]
///Example Post 4
[PASTE POST]
Now write 5 new posts about: [TOPIC]"
✅ The Validation Engine
The brilliance of this workflow isn’t just the use of AI; it is the source of the ideas. The industry pro behind this method highlights a critical truth: people have already told you what they want to read. When you look at a popular Reddit thread in your niche, you are looking at validated demand. The upvotes and the volume of comments are proof that the topic resonates.
This approach reverses the typical content creation process. Instead of writing a post and hoping it lands, the author finds a conversation that has already landed and effectively "ports" it to a different platform. It solves the blank page problem instantly. You aren’t staring at a blinking cursor wondering what to say; you are acting as a curator and translator, bringing valuable insights from a forum discussion to a professional network.
Potential Nuances and Challenges
While this .json trick is powerful, there are a few things to keep in mind. The raw text from a large Reddit thread can be massive. Depending on the length of the discussion, the JSON data might exceed the context window of standard LLM prompts. You may need to truncate the data or select only the most relevant sections of the JSON if the thread is thousands of comments long.
Furthermore, the "translation" from Reddit to LinkedIn is delicate! Reddit culture is anonymous, often cynical, and highly informal. LinkedIn is professional and reputation-based. The prompt provided by the creator does a great job of mitigating this by asking Claude to match specific LinkedIn examples, but you should always review the output to ensure the tone didn’t stay too "Reddit-like" during the transfer.
The original post has a full PDF guide that walks through this visually.