@ShadeSpecter
Account based inBrazil
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Youtube twentyforseven
Joined December 2017
- Tweets854
- Following118
- Followers19
- Likes1.1K
Sean retweeted
the middle of your script is where 60% of your audience disappears.
and no amount of editing tricks, music changes, or b-roll swaps will fix it. because the problem is structural rather than visual. the script flatlines at the 2-3 minute mark because the hook energy has faded and nothing has replaced it. the framework eliminating mid-script drop-off entirely is below...
i call it nested tension loops and it's the strongest retention technique i've found across 8,000+ scripts.
the concept is simple. 9 out of 10 scripts run 1 storyline. they open with a hook, deliver information linearly, and close with a payoff. a single thread of tension has a natural decay rate: the hook creates interest, by minute 2 that interest has faded, and by minute 3 the viewer is checking their phone.
nested tension loops stack multiple threads of tension simultaneously. the viewer is tracking 2 or 3 unresolved questions at once. and the key: you resolve 1 loop while OPENING another. the viewer never reaches a natural exit point.
how it works in practice:
loop 1 (the anchor): the primary question established in the hook. "what happened in this room?" this loop stays OPEN for the full video. it's the thread that carries the viewer from start to finish.
loop 2 (the reveal): a secondary question introduced at the 2-minute mark. right when loop 1's tension would naturally start decaying, loop 2 injects new tension. "but what they didn't know was that the person on stage was lying."
loop 3 (the backstory): a tertiary question introduced at the 4-minute mark. this one provides context that reframes BOTH previous loops. "the real motive behind everything that happened was a power struggle that started 4 years earlier."
the viewer is now tracking 3 unresolved threads simultaneously. their cognitive investment is 3x what it would be in a linear script. and the part making this framework so effective is this:
you resolve loop 2 at the 6-minute mark. the secondary question gets answered. the viewer gets a micro-payoff. but loop 1 and loop 3 are still open. the payoff from loop 2 actually INTENSIFIES the tension on loop 1 because the new information changes what the viewer thinks the answer will be.
you resolve loop 3 at the 8-minute mark. the backstory completes. another payoff. but loop 1 is still open. and now the viewer understands the FULL context, which makes the resolution of loop 1 even more anticipated.
loop 1 resolves in the final 90 seconds. the grand payoff. and because the viewer has been carrying this question for the entire video, layering context and revelations on top of it, the resolution hits SIGNIFICANTLY harder than it would have in a linear script.
the retention curve on a nested tension loop script doesn't decline, it holds flat through the middle and SPIKES near the end. the inverse of what most faceless channels see.
how to build this for YOUR niche:
the framework is structure-specific rather than niche-specific.
for a business breakdown: loop 1 is "how did this company go from dominant to bankrupt?" loop 2 is "the internal decision that doomed them was hidden from the board." loop 3 is "the person who made the decision was the same person hired to prevent it."
for a science explainer: loop 1 is "this experiment produced results that shouldn't be possible." loop 2 is "the researchers initially thought their equipment was broken." loop 3 is "the broken equipment hypothesis collapsed, and the implications are bigger than anyone expected."
for a gaming documentary: loop 1 is "this player was about to make esports history." loop 2 is "the team behind him was falling apart during the tournament." loop 3 is "the organisation knew and chose not to intervene."
the build rule: every time you introduce a new loop, the previous loop's tension should INCREASE rather than hold steady. the new information reframes the old question. the viewer's prediction model keeps getting disrupted. and every disruption deepens their investment.
this technique is baked into every script format inside the FacelessOS skill files. the AI builds nested loops automatically based on the niche and format you declare.
DM me "SCRIPTS" if you want to see how nested loops would work in your niche
haris
Sean retweeted
some people still underutilize the collab feature 😂 go crazy with it as long as it works that well.. check this guy out
Sean retweeted
🧵 Almost NO ONE knows these old Youtube Exploits.......
Disclaimer: I no longer use any methods which violate the YPP this post is PURELY for educational and entertainment purposes.
Low Key this is the most overkill combo right now to skyrocket your YouTube business.
