🚨 Hiring a Creative Strategist x Meta Media Buyer for our $1M/month DTC health brand
What you get:
- US$5K-10K/month OTE, including base + performance bonuses
- Remote, full-time, with serious room to grow
- Work directly with our Head of Marketing
What you’ll own:
- Customer research, angles, hooks and video scripts
- Editor briefs and creative feedback
- Meta campaigns, testing and performance analysis
Requirements:
- Recent DTC health, supplement or telehealth experience
- Strong direct-response copy and hands-on Meta buying
- Proof of winning ads you personally researched, wrote or briefed
- Full-time availability for an individual role
Portfolio, results and a short Loom required.
Apply: form.jotform.com/26291559702…
DM if you want to get this process done faster
i'm under so much pressure
🔁
i get to be under all this pressure since people are counting on me, what a privilege
V retweeted
Business is fucking euphoric when you’re printing and literal hellfire when you’re not. Like some of the most agonizing pain you can experience.
This is why most entrepreneurs are religious.
You will go insane without turning to God for balance and stability, guaranteed.
the great annual plot twist is almost upon us
this time last year was life changing
this year has been unreal
very excited for what’s to come…
V retweeted
i built a way to generate full ai vlogs for youtube using seedance 2.5, without ever picking up a camera
this was supposed to stay internal but f*ck it, i'm leaking the whole thing
you give it a script or even just a topic and it comes back with a finished vlog, voiceover, b-roll, captions, ready to upload
here's how it works: a custom claude skill breaks your script into scenes and writes timestamped storyboard prompts for each one, matched to pacing so nothing feels random. those prompts get fed into seedance 2.5, using its 30 second continuous generation and reference asset support to keep the visuals consistent across scenes instead of looking like ten unrelated clips stitched together. then it pulls in an ai voiceover that matches the tone of the script, stitches every scene together, and burns in captions automatically
you're not filming, not voicing, not editing, not exporting from three different apps
the whole thing runs start to finish and outputs a finished 16:9 vlog ready to post, and it costs a fraction of what an editor or camera setup would run you
i'm sharing the full breakdown, which includes:
the claude skill that handles scene breakdown and storyboard prompts the seedance 2.5 setup that keeps visuals consistent scene to scene the voiceover setup that keeps it from sounding robotic the exact workflow from script to finished vlog
RT + reply "PROMPTS" and i'll send it over (must follow so i can dm)
V retweeted
google's omni model + podcast ugc is actually insane
this entire conversation is ONE generation
i didn't have to stitch any clips together. simply pasted the exchange and it came back talking
i've tested this format to death and mastered the exact setup that makes 2 ai people feel like a real scroll stopping podcast
it's the best converting style i've touched and nobody is running it yet
so f*ck it, i'm giving away the whole system:
> the exact build, script to finished video, in about 5 mins
> how i make full 60s video generations in 1 prompt, no editing
> the two person script trick that sells without pitching
> my starting image rules (this is where realism lives)
rt + comment "PODCAST" if you want the full system, and i'll send it
(gotta be following so i can dm)
V retweeted
This is fucking insane! A big Ecom guru Samuel Onuha got arrested for walking in streets of Greece naked and humping status?????
His name should be Samuel Offnuha, his clothes are off and his mind is fucking lost and off
This is going to be big
This quoted post is unavailable.
V retweeted
i've been testing Higgsfield MCP + the NEW Claude Opus 4.8 to generate ALL our Meta ads creative inside 1 conversation...
and it has been ABSOLUTELY cooking
so i've decided to document the ENTIRE workflow...
covering the setup, market research, image gen, animation, copy, and 7-day test campaign structure to take a Meta ads creative batch from 0 to launch in a single afternoon as a service based business (agency, firm, brick and mortar, consultant, etc)
here's what's included inside the guide:
→ Higgsfield MCP setup in 5 minutes (claude.ai integrations → paste mcp URL → authorize. 30+ image and video models inside one Claude chat)
→ phase 1, market research + angle development (master brief prompt that returns 7 ad angles ranked by differentiation, top 3 expanded into 3 hook variations each)
→ phase 2, image generation with ChatGPT Images 2.0 (3 variations per angle in under 90 seconds. model selection table covering ChatGPT Images 2.0, Soul 2.0, Nano Banana Pro)
→ phase 3, scroll-stop animation with Seedance 2.0 (static image to cinematic motion loop. first 0.5s stops the scroll. one client hit 5.1% CTR week one... their highest-performing creative ever)
→ phase 4, the 4-variation copy stack (loss aversion, authority + specificity, contrarian, identity. 12 ready-to-test ad combinations from one session)
→ phase 5, 7-day test campaign structure (budget allocation, day 3 signal thresholds, day 7 kill and scale criteria, the 3 highest-probability winners to launch first)
all backed by $10M+ generated through Meta ads funnels for service-based businesses (and a legal funding client that we expanded from 8-12 to 40+ creative variations per month using this method... even finding 3 winners that scaled him to $89k/mo within 90 days)
like + comment "COOK" and i'll send it over
(must be following + RT for priority access)
V retweeted
We’ve officially hit the point where AI UGC is cheaper AND better than real UGC.
