Bill Stathopoulos

Founder

👋 I'm Bill, and here's my story:

1. Building SalesCaptain, an Outbound & AI GTM agency for B2B SaaS to $3M+ ARR, while being a digital nomad for 4 years.
2. Authored a book - "Cold Email Secrets"
3. Scaled a Growth Marketing Agency to $1M ARR at the age of 28. Grew the team from 7 to 25+ employees in 3 years. Closed clients like Nestle, Revolut, GE, and the Singapore Airport.
4. Helped multiple startups go from zero to $5M+ revenue in 18 months since 2015
5. Trained 2,500+ Growth Marketers in the last 5 years
6. Built the speakers lineup for Ad World, with 50k+ attendees and 100+ speakers, making it the largest advertising conference in the world
7. Interviewed Seth Godin, Scott Galloway, Arianna Huffington, Rory Sutherland, the CMO of Samsung, the CMO of Hubspot, and 30+ world-class Marketing executives.
8. Published the book “Cold Email Secrets”, the bible of modern Outbound & GTM. 
9. Named “Top Lead Generation Voice” on LinkedIn in 2024
10. Became the Clay Club Host in London, leading a team of 15+ GTM Engineers

What you'll get working with me:
🧲 Your Go-To-Market (aka GTM) Strategy
🏀 Optimize your Marketing channels; make the most of your budget
🏆 Build systems for User Acquisition, Activation, Retention, and Revenue

Peace, love & growth ✌️

Bill

Co-Founder

We build and scale Outbound Sales systems that include multi-channel prospecting, lead response, and our cutting-edge processes to help you build your business.

This is the exact stack we're relying on to get us to $6M ARR. 
After working with 70+ GTM teams, testing 125+ tools, here is what stayed.

To get from $0 to $3M we ran a much bigger stack.
It worked, but the tools got better and we got smarter about what we actually needed.

So we simplified our stack.

This is what stayed, organized by job to be done:

0. The Engine

→ Clay: data orchestration. Every source plugs in, every workflow runs through it
→ n8n: where our agents live and automations run 
→ Claude: research, intelligence, copy

1. Finding the right accounts 

→ Apollo: targeted lists 
→ LinkedIn Sales Navigator: full stakeholder mapping 
→ Ocean.io: lookalike companies once you've nailed an ICP

2. Capturing buying intent

→ RB2B: identifies warm website visitors
→ Trigify.io: catches LinkedIn engagement signals before your competitors do 
→ Common Room: monitors your CRM accounts and flags when it's time to reach out

3. Getting clean contact data

→ FullEnrich: phone + email waterfall 
→ Prospeo: fills the gaps for specific cases 
→ ZeroBounce: validate before you hit send

4. Personalizing at scale

→ Claygent: account research on autopilot 
→ Twain / Octave: purpose-built copy tools for teams that want alternatives

5. Reaching out
 
→ lemlist: best multichannel 
→ HeyReach.io: LinkedIn DMs at scale, zero bans 
→ Instantly.ai: cold email with warmup + rotation built in 
→ Salesfinity: cold calling that actually books meetings

6. Closing and tracking
 
→ HubSpot: still the best CRM if you use it right 
→ Attio: our recommendation for teams under 50 
→ Qwilr: proposals that move deals forward async 
→ Sybill/ Claap so reps spend time selling, not taking notes

That's 23 tools across 6 layers.

The catch is: you don't need all of them.

We run this many because we work across 70+ clients, different industries, different ICPs, different motions that are built for their specific case.
(What works for a PLG SaaS won't work for an enterprise services firm.)

But the logic behind every tool is the same:
Signal → Enrich → Personalize → Reach out → Close → Learn
Each tool has one main job, each job feeds the next.