(no promo, no affiliates, no favoritism, just objectivity.)
Proxy Setup: @TubeProxiess
Good TrustScore Channels: @algrow_online
Editing: @vidrush
Ideation: @nexlevio MCP + @claudeai
Sell Digital products: @gumroad
Finding winning niches: @algrow_online + @nexlevio
Making digital products, research and data: @claudeai
Scripts: @ChatGPT or @claudeai Opus 5.5 (Goated)
Thumbnails: I will prob recommend Nano Banana Pro but GPT Image 2.5 is very good as well.
Goated Coaching Programs (if you want to make $100k+ /mo fast) you need some experience and money ofc this is not for people who start from 0: @wizofYT or @thomaas & @carl_pisano_
I just sorted out your Q4. This tweet alone is an entire YouTube Automation 101 course.
Sean retweeted
This guy literally explained why some people become successful… while others stay average.
And the reason is uncomfortable.
It’s not just hard work.
It’s not luck.
It’s Game Theory.
Once you understand this, you’ll start seeing the “game” behind success differently.
Watch this. 👀
Sean retweeted
You spend 2 weeks producing a perfect first video for a new channel.
The upload gets 12 views, so you blame the niche, the title, the thumbnail.
Wrong. The channel could’ve been dead before you uploaded anything, and there's a 10 minute test that would've told you:
Some channels are born suppressed, and content has nothing to do with it.
What happened at birth does:
→ The IP the channel was created on
→ The phone number and recovery email attached to it
→ The sign-up fingerprint and the Wi-Fi behind it
YouTube scores all of it before your first upload exists.
A MrBeast-level video with zero impressions gets pushed to NOBODY. Nobody outproduces a dead channel.
So before investing a single production hour, run the warm-up test:
1. Record something with zero effort and zero context. Walking through your city on your phone. Unedited.
2. Title it like a normal human. "Walking in Limassol." No keywords, no strategy.
3. Upload and wait 72 hours.
4. Open the impressions number. That's the whole test.
The first upload is where YouTube shows its hand.
The algorithm throws a probe audience at every new channel to see what it is.
A healthy channel gets thousands of impressions ON A NOTHING VIDEO. A flagged channel gets crumbs.
The reading:
Under 500+ impressions after 72 hours = born suppressed. Don't fight it. Burn it, fix the infrastructure it was created on, rebuild clean.
Over 500 of impressions on a context-free clip = YouTube trusts this channel. Now it deserves your production budget.
Live example. A channel called The Senior Traveler launched a month ago.
First upload: a shaky phone clip titled "Struggling to set up my phone | Quick trip to Dumaguete."
239 views.
Sounds pathetic until you run the numbers.
A throwaway clip like this converts roughly 0.1% of impressions into clicks.
239 views at 0.1% means YouTube pushed it to roughly 2k+ feeds. On upload ONE.
Second real upload: 292k views. Channel's at 19.9k subs in a month.
The test called it before a single real video existed.
Ten minutes of walking versus two weeks of production on a corpse. Run the test first, every channel, every time.
Sean retweeted
the part of training claude on your youtube scripts that most people leave out:
you need it to explain what the winners have in common before it writes the next one
give it 10-15 strong reference scripts from the channel or niche. then use this:
"Read every reference. Build a writing SOP for this channel. Show me the recurring opening structure, how each script moves between topics, the sentence style and the approximate length. For every rule, point to examples in the references. Keep one-off details out of the rules."
check the SOP against the videos yourself. if it found a pattern that isn't actually there, fix that before generating 20 scripts with it
then have claude code build the script generator around those files. same context every time, a brief for the new video, and bulk generation when you need it
this is the setup i'd save, not another folder of random prompts
Sean retweeted
So YouTube added another watch metric called Views (Co-viewed). This expands the many ways a view is being calculated.
Engaged views, which calculate a viewer after a certain number of seconds.
Co-viewed views, which estimate the total number of views, including multiple people watching together.
Views, which is the total number of first-frame impressions.
In my opinion, this is great for the analytics nerds (people like myself), even though it may confuse the average user trying to figure out which metrics they should pay attention to.