This video is 100% AI and cost under $1. (And no, it’s not Sora, Veo, or Kling).
My system is built for mass-scale organic across thousands of accounts. Here is why it wins:
- Hyper-realistic visuals: Natural physics and movement look flawless.
- Insane cost efficiency: Costs pennies compared to traditional UGC programs.
-Consistent audio: High-quality, rock-solid voiceover throughout.
- Infinite scaling: Videos can run to any length cost-effectively.
This changes everything.
Want the WORKFLOW? Check the comments!
V retweeted
$38k/month funnels don’t start from a blank page
they start from proven structures
advertorial
problem-aware page
mechanism page
product education page
offer page
checkout push
most brands don’t need a prettier landing page
they need a funnel that moves the buyer from:
problem
belief
proof
product
offer
action
that’s why templates work so well
you’re not guessing the page flow
you’re plugging your product into a structure already built to convert cold traffic
same traffic
better education
stronger offer framing
higher buyer intent
rt + comment "funnelpack" and i’ll send you the ecommerce funnel guide and templates
(follow for dm)
V retweeted
cleared ~$214k using a setup like this recently
people think scaling comes from better ads
it doesn’t
it comes from faster iteration
this is the whole system
- one product
- multiple static angles generated with ai
- turned into ugc-style videos instantly
- pushed across tiktok + meta
claude handles hooks + angles
everything else gets rendered and launched fast
no overthinking funnels
no long creative cycles
no waiting on anyone
just test → read data → double down
same structure repeated daily
that’s how volume compounds into results
rt + comment “loop” and i’ll send the full breakdown
(follow for dm)
V retweeted
I automated my content engine and 2 hrs/day dropped to 10 min
[ what’s new in v2 ]:
- 9 platforms scraped while I sleep → 2,000+ topics/day
- a 5-signal scoring brain that filters down to the 10 that matter
- voice DNA writer.. same tone, different structure every time
- a self-learning loop that remembers every approve and decline
- profile DNA — knows exactly what goes viral on MY account
v1 was a brain with no body
v2 has eyes, a filter, and memory + fully automated
Here’s how to build it step-by-step ↓
[ The architecture]:
/content-engine
├── scrapers/ (9 platform scrapers)
├── extension/ (chrome ext for X, linkedin, reddit)
├── ai/
│ ├── ranker.py (5-signal scoring brain)
│ ├── content_writer.py (voice DNA + structures)
│ ├── profile_analyzer.py (your positioning DNA)
│ └── sentiment_analyzer.py
├── publisher/ (export + time slot scheduling)
├── gui/dashboard.py (streamlit command center)
├── ingest_server.py (local server on localhost)
└── data/content_engine.db (everything stored locally)
let me walk you through each layer ↓
LAYER 1: Research engine
9 sources scanned 24/7 (X, reddit, YT, HN, github, trends + chrome ext for reddit and linkedin)
every post you scroll past gets tagged and stored locally
LAYER 2: Scoring brain
every topic scored on 5 signals:
- freshness (0.20)
- velocity (0.25)
- virality (0.25)
- relevance (0.20)
- uniqueness (0.10)
velocity 8+ → forced min score of 7. catches late bloomers that suddenly explode
2,000 topics → top 10 ranked
LAYER 3: Voice DNA writer
not one structure every time. system picks the format:
- short take
- tactical playbook
- QT contrast
- contrarian
- resource drop
- proof post
a voice guardian auto-rewrites anything that fails: lowercase ratio, no hashtags, no corporate words
LAYER 4: Dashboard Streamlit
dark theme. 5 tabs
review queue = tinder for content. swipe approve, swipe decline
LAYER 5: Publishing
no auto-posting. zero account risk
approve → pick a slot (8am / 12pm / 5pm) → exports a .txt → copy / paste / post
also auto-drafts a linkedin version of every approved tweet
LAYER 6: Self-learning loop
every click logged. weekly the system embeds your decline notes and re-tunes the scoring brain
month 1: you approve 30%
month 3: 70% pre-filtered
month 6: 10 min/day
LAYER 7: Profile DNA
analyzes your past tweets. tells you exactly which pillars, formats, and hooks perform best on YOUR account
the scoring brain uses it to prioritize what already works for you
daily run: open dashboard → 10 min reviewing → post 3x → close
total cost: ~$15/month
everything else: local, sqlite, no cloud, no subscription
unfortunately I couldn’t paste in long-form format initial description which was made before
but if this hits 2,000 likes I drop the full build guide with every prompt you need to ship it in claude code
reply "ENGINE" + RT and I'll DM you access to test it (follow me first so I can write)
save this so you don't lose it
V retweeted
Our biggest resource of 2026 has been downloaded nearly 3000 times. It just got updated.