What's the one tool you'd never cut? 👀

CEO, SalesCaptain | Clay London Club Lead 👑 | Top lemlist Partner 📬 | Investor | GTM Advisor for $10M+ B2B SaaS

We're building toward $6M ARR, 
Signal-led outbound is the bet... Here's every signal worth tracking in 2026 👇
 
🟢 1st Party (The signals you have, nobody else has access to this)

- Website Visitors:
RB2B
Midbound
Warmly,

- Product Usage
Common Room
Pocus

- LinkedIn Signals
Trigify.io
Clay
Expandi

- CRM Data
HubSpot
Close
Attio

- Call Transcripts
Fathom.ai
Attention
Claap
 
🔵 2nd Party (these are shared by your ecosystem: from partners, platforms, and communities your buyers are already part of)

- Champion Tracking
Clay
UserGems 💎
Unify

- Ad Engagement
ZenABM
Fibbler

- Affinity Signals
Crossbeam
The Swarm

- Review Sites
G2
Capterra
 
🟡 3rd Party (These are inferred from public data, it's everything happening in the market.)

- Job Openings
Clay
PredictLeads
LoneScale

Funding
Crunchbase
PitchBook
Clay

Technographic
BuiltWith
HG Insights
Clay

Custom Scraping
Apify
Claygent
Firecrawl

Firmographic Data
BetterContact 
Apollo
Clearbit
Clay
 
P.S. We turned everything we learned into "The Intent Signals Playbook".
26 pages, every signal type, every tool, and every workflow.

Comment SIGNALS and I'll send it over.

search-magic

salescaptainio

scicord-llc

pixofix

madbold

$45+ Billion in GTM software valuations, from just 9 tools on this map!!
There are 80+ on here!

(And most weren't built in Silicon Valley.)
 
V2 of the 🌍 Global GTM Map is here.

After dropping the first GTM map last week,
the comments became a map of their own.
Founders and GTM operators tagging tools, adding countries, calling out what I missed.

So I updated it.
 
+20 New tools, +3 new countries, same mission:
Showing that GTM is now a global movement.
 
A few things that you can see from the map:

→ There is a concentration of tools in France, UK and Estonia
→ France is leading enrichment
→ Estonia coming strong in email outreach
→ The US still leads on signals and intent
→ The UK is dominating AI video & voice
→ Bulgaria, Canada, and Ireland just joined the map
 
The tools that got the most love in the comments:

🇺🇸 Clay
🇫🇷 FullEnrich 
🇫🇷 lemlist
🇪🇪 Instantly.ai
🇲🇰 HeyReach.io
🇺🇸 RB2B 
🇬🇧 Synthesia
🇬🇧 Attio
🇺🇸 Zapier 
🇩🇪 n8n

New additions include:
🇺🇸 Lovable 
🇫🇷 Claap 
🇧🇬 clearcue.ai
🇨🇦 EmailBison
🇮🇪 Trigger.dev
🇺🇸 Chili Piper
🇺🇸 Artisan
🇺🇸 Calendly
🇳🇱 Signalbase
 
What's the best GTM tool from your country that didn't make the map?

Claude Code went from $0 to $2.5B in under a year!
We spent 3 months figuring out how a GTM team should use it. Here's everything we found..
 
LinkedIn is giving you FOMO about Claude Code,
but nobody is explaining how it actually fits into GTM.
 
We built the playbook that answers that.
 
Whether you're an AI expert or this is the first time you hear about Claude,
this resource has everything you need to get started, like:
 
1️⃣ Setup in 10 minutes, no dev background needed
2️⃣ Your first win in 60 minutes, copy paste prompts included
3️⃣ 12 playbooks every GTM team should build first
4️⃣ The full 8-step outbound campaign pipeline
5️⃣ CLAUDE.md templates by GTM motion
6️⃣ 25 workflows by GTM role, SDR, AE, Marketing, RevOps, CS
7️⃣ What NOT to automate, and the readiness checklist
 
Every workflow in it is running in production today.
 
We gave early access to our newsletter subscribers, the response was overwhelming.
Now we're making it public, for free.
 
Comment CLAUDE and I'll send it over.

100+ hours tracking LinkedIn feeds.
These are the 50 GTM voices worth your attention in 2026.
 
