Human Center of Mass
Anchor AI amplification to a valuable human-created core.
- Difficulty
- Moderate
- Time to result
- ~months to results
- Steps
- 6
- Confidence
- 97%
The Human Center of Mass model separates the valuable core of a content operation from the automation surrounding it. The center might be a live show, expert interview, original analysis, distinctive performance, or another human experience worth paying attention to. A team first makes that primary asset genuinely strong through expertise, effort, taste, and access. AI is then applied around the center to research supporting material, generate clips, draft newsletters, repackage insights, and distribute derivative content. This produces both quality and quantity without asking automation to manufacture the underlying reason audiences care. The mechanism is multiplicative: automation amplifies the value already present, so a weak or empty center remains weak regardless of how much content is generated.
Origin
Extracted from Marketing Against the Grain. Riley Brown uses the internet-first show TBPN to explain why a valuable human production should sit at the center of AI-powered content amplification.
Core principles
- 01Create genuine value before automating distribution.
- 02Keep human taste at the center of the work.
- 03Use AI to scale quality rather than replace it.
- 04Automate derivative work around a strong source asset.
- 05Multiplication cannot rescue a worthless core.
How to run it
- 1
Define the human core
Identify the expertise, access, performance, relationship, or original work that gives the primary asset value. State why a real audience should care about it without mentioning AI.
Pro tip Choose a core that would remain worthwhile even if no derivative content were produced.
Watch out A generic premise gives automation nothing meaningful to amplify.
- 2
Build the primary asset
Create the show, interview, report, event, or analysis with strong human judgment and production standards. Focus first on substance and audience value.
Pro tip Concentrate scarce human effort where taste and authenticity matter most.
Watch out Do not reduce core quality merely to publish more frequently.
- 3
Validate attention
Look for evidence that the core resonates, such as retention, thoughtful responses, repeat viewing, or qualified audience growth. Diagnose weak value before adding volume.
Pro tip Use signals of genuine attention rather than raw output count.
Watch out Automating distribution can disguise but cannot fix an unwanted core asset.
- 4
Map the amplification layer
List repeatable derivative outputs that can carry the core value into additional formats and channels. Examples include clips, newsletters, summaries, research packs, and social posts.
Pro tip Trace every derivative asset back to a specific valuable moment or idea in the source.
- 5
Automate the boring work
Use AI for repetitive retrieval, formatting, editing, repackaging, and distribution while retaining human approval over taste-sensitive decisions. Preserve the qualities that made the original asset valuable.
Pro tip Automate preparation and transformation before automating final judgment.
Watch out Scaling low-quality derivatives can damage the reputation of the core.
- 6
Reinvest in the center
Use the capacity gained through automation to improve guests, research, production, insight, or frequency at the core. Treat amplification as support for the human asset rather than its replacement.
Pro tip Measure whether automation creates more time for high-value human work.
In the wild
A team produces a substantial live show with strong guests, multiple cameras, and sustained human conversation. Once the program has earned attention, AI systems extract clips, draft newsletters, and distribute supporting content across the internet.
→ The team increases reach and publishing volume while the original human show remains the source of value.
An analyst publishes a deeply researched monthly briefing with original conclusions. AI then produces chart captions, short summaries, email variants, and social excerpts, all of which link back to the primary report and receive human review.
→ One differentiated research asset supports many distribution formats without diluting its analysis.
Common mistakes
Amplifying nothing
A large automated distribution system cannot compensate for a primary asset that lacks substance or audience value.
Replacing the source of taste
Letting AI make every subjective decision removes the expertise and sensibility that differentiated the work.
Trading quality for quantity
More assets are useful only when they preserve the quality that earned attention in the first place.
Is it for you?
Best for
It is best for creators and marketing teams that have strong expertise, access, taste, or original source material to amplify.
Not ideal for
It is not ideal for organizations seeking fully autonomous content without a differentiated human contribution.
From the transcript
“And so that's their human center of mass.”
“But, if you don't have that thing that's valuable at the center, then you're just going to be amplifying nothing.”
“If the first number is zero, then no matter what you multiply it by, it's still going to be zero.”
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