Sean retweeted
People would rather talk than do.
If you just “do” aggressively for a long duration, you’ll almost certainly win.
Doing is usually less fun than talking which is why few sustain the doing.
Being able to trick yourself into loving the “doing” is the single factor that dictates success.
Btw, content is popular because it allows people to make talking and doing the same thing.
Sean retweeted
There's SO much money on Reddit
Add "/.json" at the end of ANY Reddit link
> You get the entire thread as JSON
> All replies included
> Every comment, upvote, metadata
Now feed that into an LLM
If you're making a video about the latest Stranger Things episode for example...
> Go to the r/StrangerThings thread
> Add /.json to the URL
> Feed it to ChatGPT/Claude
> Extract top theories, reactions, what people are saying
> Use it as context for your script
Sean retweeted
Full Tutorial How To Start AI Avatar channels from SCRATCH!
Sean retweeted
YouTube just released a video explaining their algorithm. Here are 50 lessons from this video:
1. YouTube says recommendations are generated based on what it knows about a viewer and their current context. Current context could be factors such as viewing history, time of day, and device type.
2. YouTube says it doesn’t just take a video and try to find an audience for that video. Instead, it starts with a viewer and asks which videos are best for that video at that specific moment.
3. YouTube says a video can have very strong overall metrics (such as ctr and avd) while still being a bad recommendation for a particular viewer.
4. YouTube says a video isn’t initially testing against your subscribers.
5. YouTube says some channels could receive the majority of their viewers from non-subscribers, even shortly after the video being uploaded.
6. YouTube says it can learn that subscribers may not like a video while non-subscribers do.
7. YouTube says it does not decide whether a video is good or bad for everyone based on its early audience response.
8. YouTube says creators tend to overfocus on the first few hours of their analytics. And I couldn’t agree more with this statement.
9. YouTube says a viewer may need to be shown the same video multiple times before they decide to click on it. Often, more than 5 or 6 times even.
10. YouTube says it has experimented with limiting how many times the same video can be recommended to someone.
11. YouTube says context can determine what videos get shown, such as prioritizing a longer video when someone is watching from their TV in the evening.
12. YouTube says its algorithm tries to focus on the long-term value for a viewer.
13. YouTube says there’s no individual metric which determines a video’s success.
14. YouTube says click-through rate often decreases as a successful video reaches a broader audience.
15. YouTube says watch time is important, but doesn’t assume that every minute watched actually represents value.
16. YouTube says it considers both absolute and relative watch time. For those who aren’t too aware of what this means. Absolute watch time is the total amount of time someone spends watching a video, while relative watch time is the total amount of time someone spends watching a video relative to its length.
17. YouTube says satisfaction surveys are used because other metrics alone can’t tell whether viewers actually enjoyed the video.
18. YouTube says, and this one is important, that there’s no universal weighting where one metric has the same importance for every viewer.
19. YouTube specifically recommends looking at retention graphs to understand where viewers are dropping off (You can image how much I smiled when a heard this, for those who don’t know me, I’ve been obsessed with retention knowledge for years)
20. YouTube says turning comments off is not supposed to cause the recommendation system to penalize your videos.
21. YouTube says it tries not to interpret the lack of comments as evidence that viewers don’t like the video.
22. YouTube says the recommendation system is designed not to make decisions based on a single factor.
23. YouTube says turning ads off reduces your video’s reach.
24. YouTube says the algorithm is not trying to assign your entire channel to one topic category.
25. YouTube says it doesn’t deliberately push longer videos simply because it wants longer content getting more views.
26. YouTube says the change in performance for longer viewers is driven by viewer preferences.
27. YouTube believes short-form video became successful because it reduces the decision a person needs to make when choosing what to watch. I’m saying believe because it’s a hypothesis, a hypothesis that I believe is fair to make.
28. YouTube says increasing thumbnail size and showing less videos on desktop increase overall engagement with long-form content.
29. YouTube says it would not have launched the homepage redesign if its experiments had shown that it reduced viewership.