These are the people moving the needle in GTM right now.
Sharing frameworks you can steal on a Monday morning.
Building and leading the companies defining how B2B revenue is won in 2026.
 
A few highlights 👇

Kyle Coleman: redefining how AI should actually plug into your sales motion, not just your copy.

Chris Walker: the person who was right about the dark funnel before the rest of the market caught up.

Kyle Poyar: if you touch pricing or PLG, his Growth Unhinged newsletter is the closest thing to a cheat code that exists.

Adam Robinson: bootstrapped RB2B to $7.5M ARR by turning building in public into a real distribution engine.

Andrei Zinkevich and Emilia Korczynska: the most consistently rigorous ABM thinkers posting on LinkedIn.

Plus top voices from Clay, lemlist, Salesforge.ai 🔥and others.
 
I'm on the list too 😎 I share what we're learning at SalesCaptain in real time: the workflows we run, the outbound playbooks that actually convert, what's working in GTM right now and what isn't.
If any of this is useful → hit Follow, I post 4-5 times every week.
 
Full list in the creative,
Everyone else tagged in the comments 👇

Clay hit $100M+ ARR without a traditional sales army.
Because Clay's best customer is Clay.
 
They use their own product to run their entire GTM, and it helped them scale to $100M ARR and a $5B valuation, serving 15,000+ customers including OpenAI, Canva, and Google.
 
This Thursday, at 🇬🇧 Clay Club London, Clay's Co-Founder Varun Anand is breaking down the actual operating model.

You’ll see:
- How Clay uses Clay internally
- How website intent becomes outbound action
- How workflows replace manual prospecting
- What stays human, and what doesn’t
 
Plus:
Yash Tekriwal 🤔 is walking through Clay’s internal education and enablement engine.
lemlist and Dealfront are joining the operator roundtable.

And I’ll be doing a live breakdown of how we build signal-driven GTM systems for clients right now.

Real workflows + open Q&A.

If you're in London, you don't want to miss the insights (and the people) in this room.

Registration link is in the first comment.

See you there 🔥 😎

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"Should I just use Claude Code instead of Clay?"
"What about n8n or Make?" ,"Do I even need Zapier anymore?"

We get these questions every week across 70+ clients. 
The confusion is understandable. 
Here's the answer nobody's giving you.

You don't need all 5 of these tools. 
You need to know what each one does, pick the ones that match your stage, your team, and your budget.

1. Claude Code

✅ Calls any API, writes and runs its own scripts 
✅ Replaces tasks that used to need a developer 
✅ Cheapest of the five ($20/mo base)

❌ Your code and prompts go to Anthropic's servers (data privacy concern) 
❌ No visual interface (non-technical will have a steep learning curve) 
❌ Needs deployment setup to run autonomously 
❌ Cost spikes with heavy API usage

Best for: Scale stage teams ready to automate custom workflows

2. Clay

✅ Best B2B enrichment on the market (waterfall 15+ providers) 
✅ Visual, non-technical friendly
✅ Native AI built in (Claude, GPT, Gemini)

❌ Won't run on its own  
❌ Credits stack up fast at high volume

Best for: Any stage, the GTM tool most teams start with

3. n8n

✅ Runs 24/7 autonomously 
✅ Self-hosted = zero per-op cost
✅ Full logic control, AI agent nodes built in

❌ Steep learning curve 
❌ Every API update = manual fix on your end 
❌ Managing 20+ client instances needs a dedicated person

Best for: Scale stage (only with a dedicated GTM engineer)

4. Make 
✅ Visual drag-and-drop, no code needed 
✅ Affordable entry point ($9/mo) 
✅ Runs 24/7

❌ Hits its ceiling fast on complex logic 
❌ Not built for serious GTM engineering at scale

Best for: Growth stage teams who need automation without hiring a developer

5. Zapier 

✅ Easiest to set up 
✅ 6,000+ integrations 
✅ every team already knows it

❌ Most expensive at scale 
❌ Not built for complex GTM logic (you'll outgrow it fast)

Best for: Early stage, or simple triggers at any stage

The clients who get this right early save 3-6 months of rebuilding. 
The ones who don't always come back saying they wish they'd started smaller.


