rollingwaves231

[rollingwaves231 @rollingwaves231]

@johnvirality loop

[John @johnvirality]

i've been running Sonnet 5.5 + Jev scoring + Higgsfield + Capcut MCP as ONE closed loop instead of a pile of tools...

and it has been ABSOLUTELY cooking

most people open a chat window, ask for 10 tiktok ideas, make one, do 400 views, then decide AI content doesn't work

generation was never the bottleneck. it's the cheapest part of the process and everybody optimised it first

so i documented the ENTIRE machine...

covering research, ICP excavation, idea scoring, image gen, video animation, the edit layer, distribution, and the feedback loop that makes next week's batch smarter than this week's

here's what's inside the guide:

→ the context engine that makes every downstream prompt actually work

(sales calls, DMs, support tickets, closed-lost notes, 90 days of analytics. the system tells you what context it's MISSING, which is usually how you find out your positioning is vague)

→ ICP excavation that builds your hook library from your customers' mouths

(verbatim quotes mapped to pain, failed solutions, objection, awareness stage. any phrase appearing in 3+ separate conversations gets flagged as a probable hook)

→ the research layer: platform scrape + adjacent market mining + competitor gap teardown

(your competitors are all watching each other. the formats that feel fresh in your category were invented in a different one. this prompt steals the mechanics, not the topics)

→ the scoring layer that decides what deserves production

(50 ideas scored across viral, business and execution dimensions. you produce the best 5 of 50 instead of the first 5 you thought of, for the exact same production cost. the part everyone skips)

→ the sonnet 5.5 x gpt images 2.0 x seedance 2.5 x higgsfield production stack

(consistency lock built once and pasted into every prompt. character reference locked across every shot AND every video in the batch. broken renders flagged and regenerated automatically)

→ the capcut MCP edit layer, because editing is retention not polish

(cut on action never after it, no shot over 2.5s in the first 6 seconds, word-by-word captions, hook in frame 1, CTA in the final 2 seconds)

→ the closed-loop feedback system that compounds

(post-mortem names the exact second retention dropped, winners get doubled down on with one variable held constant, context file updates every week. week 12 you're generating from your own performance history instead of guessing)

19 prompts. written out in full. copy-paste and run.

all backed by what i've seen running distribution for 200k+ creators and watching which clips actually convert to installs

like + comment "LOOP" and i'll send the whole protocol over

(must be following + RT for priority access)

will stop sending in 24hrs...

[Zack (Paid Ads Specialist) @zackpaid]

i just said fuck it and gave away the entire meta ads course for FREE after generating $12m+ for clients so far

10 modules. 3 hours 54 minutes. 4 documents.

start to finish.

how meta actually works now, and exactly what to do about it in your account.

everything we run in client accounts spending $1m a month.

comment "COURSE" and drop a follow.

rt for priority access

[rollingwaves231 @rollingwaves231]

@zackpaid COURSE

[rollingwaves231 @rollingwaves231]

@alexolim_ CREATORS

[rollingwaves231 @rollingwaves231]

@alexolim_ PLAYBOOK

[rollingwaves231 @rollingwaves231]

@chancl3x Sauce

[rollingwaves231 @rollingwaves231]

@johnvirality 100

[John @johnvirality]

claude fable 5 just made it possible to post 100 AI UGC videos per day across 4 platforms in JUST 30 minutes of production

everything else runs 100% autonomously

clippers might be cooked 😭

this mythos model watches raw video footage and finds viral moments transcripts would miss

it scrolls tiktok while you sleep and builds trend reports, generating 100 production packages and renders them through higgsfield MCP without you touching another tab.

so i documented the ENTIRE machine with every prompt, every setup instruction, and every workflow step

here's what's inside:

→ the overnight market research system that runs while you sleep

(cowork scrolls 5 platforms, analyzes 60-80 pieces of content each, returns a trend intelligence report with 10 specific content ideas by the time you wake up)

→ raw-pixel clip identification that finds moments human clippers miss

(facial expression shifts, product reveals, body language peaks, visual incongruities. all timestamped and ranked by predicted virality.)

→ batch script and asset generation: 20 complete production packages per prompt, run 5x for 100 total

(6-shot scripts, character prompts, product frame prompts, voice direction, platform captions. 15-25 minutes total.)

→ the higgsfield MCP pipeline that renders all 100 videos automatically

(fable 5 calls seedance 2.0 directly. character reference locked. lip sync aligned. zero human involvement.)

→ the virality predictor that filters your top 20 candidates before posting

(hook score, hold rate, brain region activation. bottom 5 get diagnosed and revised automatically.)