The 2026 playbook now includes a full breakdown of Meta's 31 March algorithm update, the rise of persona-led creative, partnership ads, AI UGC, and how the next wave of UGC is forming.
Four pillars: Meta, TikTok, AI, Creative. Built from £600M+ in revenue across the brands we run.
Retweet this post and comment "2026" and I'll send it across.
V retweeted
The vaccine dosage was obviously too high and done too many times.
I had the original Wuhan virus before there was any vaccine and it was much like any other cold/flu. Bad, but not terrible.
But my second vaccine shot almost sent me to the hospital. Felt like I was dying.
This should be headline news EVERYWHERE.
A Pfizer insider who was former head of toxicology in Europe has just come out and said something that many "conspiracy theorists" suspected.
He estimates that 20 000 to 60 000 people in Germany have died from the c*vid vaccine.
This was said at a parliamentary enquiry commission in Germany.
So why isn't this massive news being reported everywhere?
Is the mainstream media that has recieved millions in funding from Bill Gates deliberately covering this up... 🤔
V retweeted
How did Gruns actually scale the way they did, financially speaking?
I dont have any inside info, but I can tell you how. Balancing inventory, CACs, opex, etc during hypergrowth is an extremely difficult task; however on a spreadsheet it can in fact all be reduced down to a very simple mathematical model that is highly dependent on two variables and one ratio:
Lifetime profit per customer divided by the cost to acquire said customer
or for the initiated; LTV:CAC
Put simply, there is approximately a zero percent chance that Gruns had an LTV:CAC less than 3.0x. Further, if they did manage to somehow scale without 3.0x, Unilever wouldn't have acquired them.
My best performing substack post ever (will link in the comments) is titled "Why 3.0 LTV:CAC"
Summarized into a sentence; the answer is: because when 1 customer gives you enough profit to pay back the first customer and acquire 2 more customers, you can grow exponentially. 1 customer turns into 2, 2 customers turns into 4, 4 turns into 8 and voila - you have your hockey stick (figure 1).
Over time, the wide majority of revenue becomes repeat customers. Terminally, a healthy ratio for new:repeat is about 30% new to continue compounding at an exponential rate.
However, you are acquiring these customers at a loss on the first purchase. In the early days, this creates a cash burn. I theorize that this is why Gruns raised fairly significant capital early on, becuase they recognized the nature of the 'J-curve'
The J-curve is when you are burning cash on customer acquisition, and you don't yet have enough cohorts returning to actually cover the cost of the marketing investment you're deploying to acquire new customers. It creates a period of negative contribution prior to a period of compounded profits, in the shape of a J.
When you have the proper LTV:CAC, the business case for financing the negative portion of J curve with equity is very very strong, hence the early capital raising.
So the calculus is essentially:
establish unit economics -> raise capital ->scale
The most critical part of executing on this model is ensuring that as you scale customer acquisition, each cohort is CREATING enterprise value, not DESTROYING it. This is where 99% of founders fail.
EV is only created then those cohorts pay back and start generating profit. As you scale, often CAC goes up so much that cohorts never pay back, and you are actually losing money and destroying enterprise value, even if revenue is going up.
This is where the phrase 'not all growth is good growth' comes from.
And that ladies and gentleman, is your financial modeling primer. Someone told me not to put the term 'financial modeling' at the front of this post because they will fall asleep, but ha ha i've tricked you into learning it!
This is the kind of work we do every day with brands at iris. We deploy agents to clean your data & build your models. if that sounds like something you could benefit from, shoot me a DM