Which of these are you currently running?

40% of our outbound now runs on Claude Code.
Here are the 25 workflows making it happen, broken down by role.
 
👨‍💼 SDR / Business Development

1. Signal-triggered outbound
2. LinkedIn engagement scraping
3. Job-change tracking
4. Competitor evaluation targeting
5. Influencer outreach automation
 
💼 Account Executive

6. Meeting prep brief
7. BANT call analysis
8. Recovery email after tough calls
9. Buying committee mapping
10. Deal intelligence from transcripts
 
🤳 Marketing

11. LinkedIn ads via API
12. Content-to-pipeline workflow
13. SEO content pipeline
14. Win-loss messaging analysis
15. Sales calls to content
16. Event attendee outreach
 
💰 RevOps

17. Pipeline forecast check
18. Custom signal enrichment
19. Positive reply routing
20. Weekly pipeline digest
21. Lead magnet follow-up automation
 
🤝 Customer Success

22. Champion departure response
23. Renewal intelligence
24. QBR preparation
25. Account health scoring
 
These workflows are built on:

Claude Code 
Clay
Apollo
HubSpot
HeyReach
lemlist
Instantly.ai
RB2B 
Fathom.ai
Slack
n8n
 
We documented all 25 in detail in the Claude Code GTM Playbook, exact prompts, setup steps, tools and 30-day plan for using Claude Code in GTM included.

Comment CLAUDE and I'll send it over. 👇

25 Claude code Workflows for GTM teams

Here's the full ABM stack we're using to hit $6M ARR
200+ ABM campaigns taught us which tools actually matter. 

P.S. The top 1% GTM teams in 2026 are running seven layers, the rest 99% run only three.

1. Intent Signals
Unify
Bombora
Common Room
 
2. LinkedIn Ads & Tracking
ZenABM
Fibbler
LinkedIn Campaign Manager
 
3. Website Visitors
RB2B
Midbound
Warmly,

4. Data Orchestration
Clay
Apollo
Sales Navigator

5. Outreach
Instantly.ai
lemlist
Salesforge.ai 🔥
HeyReach.io
 
6. AI Layer
Claude
Claygent

7. CRM & Ops
HubSpot
n8n
Zapier
 
💡 One tip we learned after 200+ campaigns:
The main reason ABM fails is because you're reaching one person at a company, not the buying committee. 
Fix your contact coverage first.
(Match rates went from 40% to 80%+ for our clients when we did 🔥)
 
What's the one layer missing from your current ABM stack?

We analysed 6,000+ signals across 200+ B2B campaigns.
These 9 generated $2M+ in pipeline.
The rest were just noise.

Last month we ran a webinar with lemlist about signals, 1,200 people showed up.
Most of them had the tools, Clay, RB2B, Bombora... you name it.

They all had signals,
But almost none had a system for what to do with the signals.

They had the tools, not the playbook.
So we wrote it for you.

A comprehensive resource (9 chapters) on:

→How to find the signals UNIQUE to your business (that your competitors don't have)

→ How to prioritize the accounts they surface (the exact scoring matrix) 

→ What to do at every stage: TOFU, MOFU, BOFU 

→ What to say when a signal fires (the AI personalization framework) 

→ 17 signal types + the full GTM tech stack to run it all

Everything we use at SalesCaptain and across 70+ clients
Nothing held back.

Comment SIGNALS and I'll send it over.

We used these 7 signals to generate 20+ meetings/month and $1M+ in pipeline, ONLY from LinkedIn.
Here are the signals, the steps and the tools we used:
 
1. LinkedIn Ad Engagers → They engaged with your ad but never clicked. Capture, enrich, reach out.

2. LinkedIn Harvesting → 3+ engagements from the same person. 
Auto-DM + follow-up email.

3. Event Attendees → New events in your space every Monday. 
Find who's attending first.

4. Keyword Engagers → Someone posts about the exact problem you solve. 
You show up.

5. Followers Outreach → They followed your page. Enrich, classify, personalize, reach out.

6. Competitor Followers → Already in the market. 
The warmest outreach you'll ever run.

7. Decision Maker Connect → Meeting booked → full buying committee found → connected before the call. (This one alone changed how we close deals)
 
Most reps are waiting for prospects to raise their hand.
These workflows find them the moment they show intent, before they even know they need you.
 
