Frameworks

Framework Breakdowns

Documented extraction processes for each major content format. Built around examples, not abstractions.

Every framework here follows the same structure.

Source analysis. Format requirements. The extraction steps. A worked example using a real article type. Then notes on what to watch for — the parts where most people get the format wrong.

Frameworks are organized by output format, not by source type. You start with the format you need to produce, then work backward to understand what to pull from the source.

Framework diagram printed on paper with annotations and colored markers on a clean desk
Framework 01

The 5-Post LinkedIn Extraction

What this framework does

A well-researched article contains multiple distinct arguments, each capable of standing alone. This framework identifies those arguments systematically and rebuilds each as a native LinkedIn post — with a format-appropriate hook, a clear narrative arc, and a closing that invites engagement without demanding it.

The extraction steps

1
Map the article's claims.

Read through the article and pull out every distinct assertion. Each is a potential post seed. Most articles have between six and ten, though shorter pieces may have fewer. Do not evaluate them yet — just list them.

2
Score for LinkedIn fit.

LinkedIn audiences respond well to counterintuitive insights, process revelations, and professional lessons. Score each claim on those three dimensions. The top five become your posts. Skip anything too technical, too niche, or that requires the full article context to make sense.

3
Write the hook first.

LinkedIn posts live or die on their first two lines — the text that appears before the "see more" break. Write the hook as a standalone sentence that creates tension or presents a contradiction. The body resolves it. This structure is consistent across all five posts.

4
Build the body as a narrative, not a list.

Most LinkedIn posts lean on bullet lists. Native-feeling posts that perform consistently tend to use short paragraphs with one idea each. The claim from the article becomes a story or a sequence. Lists work for instructional content — for insights, narrative outperforms.

5
Close with a question, not a call to action.

LinkedIn's algorithm rewards comment engagement. A genuine question — one you actually want the answer to — performs better than "what do you think?" or "have you experienced this?" Be specific. The question should follow logically from the post's argument.

Worked Example

Source article: "Why Most Editorial Calendars Fail Before the First Month." The article contains seven distinct claims. After scoring, the top five are: (1) the planning horizon mismatch, (2) the single-author bottleneck, (3) the format-agnostic approach, (4) the publication-first mindset, and (5) the measurement gap. Each becomes a post. The planning horizon post opens: "Most editorial calendars fail because they are planning documents pretending to be publishing systems." The rest of the post unpacks that tension. The question at the end: "What is the longest your team has consistently followed a content calendar before it collapsed?" The other four posts follow the same structural logic with different opening tensions.

Format requirements

  • 1,300 character limit for most posts
  • First 2 lines must create tension or intrigue
  • No external links in post body (add to comments)
  • Single clear argument per post

Common mistakes

  • Summarizing the article instead of extracting one idea
  • Using the article's title as the hook
  • Ending with a link to the full article
  • Publishing all five posts in the same week

Sequencing note

Space posts two to three days apart. The fifth post can reference the earlier ones explicitly — by that point, followers who saw the earlier posts will recognize the thread.

Framework 02

Newsletter Extraction from Long-Form

What this framework does

A newsletter is not a summary of your article. It is a complete reading experience delivered to an inbox, where the reader has opted in for editorial voice and contextual depth. This framework extracts one section of a longer piece and expands it into a self-contained newsletter issue — with its own opening, its own context-setting, and its own conclusion.

The extraction steps

1
Identify the section with the most editorial depth.

Not the most important section — the one with the most texture. The section where you had the most to say, where the argument was most nuanced, or where you cut content for length. That section has the most to give in a newsletter format.

2
Write a new opening that assumes no context.

Newsletter subscribers may not have read the original article. The opening paragraph needs to establish the topic, its relevance, and the perspective you are bringing — without referencing the original piece at all. Write it as if the original does not exist.

3
Expand what the article compressed.

Articles often compress nuance for length. In the newsletter, restore that nuance. Add the example you cut. Develop the counterargument you dismissed in one sentence. The newsletter reader is expecting depth — the format rewards it.

4
Close with a genuine observation, not a link.

Newsletter closings that perform well tend to end with an observation or a question that lingers. A link to the full article can appear in a postscript, but it should not be the structural destination of the piece. The newsletter should be complete without it.

Format requirements

  • 600 to 900 words for most issues
  • Single topic, single argument
  • Conversational but substantive voice
  • Subject line written as a tension statement

Platform context

Substack, Beehiiv, and ConvertKit each publish creator benchmark data. Single-topic issues consistently show stronger click and reply rates than multi-section digests in professional niches. Check current platform reports for updated figures.

Framework 03

Written Research to Podcast Script

Why the rewrite is non-trivial

Audio listeners cannot re-read a sentence. They cannot skim. They follow a linear experience and process information in real time. This means written structure — which often relies on headings, visual hierarchy, and the ability to scan — fails almost completely when read aloud. The podcast script is not a read-aloud of the article. It is a different document that carries the same research.

