The One Paper, Ten Posts Machine: Systematic Content Generation from Research

Transform one paper into Twitter threads, LinkedIn articles, newsletter blurbs, video scripts, and blog posts—systematically generated in under an hour. Your complete launch package ready on publication day.

The One Paper, Ten Posts Machine: Systematic Content Generation from Research

Publication day arrives. Your paper is live. And you... send one tweet and move on.

Not because you don't care about dissemination. Because creating content for multiple platforms feels overwhelming. By the time you could generate a proper launch package, you're deep into the next project.

The Asset Factory solves this. One systematic process transforms one paper into a complete content package—ready before publication day.

The Content Gap Problem

Most researchers produce one piece of dissemination content per paper (if that):

Meanwhile, the research that gets noticed produces:

The difference isn't talent or time—it's systems.

The Asset Factory: What You'll Generate

From one paper and one Research Brain context, you'll create:

Primary Assets (Publication Day)

  1. Twitter thread (8-12 tweets)
  2. LinkedIn article (800-1200 words)
  3. Blog post (1500-2500 words)
  4. Visual abstract (single image summary)
  5. Press release (journalist-ready)

Secondary Assets (Follow-Up)

  1. Newsletter blurb (150-200 words)
  2. Video script (3-5 minute explainer)
  3. Podcast talking points (for interviews)
  4. FAQ document (anticipated questions + answers)
  5. Policy brief (if applicable)

Time Investment

| Asset | Traditional Time | With Asset Factory | |-------|-----------------|-------------------| | Twitter thread | 45 min | 10 min | | LinkedIn article | 90 min | 15 min | | Blog post | 3 hours | 20 min | | Visual abstract | 4 hours | 15 min | | Press release | 2 hours | 15 min | | Secondary assets | 3+ hours | 25 min | | Total | 13+ hours | ~100 min |

The Cascade Prompt

Generate everything through a systematic cascade:

Step 1: The Master Summary

Start with this prompt:

"Using my Research Brain context, create a master summary of this research optimized for dissemination:

[Upload/paste Context Readme and Nuance Guardrails]

Include:

  1. The Hook: One compelling sentence that makes people want to know more
  2. The Problem: What gap or issue this research addresses (2-3 sentences)
  3. The Approach: How we studied this (1-2 sentences, accessible)
  4. The Key Findings: 3-4 main findings, accurately stated with appropriate hedging
  5. The Implications: Why this matters for [practice/policy/public] (2-3 sentences)
  6. The Limitations: What we can't claim (1-2 sentences)
  7. The Bottom Line: One sentence takeaway

This master summary will fuel all subsequent content. Accuracy is critical."

Step 2: The Twitter Thread

"Using the master summary, create a Twitter thread (10 tweets):

Tweet 1: Hook + promise (why should someone read this thread?) Tweets 2-3: The problem we addressed Tweets 4-6: Key findings (one finding per tweet, accessible language) Tweets 7-8: Why this matters / implications Tweet 9: Important caveats (maintain scientific integrity) Tweet 10: Call to action + link placeholder

Rules:

  • 280 characters max per tweet
  • Use thread numbering (1/10, 2/10, etc.)
  • Accessible language (imagine smart friend, not academic)
  • No jargon without definition
  • Maintain accuracy per Nuance Guardrails"

Step 3: The LinkedIn Article

"Using the master summary, create a LinkedIn article (900 words):

Structure:

  • Opening hook (why professionals should care)
  • The research question and why it matters
  • What we found (accessible, with appropriate hedging)
  • What this means for [industry/practice/policy]
  • What questions remain
  • Personal reflection on the research (optional)
  • Call to action

Audience: Professional network, educated but not academic Tone: Thoughtful, authoritative, accessible Include 2-3 subheadings for scannability"

Step 4: The Blog Post

"Using the master summary, create a full blog post (2000 words):

Structure:

  • Engaging introduction (hook readers immediately)
  • The context: what's the problem or gap?
  • What we did: methodology in accessible terms
  • What we found: findings with examples and implications
  • What this means: practical takeaways
  • What we don't know: limitations and future directions
  • Conclusion: the bottom line

Style:

  • Subheadings every 300-400 words
  • Short paragraphs (3-4 sentences max)
  • Occasional bullet points for scannability
  • Accessible but not dumbed down
  • Links to paper and related resources (placeholder)"

Step 5: Newsletter Blurb

"Create a 150-word newsletter blurb summarizing this research:

The reader is a busy professional scanning a weekly newsletter. They need:

  • Why this research matters (one sentence)
  • What we found (2-3 sentences)
  • What to do with this information (one sentence)
  • Link to full article (placeholder)

Make it compelling enough to click through but valuable even if they don't."

Step 6: Video Script

"Create a script for a 4-minute research explainer video:

Structure:

  • Hook (0:00-0:20): Why should viewers care?
  • Problem setup (0:20-1:00): What question are we answering?
  • The research (1:00-2:00): What we did (simplified)
  • Key findings (2:00-3:00): What we found (2-3 points)
  • So what? (3:00-3:40): Why this matters
  • Caveats + close (3:40-4:00): What we can't claim + call to action

Tone: Conversational, as if explaining to a curious friend Include visual cues [SHOW: data visualization] where helpful"

Quality Control

After generating assets, run quality checks:

Accuracy Verification

"Compare these five pieces of content against my Nuance Guardrails:

[Paste all content]

Nuance Guardrails: [Paste guardrails]

For each piece:

  1. Does it stay within what we can claim?
  2. Are there any overstatements?
  3. Is hedging language preserved?
  4. Any problematic phrases to flag?"

Consistency Check

"Review these content pieces for consistency:

[Paste all content]

Verify:

  • Key findings stated consistently across all pieces
  • No contradictions between versions
  • Appropriate complexity for each platform
  • Core message preserved despite format differences"

Platform Optimization

"Review each piece for platform fit:

Twitter thread: Character limits? Thread flow? Hashtag opportunities? LinkedIn: Professional tone? Valuable to network? Blog: SEO considerations? Subheading structure? Newsletter: Scannable? Clear value proposition? Video: Pacing appropriate? Visual cues sufficient?"

The Publication Day Protocol

Week -2: Preparation

Week -1: Generation

Publication Day: Execution

Week +1: Follow-Up

Building Your Asset Library

Over time, customize your Asset Factory:

Template Refinement

After each paper, note:

Update your prompts based on learnings.

Platform Specialization

Different fields have different norms:

Customize prompts to match your professional community's expectations.

Feedback Integration

When content performs well (or poorly):

The Return on Investment

Per Paper: ~10 hours saved

Traditional complete launch: 13+ hours Asset Factory launch: ~100 minutes Savings: ~11 hours per paper

Per Year: 33+ hours (at 3 papers)

Time returned to research, teaching, or life.

Beyond Time: Reach and Impact

Research that gets disseminated gets:

The real ROI isn't time—it's impact.

Ready to Build Your Dissemination Engine?

This article is part of a comprehensive guide to AI-powered research dissemination. Learn how to get your research out of the PDF graveyard and into the hands of people who can use it.

Explore the Complete Book: Claude for Research Dissemination