→ the CPM math: 400 platform-posts/day × 3,000 avg views = 36M views/mo = $180k/mo at $5 CPM

→ all 6 copy-paste prompts that run the entire machine

all from my personal experience in looking behind the scenes on how Rizz App + Looksmax AI + Memix scaled past 7-figures with this method

like + comment "100" and i'll send you the ENTIRE system

(must be following + RT for priority access)

will stop sending these out in 24h...

[rollingwaves231 @rollingwaves231]

@mrbrandowner MRR

[Brandon @mrbrandowner]

Most Ecom operators are doing good numbers

But they can't tell you what next month looks like

I started doing MRR and filmed my entire playbook

$2.4M/month. Supplement brand. MRR.

Here's what's inside the video:

- Why one-time purchase brands always reset to zero
- The subscription architecture nobody is teaching properly
- How to find a winning product before you spend a cent
- Billing cycles, cancel flows, churn reduction (the full backend)
- The creative engine that scales without burning out
- How your MRR compounds so your revenue goes up every month

This is the thing I wish existed when I started.

Like, RT, comment "MRR" (must follow) & I'll DM you the link

[rollingwaves231 @rollingwaves231]

@Peter_Quadrel AI

[rollingwaves231 @rollingwaves231]

@demeteralexx COPY

[rollingwaves231 @rollingwaves231]

@ig_claims META

[Zack (Paid Ads Specialist) @zackpaid]

after generating $10,000,000 with meta ads funnels

I’ve condensed EVERYTHING I learned about them into a 48 laws doc

like + comment “META” and I’ll send you access to it

(must be following + RT for priority access)

[rollingwaves231 @rollingwaves231]

@blvckledge swipe

[rollingwaves231 @rollingwaves231]

@nicktheriot_ NICK

[rollingwaves231 @rollingwaves231]

@EddChalk @TimpanoDante CLOUT

[Edd Chalk @EddChalk]

My OpenClaw ships banger ad briefs while I sleep.

Production-ready briefs. Scored. Validated through a QA skill tree.

And I am going to show you how to set it up in return for a little bit of clout

Here's what's actually running while I'm asleep.

OpenClaw has a skill graph. Three AI agents connected in sequence — each one feeds the next, and nothing moves forward until it passes.

The first agent is pure research. It's scraping the Meta Ad Library pulling 5–10 active competitor ads, extracting repeating hooks, mapping visual patterns, documenting copy structures, and analysing CTA approaches (offer vs urgency vs curiosity).

At the same time it's running Golden Pain Extraction — pulling verbatim emotional language from Amazon 3-star reviews, Reddit threads, TikTok comments on competitor videos, and customer service logs. Not summaries. Exact words real customers used. Each pain gets tagged and mapped to one of the 8 Life Force drives.

Then it runs an asset audit — lifestyle product shots, founder content, UGC, testimonials, before/afters. Everything gets catalogued.

All of that gets compiled into a research document. Competitor analysis. Golden Pains mapped to LFE8. Dream outcomes. Available assets. Recommended angles.

That document feeds the second agent — the brief writer.

It builds static briefs: 3 copy variations per brief, each with Headline + Subline + CTA. Left side: 3 USPs. Right side: Feature → Benefit mapping x3. Visual direction, do's and don'ts, product URL, primary image, drive assets — all included.

It builds video briefs: 3 hook variations per brief, each broken into Text Hook + Visual Hook + Audio Hook + Why It Works.

Then 3 full timed body scripts — [0–3s] Hook → [3–8s] Setup → [8–15s] Product → [15–18s] Proof → [18–20s] CTA.

The 3-Second Formula is embedded at the writing stage. Second 0–1: Triple Stack (visual hook, text hook, audio hook firing simultaneously). Second 1–3: The Promise. Second 3–5: The Rehook.

If the structure doesn't hit those timings, it doesn't get written.

Every brief then hits the QA agent. This is where most of them die.

Validation checklist: 10 Golden Rules scored out of 10.

Minimum 7 to pass.

Score below 7? It doesn't get sent to me. It gets rejected back to the brief writer with specific fix notes.

Not a soft pass. A directed rewrite. The loop runs until it passes.

Only when a brief clears every node does it hit my Telegram.

6 production-ready briefs. 3 static. 3 video. Validated hooks. Fresh angles built from real market intelligence.

Ready for designer handoff → testing → iteration → scale.

No docs opened. No prompts written. No hours wasted.

I've scaled 50+ brands to 7 and 8 figures at MHI Media.

I mapped the full skill tree — every agent, every node, every framework, every validation gate.

Like + Repost + Comment "CLOUT" and I'll send it over.
(Follow me so I can DM you)

Screenshot not revelant but the last 30 days aint too bad.

[rollingwaves231 @rollingwaves231]

@nicktheriot_ ECOM