The extraction steps

1
Convert structure to verbal signposting.

Every heading in the article becomes a spoken transition. "Now I want to talk about..." or "Here is where it gets interesting..." These verbal signposts do the work that visual hierarchy does on a page. They are not optional — without them, audio listeners lose orientation quickly.

2
Shorten sentences. Then shorten them again.

Written prose can sustain complex sentence structure because readers can pace themselves. Spoken word cannot. Every sentence in the script should be speakable in one breath. Complex ideas get broken across multiple short sentences. Read it aloud as you write it — if you run out of breath, rewrite it.

3
Replace abstract data with spoken context.

A written article can include a precise percentage. In audio, that number needs context immediately, in the same breath: "LinkedIn's own published data shows that document posts — that is, native PDF-style uploads — get significantly higher organic reach than posts that include external links. We are not talking about a marginal difference." The listener cannot check a footnote.

4
Open with a question the listener is already asking.

Podcast retention data consistently shows that episodes retain listeners when the first sixty seconds make clear exactly what question the episode answers. Not what topic it covers — what specific question it answers. Take the article's central argument and reframe it as a question the listener would actually ask themselves.

Script structure

  • Cold open (0-60 sec): the question
  • Context (60-180 sec): why it matters now
  • Main content: the article's argument, restructured
  • Close: what to do with this information

Length note

A 1,500-word article typically becomes a 12 to 18 minute episode. Speaking pace averages around 130 words per minute for clarity. Script accordingly — do not try to fit the full article into a 5-minute format.

Framework 04

Identifying Infographic Potential in Written Content

Not all content translates visually

The first step in infographic extraction is deciding whether the content is actually visual. Arguments that depend on nuance, narrative flow, or contextual reading rarely work as infographics. Content with clear comparisons, sequential processes, or hierarchical structures translates well. This framework starts with that diagnostic before touching any design tool.

Visual potential diagnostic

1
Look for process, comparison, or hierarchy.

Does the article describe a sequence of steps? A comparison between two or more approaches? A hierarchy of concepts? Any of these structures translate directly to a visual format. Narrative arguments, opinion pieces, and nuanced analysis generally do not.

2
Extract the skeleton, not the flesh.

An infographic carries the structural logic of the content, not the explanatory text. Pull only the labels, the sequence numbers, and the core terms. If the infographic requires more than eight words per element to make sense, the content may not be ready for visual format — or the extraction needs to go deeper to find simpler underlying structure.

3
Design for a specific sharing context.

An infographic designed for Pinterest has different dimensions, density, and label size than one designed for a LinkedIn document post. Before touching layout, decide where the infographic will live — that determines every design decision that follows.

Visual types by content type

  • Process content → flowchart or step diagram
  • Comparison content → side-by-side table
  • Hierarchy content → pyramid or tier diagram
  • Timeline content → horizontal or vertical timeline
  • Relationship content → network or Venn diagram

Platform sizing

  • Pinterest: 1000 x 1500px (2:3 ratio)
  • LinkedIn document: 1080 x 1080px per slide
  • Blog embed: 800px wide, variable height
  • Email: 600px max width
Framework 05

One Research Piece, Three Months of Content

The sequencing logic

Publishing atomized content without a sequencing plan produces disconnected outputs that do not build on each other. This framework maps the outputs from a single research piece across a twelve-week calendar in a sequence designed to create narrative momentum — where each output references or extends the previous ones.

Month 1: Establish the idea

Week 1 Publish the source article on your owned platform
Week 2 LinkedIn post 1 (the counterintuitive hook)
Week 3 Newsletter issue (deepest section of the article, expanded)
Week 4 LinkedIn posts 2 and 3 (process angle, data angle)

Month 2: Extend and visualize

Week 5 Infographic (process or comparison section of the article)
Week 6 LinkedIn post 4 (shares the infographic, references the article)
Week 7 Podcast episode (full article, restructured for audio)
Week 8 LinkedIn post 5 (references the podcast, closes the thread)

Month 3: Resurface and synthesize

Weeks 9-10 Gap fill: respond to questions from LinkedIn comments with mini-posts
Week 11 Newsletter issue 2 (reader responses and updated thinking)
Week 12 Updated article or companion piece — beginning the next cycle

Why sequencing matters

Audience members who see the newsletter are more likely to engage with the LinkedIn post that references it. The podcast episode reinforces the ideas from both. Each output adds context to the others, creating a content ecosystem rather than isolated pieces.

Scaling this framework

With four source articles per quarter, you have the foundation for a full year of content across all channels — without starting from scratch at any point. The research investment compounds rather than getting spent once.