MMarketing Against The Grain
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MarketingNathan Labenz

Create Once, Transform by Medium

Create the original insight yourself, then use AI to adapt it for each channel.

Difficulty
Easy
Time to result
~days to results
Steps
5
Confidence
96%

Create Once, Transform by Medium separates original thinking from content adaptation. The creator first develops a high-quality canonical artifact—such as a Twitter thread—using current knowledge, firsthand experience, and personal judgment. Once satisfied with the substance, the creator gives the complete artifact to an AI and requests versions designed for specific channels, such as a blog post or LinkedIn post. The larger context window helps the model retain the source's argument while changing structure, length, and presentation. Human review then protects the original point of view and removes distortions. This workflow increases publishing volume without replacing the source insight with generic model-generated material, and it avoids the weak practice of pasting identical content into channels with different audience expectations.

Origin

Nathan Labenz described this division of labor for repurposing his AI analysis threads during Marketing Against The Grain.

Core principles

  • 01Original insight and point of view come before automation.
  • 02A finished source artifact gives the model reliable context.
  • 03Each medium requires a distinct format rather than a direct paste.
  • 04AI is strongest at transformation when it does not need to invent the thesis.

How to run it

  1. 1

    Create the Canonical Piece

    Write and refine the original artifact using your own expertise, experience, and point of view.

    Pro tip Choose the medium in which you think most clearly.

    Watch out Do not ask the model to manufacture personal experience.

  2. 2

    Lock the Core Meaning

    Identify the thesis, essential evidence, tone, and claims that every adaptation must preserve.

    Pro tip Include these requirements alongside the source artifact.

  3. 3

    Choose One Destination

    Define the next channel and its native conventions, audience, and length constraints.

    Pro tip Adapt one medium at a time for greater control.

    Watch out A generic request to repurpose everywhere produces generic output.

  4. 4

    Generate the Transformation

    Ask the AI to recast the approved source for the destination without adding unsupported claims.

    Pro tip Supply the entire source when the context window permits.

  5. 5

    Review and Publish

    Verify fidelity, restore personal phrasing, and approve the adaptation before publication.

    Pro tip Compare every major claim against the canonical artifact.

    Watch out Fluent output can still subtly change the creator's position.

In the wild

Thread to Blog and LinkedIn

An AI analyst writes a current, opinionated Twitter thread without model assistance. After approving it, he supplies the thread to GPT-4 and requests a structured blog post and a concise LinkedIn version, preserving the analysis while changing the presentation for each audience.

One piece of original thinking supports several native channel assets with much less reformatting work.

Common mistakes

Outsourcing the Thesis

When the model lacks current information or firsthand experience, asking it to create the core argument produces generic or inaccurate content.

Copying Without Adapting

Pasting the same artifact into every channel ignores differences in audience, structure, and reading behavior.

Skipping Fidelity Review

The transformed version may introduce claims or emphases the creator never intended.

Is it for you?

Best for

Experts and creators with strong original material but limited time to reformat it for multiple platforms.

Not ideal for

Creators who lack a substantive source artifact and expect AI to invent a credible personal perspective.

From the transcript

So oddly enough, I don't really use AI at all in writing my threads.

Nathan Labenz · 28:30

So it should allow me to do more, you know, it should be helpful in my content creation, but I'm not expecting anything this year…

Nathan Labenz · 29:30

It's going to be more about transforming it after it's created.

Nathan Labenz · 30:00

From the episode

GPT-4 Beta User Reveals What Jobs It Will Destroy In 2023 with Nathan Labenz (#103)

Nathan Labenz