Tools used across all 7:

LinkedIn
Clay
HeyReach.io
lemlist
Trigify.io
Common Room
PhantomBuster
HubSpot
ZenABM
Instantly.ai
Calendly
 
Workflow 06 is the one most people skip because it feels too aggressive. It's also the one I'd start with.

Which one are you running? 👀

7 LinkedIn workflows that generated $1M in pipeline

HeyReach just got banned by LinkedIn ❌ 
We've run 200+ campaigns with them. Here's my opinion 👇

Of all the LinkedIn tools out there, HeyReach was one of the most careful.

They respected rate limits.
They built for safety.
They did everything right
... and they still got banned.

Which means no one is safe.
Because this isn't about compliance.
 
LinkedIn is playing a different game entirely.
Every tool that monetizes their data better than they do is a target.

Automation tools first.
Then enrichment.
Then analytics.
 
LinkedIn is closing the loop, slowly, then all at once.
Worth noting, existing campaigns are still running, users are not affected.
 
The right question to ask isn't "which tool do I switch to?"
It's: 
"How much of my GTM is built on a platform that can pull the plug overnight?"
 
Curious what others are thinking here.

Clay just dropped a major pricing update (March 2026)🆘
Here's who benefits, who should pay attention, and what most people missed.
 
🟢 BIG WINNERS

→ Teams doing heavy enrichment with Clay's marketplace 
Data costs just dropped 50–90%.
Your budget goes a lot further from day one.
 
→ Teams that wanted CRM + Web Intent but couldn't justify $800/mo
Those features now unlock at $495/mo on the Growth plan.
That's the biggest access shift in this update.
 
→ Heavy Claygent users Clay says 85% of AI users will pay less.
Frontier models now pass through at cost, zero markup.
 
🟡 WATCH OUT

→ Pro plan users running workflows on your own API keys 
Three things to know:
 
1️⃣ You may see a price increase, Clay admitted the old Pro plan was mispriced

2️⃣ Using your own API keys DOES consume Actions, this is the detail most posts are missing.

3️⃣ Even a single HTTP API call to your own database now requires the $495 Growth plan

→ Heavy credit users (70K–100K credits/month)

One user publicly shared their math:
Currently paying ~$1,500/mo.
To maintain the same volume on new plans → $3,500–5,000.
If you're in that range, model this out before you switch.
 
→ Solo GTM engineers and individuals

Clay essentially coined the GTM Engineer role.
But higher fixed costs raise the barrier for people just getting started.
Worth flagging honestly.
 
→ Anyone assuming Actions = Credits
They're not.
Actions measure platform work, 1 action per task, regardless of data spend.

The good news: 90% of customers will never hit their limit.
 
What does NOT consume Actions: Lookups, CRM imports, webhook imports, CSV exports.
 
🔵 THE BIGGER PICTURE
 
Clay is separating what the platform does from what the data costs.

For GTM teams, that clarity matters, and it sets them up to charge properly for the orchestration features coming next.
 
Across the 70+ clients we run GTM for, 
the teams that will feel this most are the ones doing serious enrichment work inside Clay, and for them, this is a genuine win 🏆 
 
Clay also publicly said this will cost them 10% in revenue short term.
That's not a company optimizing for quarterly numbers, that's a bet on the right model winning.
 
If you've been sitting on the fence because the credit model felt unclear, this changes that.
 
On a legacy plan?
You have until April 10 to decide.
You can stay exactly where you are. No forced migration.
 
Where are you right now with Clay? 👀

- Heavy user evaluating the change
- Considering Clay for the first time
- Confused about Actions specifically

Drop it in the comments, happy to help if I can.


