8d (edited) • Intro's & General Discussion
Breaking Down Russell’s New Content Machine (Pt. 3)
Looking back at Russell Brunson’s job post, (and my last two posts) there’s a pattern that’s hard to ignore.
“Rapidly test ideas. Publish frequently. Scale what works.”
“Use AI tools daily to move faster and produce more.”
Move faster. Produce more. Use AI daily.
In Post 1, I said the bottleneck moved.
In Post 2, I showed why more output doesn’t mean more results.
(Catch up here: https://www.skool.com/prime-mover/breaking-down-russells-new-content-machine-part-2?p=433a9fa5)
Because the underlying AI content arms race happening right now isn’t actually more and faster output. It’s more optimized content.
Everyone starts getting better at the same things.
- improving their hooks
- tightening their edits
- refining their scripts
- repurposing more efficiently
And they’re all doing it with the same tools, because remember, AI allows faster iteration.
The assumption is:
👉 If I optimize faster than everyone else, I’ll win.
But that only works if you’re optimizing in a unique direction.
The problem is… most people aren’t.
They’re improving the same variables, in the same way, with the same inputs, with the same LLM advice.
Everyone is racing to the middle.
You get more of the same content—just executed more efficiently, but without the competitive edge that came more naturally when you slogged out your own content.
Now, here’s something I noticed that I haven’t seen many people talk about, outside of perhaps art:
AI doesn’t create originality, it rehashes what already works.
So when you use it to optimize content:
- it reinforces existing patterns
- it prioritizes familiarity
- it reduces variation over time
Which means the more you optimize… The more your content starts to look like everything else.
👉 I’m gonna go ahead and flag this as the AI version of the Echo Chamber effect we were seeing in social media 10 years ago.
So, returning to this topic of Russell’s (and most brand’s AI Content systems), the focus is still:
- faster production
- better formatting
- higher engagement signals
But not:
- what leads to trust
- what leads to decisions
- what leads to revenue
The reason this is still happening is because no one is paying attention to the feedback loop between content output and results.
When content people go from looking at engagement for 1-5 posts a day, to 20-50 posts a day, it’s understandable that they get lazy.
So yes, content production is seeing its industrial revolution. It’s all faster, sharper, more efficient.
But they’re all moving in the same direction, and that’s the trap:
It’s that optimization, by itself, doesn’t tell you what’s worth optimizing.
And until you can answer that… getting better at content won’t change the outcome.
👉 Only how fast you get to where everyone else is going.
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Breaking Down Russell’s New Content Machine (Pt. 3)
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