30. YouTube says they’re running hundreds of experiments on the platform at any given moment.
31. YouTube says people sometimes think temporary experiments are permanent changes.
32. YouTube says one off-topic video blowing up does not mean the algorithm is suddenly confused about your channel.
33. YouTube says the decision to create a second channel should be based on whether the content serves the same general audience.
34. YouTube says if two types of content offer different value propositions to different audiences, you should probably consider a second channel.
35. YouTube says its recommendation system can connect audiences between two separate channels when the same viewers watch both channels.
36. YouTube says even when unrelated content is uploaded on the same channel, it can distinguish which videos a viewer may care about.
37. YouTube says a viewer who watched only your short-form videos doesn’t necessarily get your long-form videos recommended. This is in-line with my own findings on viewer conversion being extremely low between formats, often reaching 0.2% or lower.
38. YouTube says a viewer who likes only one topic on your channel, can increasingly only be served that specific topic from your channel.
39. YouTube says creators should plan content around different audience groups instead of assuming their entire audience is one homogeneous group. The way I explain it to creators is: the viewer composition from one video may completely differ from the composition from another video, even though the performance looks the same.
40. YouTube says data from your subscription feed is often better to look at because it's a more controlled subset of your audience. I agree and disagree on this one, because it may also be a limited subset of your audience, so there’s nuance involved with this one.
41. YouTube says viewers regularly watch content from hundreds of channels that have little topical overlap to one another.
42. YouTube says a brand-new channel does not need existing viewer history for its videos to get recommendations.
43. YouTube says it actively tracks whether creators are succeeding and growing through the ecosystem. I can say that they definitely do, sometimes at the benefit of big creators, sometimes at the benefit of smaller creators.
44. YouTube says it actively tracks whether creators are earning enough revenue to system themselves. This is an interesting one which I haven’t heard them talk about, even in private conversations so I’d be curious to know how they’re doing this.
45. YouTube says bad retention from an external viewing source doesn’t automatically mean that performance should hurt the video on the homepage. This aligns with the advice that you can actually link your content to groups you know for some initial traffic, as long as this group would actually enjoy your content.
46. YouTube says homepage recommendations mainly care about how a video performs in the homepage context. We can actually notice this with shorts. When shorts have better thumbnails, they perform better through browse versus when they don’t have thumbnails.
47. YouTube explicitly gives advice to not disable subscriber notifications in an attempt to improve algorithm performance. They even state that it could prevent connecting your upload to people who would have watched it. Also, at the beginning of the interview they also state that this is the only way to guarantee your content being pushed to your audience.
48. YouTube says subscribing to a channel is a weaker signal of future viewing than most creators assume.
49. YouTube says creators often underestimate how many other channels their own fans regularly watch.
50. YouTube says that you should comment under this post so it reaches more people and so I’m more likely to re-appear in your feed. While I’m half-joking, it does help and my goal is to always spread as much of this information as possible to others.
Hope you enjoyed this long summary.
Sean retweeted
Real talking head channels are underrated asf.
Just copy faceless niches, hire a presenter and boom
You can now edit talking head videos with 1 click.
With vidrush talking head Beta
drop in raw talking head footage and get a fully edited video back with motiongraphics, sound design & More.
If you're a youtuber who wants to try it out for free reply with your use case and we *might* shoot over a coupon code!
Sean retweeted
my channels do six figures in profit every month and claude writes every script
here's the exact prompt:
"here's a transcript from a video that did [views] in my niche: [paste transcript]
write a new script based on it:
- take as much inspiration from it as possible: the structure, the pacing, the facts, the hooks, the exact reasons it performed
- the only rule is no copying sentences word for word
- put the payoff in the first 15 seconds
- write for listening, not reading. short sentences
- end every section with an open loop into the next one"
bookmark this for later
Sean retweeted
My favourite way of learning new ways to grow or scale your business is to describe to Claude or ChatGPT the exact situation your company is in.
And then ask it to find similar case studies that other successful entrepreneurs or companies navigated through successfully and then study those companies or approaches.
Works much better then listening to podcasts or doomscroll business content on IG.