*image via Everett Berry.

We went from $0 to $3M ARR using cold email.
The tools that got us there? Half of them don't exist in our stack anymore.

It's not because they're bad tools, but because the market moved.
 
Cold email in 2026 looks nothing like 2022, here are 10 differences:
 
1️⃣ Sending moved from basic sequencers to multichannel-first tools Instantly.ai lemlist

2️⃣ Data moved from static databases to waterfall enrichment 
Clay

3️⃣ Validation moved from manual to automated 
ZeroBounce

4️⃣ Personalization moved from Mail Merge to AI at 1:1 scale 
Clay Claude

5️⃣ LinkedIn moved from manual outreach to 30 profiles running simultaneously HeyReach.io

6️⃣ Email only outreach is replaced by Multichannel Email + LinkedIn + WhatsApp + Calls 
lemlist

7️⃣ Automation moved from Zapier clicks to plain English workflows 
n8n Claude Code

8️⃣ Deliverability moved from guessing to knowing before you send 
GlockApps Folderly Inc.

9️⃣ AI research moved from hours to minutes 
Claude Claygent

🔟 Infra moved from 1 domain to 10+ minimum 
Mailforge - Cold Email Infrastructure 📈
 
We're building toward $6M ARR.
The modern stack in this image is part of what we're betting on.
Share it with your network 🔁 
 
P.S. We put together SalesCaptain's full "Cold Email Playbook" (infrastructure, sequencer setup, drafting emails, stack...etc the whole thing) 
Comment COLD and I'll send it over.

Bad email infra costs the average GTM team $2,000+/month in wasted tools.
Here's what you actually need at every budget level.
 
💰 $500 Stack 
For solo founders and new GTM teams testing cold email. 
Goal: Test messaging fast + keep reputation intact.

Inbox Provider: 
Gmail
Outlook 

Sending:
Instantly.ai
Smartlead 

Warm-up:
Built-in (both) 

Verification:
ZeroBounce
Bouncer 

Health Monitoring: 
GlockApps
Instantly.ai reports 

AI Personalization:
Claude 

Automation:
Zapier 

Domain Setup:
Namecheap + Cloudflare

⚙️ $1K Stack 
For growing teams running consistent outbound and early multichannel. 
Goal: Stable inboxing + visibility into what's working.

Inbox Provider:
Mailforge - Cold Email Infrastructure 📈
Zapmail.ai 

Sending:
lemlist 
Salesforge.ai 🔥

Warm-up:
Mailforge Warm
Clay Signals 

Verification:
NeverBounce by ZoomInfo
ZeroBounce 

Health Monitoring:
MailReach
Mailsuite 

AI Personalization :
Claude
Claygent 

Automation:
n8n

🚀 $5K Stack 
For GTM teams sending 100K+ emails/month or agencies running multi-client. 
Goal: Predictable deliverability at volume, automated, monitored, CRM-connected.

Inbox Provider:
Mailreef
Inframail 
Mailscale 

Sending:
Lemlist
Outreach
Salesloft 

Warm-up:
Folderly Inc. 
Warmbox 

Verification:
ZeroBounce
MillionVerifier 

Health Monitoring:
Mailreach Premium 

AI Personalization:
Claude
Claygent
Twain 

Automation:
n8n
Clay
HubSpot CRM sync 

Reputation AI:
Mailscale active recovery
 
We mapped all three stacks into the slides above.
Swipe to see if you're overpaying for your current setup

P.S. If you want the FULL "Cold Email Playbook" Let me know in the comments below 👇

Cold email infra by budget 2026

The worst thing that can happen to your business : being INVISIBLE to your best buyers.
 
They're ready to buy,
You have no clue!
Because you don't know it's the right moment to reach out.

That's what signals fix.
 
Signals tell you who is in buying mode, right now.

Most teams use 1 or 2.
The best teams stack signals from all 3 layers simultaneously
and that's what separates 1% reply rates from 5%+.
 
