Thechrismarrano
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Please don’t fall for the highest volume lowest cost magic trick that Facebook is trying to pull on everybody. This year, especially the highest volume seems to be the lowest performing out of every campaign. We manage, especially over the last few weeks. Big caps are continuing to run that 50 to 70% utilization of the budget and scaling almost daily.
Stop managing people. Start managing agents.
If you are still hiring four humans to do work that one operator and an AI could handle, you are falling behind.
An AI operator doesn't just use AI; they build systems. By wiring Claude into Shopify, Meta Ads, and Slack, they create a seamless flow of data and actions that runs 24/7.
This is how you scale a $5M brand with a lean team. You automate the repetitive tasks and save your brainpower for high-level strategy.
Want the blueprint for your brand?
Comment BUILD and I will DM you our internal agent map.
iOS is not your problem. Your strategy is.
I’ve audited over 80 DTC brands this year, and the ones struggling with rising CPAs all say the same thing: “It’s the iOS updates.”
But after looking under the hood, I found the same 3 issues every single time and none of them were Apple’s fault:
1. Creative Fatigue: Using the same 3 angles since last summer.
2. Stagnant Offers: The offer hasn’t evolved since the initial launch.
3. Outdated Retention: A post-purchase flow that hasn’t been touched since 2023.
If you’re still blaming the platform, you’re missing the profit.
Want to see where your leaks are?
Comment AUDIT and I’ll send you the exact 3-point checklist we use to fix these gaps.
05/09/2026
My media buyer used to spend 90 minutes every morning on data pulls. Mia does it in 4.
Here's the routine she replaced:
Open 8 ad accounts → pull yesterday → compare to 7-day baseline → identify pauses + scales → write a Slack update → repeat. Brain fried by 10am.
Mia's prompt has 4 jobs:
1. Pull yesterday + prior 7-day baseline
2. Diagnose every active campaign
3. Recommend pause / scale / bid adjust
4. Post to Slack with [Approve] [Override] buttons
She queries Supabase directly — performance_daily, creatives, accounts. Zero Meta API calls at runtime. A 5am cron syncs the data; Mia reads from the warehouse at 8am. Fast. Deterministic. No rate-limit drama.
The buyer's job didn't disappear. It changed.
Old job: analyze
New job: approve
She reads Mia's recs, hits Approve or Override. 4 min per client. Same decisions. Fewer mistakes (Mia doesn't get tired at 9:45am).
What did 86 min/morning unlock? Creative briefing. Competitor research. Strategy calls.
The work humans are actually good at. The work that compounds.
Mia's full prompt + Supabase schema + the Slack action-button setup are inside my Skool.
🔗 Link in bio.
Two brands. Both hitting $5M/year.
But their bank accounts look completely different. Why?
Brand A: 4 people doing manual data entry, triaging tickets by hand and building reports from scratch.
Brand B: 1 operator + Claude AI.
The result? Brand B is netting 18 points more in profit.
Efficiency isn't just about working harder; it’s about working smarter with the right AI systems. By 2027, the gap between traditional ops and AI-powered brands will be brutal.
Which side are you on?
Comment OPERATOR and I’ll send you the playbook for becoming Brand B.
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