Here's every signal type worth tracking in 2026 👇
 
🟢 1st Party (The signals you have, nobody else has access to this)

Website Visitors → RB2B · Midbound · Warmly,
Product Usage → Common Room · Pocus
LinkedIn Signals → Trigify.io · Clay · Expandi
CRM Data → HubSpot · Close · Attio
Call Transcripts → Fathom.ai · Attention · Claap
 
🔵 2nd Party (these are shared by your ecosystem: from partners, platforms, and communities your buyers are already part of)

Champion Tracking → Clay · UserGems 💎 · Unify
Ad Engagement → ZenABM · Fibbler
Affinity Signals → Crossbeam · The Swarm 🔆
Review Sites → G2 · Capterra
 
🟡 3rd Party (These are inferred from public data. Everything happening in the market.)

Job Openings → Clay · PredictLeads · LoneScale
Funding → Crunchbase · PitchBook · Clay
Technographic → BuiltWith · HG Insights · Clay
Custom Scraping → Apify · Claygent · Firecrawl
 
P.S. We turned everything we learned about signals into "The Intent Signals Playbook".
26 pages, every signal type, every tool, and every workflow.

Comment SIGNALS if you want to get it.

The only Signals playbook you will ever need.

https://lnkd.in/d7J3_JRR

Founder @Blue Water Marketing | eCommerce & Digital Marketing Nerd

Hey, I'm Chris Marrano.

I've spent that last 15 years in digital marketing. Started at Mullen in Boston running campaigns for Match.com and LendingTree. Went client-side at Harvard Business School. 
Then built Blue Water Marketing from scratch.

BWM is an eCommerce growth agency that manages Meta, Google, and Klaviyo for Shopify brands scaling from 7 to 8 figures. But somewhere along the way, the agency became a lab. 

We stopped just running ads and started building what goes behind them. AI systems that monitor every client account 24/7. Automated creative briefs generated from real performance data. 

A learning algorithm that gets smarter with every human decision. Real IP that's always running in the background.

We turned an agency into a tech company that runs ads.

That thinking became ADIQ.AI. AI-powered creative intelligence that tells DTC brands what's working before their budget does.

And after building all of this publicly on LinkedIn, the same question kept showing up in my DMs from founders and agency owners: "How do I build this for my business?"

Now I help them do exactly that. Private consulting. Full infrastructure builds. And a community of eCommerce operators who are done guessing and ready to build real systems. 

I help brands and agencies stop renting results and start owning their own IP, their own data layer, their own competitive moat.

The future of eCommerce isn't more ads. It's better infrastructure. I'm here to help people build it.

South Florida. Family first. Beach days, t-ball games, and a goldendoodle who supervises everything I build.

Chris Marrano

Meta just made two announcements that most brands are going to miss.

Detailed targeting is now mostly a suggestion.
ASC and AAC campaigns are being phased out entirely by September 2026.

Read those together and there’s a clear pattern.
Meta is systematically removing every manual control lever advertisers have relied on for the last decade.

Audience targeting. Campaign structure. Budget allocation.

All of it is moving into the machine.

And the brands that are going to struggle the most are the ones who built their entire strategy around controlling those levers.

Because when the lever disappears, so does the strategy.

Here’s what that leaves you with.
- Your offer.
- Your creative.
- The strength of your signal.

That’s it. That’s the whole game now.

The agencies still arguing about ad set structure and audience stacking are having the wrong conversation entirely.

Meta has already decided that conversation is over.

The only edge left is what you put in front of people and whether it makes them stop.

Everything else is just settings.

What are you seeing in your accounts since targeting started getting overridden?

Building AI-Systems For eCommerce | Founder@ADIQ.AI | Founder@BlueWaterMarketing

What the f*ck is happening?! Shopify just quietly made half the ecommerce tech stack irrelevant.

Their Winter ’26 Edition dropped 150+ updates. Most people skimmed the headline and moved on.

That was a mistake.

Here is what actually matters and why it changes everything for brands and agencies.

1.	Sidekick is no longer an assistant. It is an operator.

It builds custom apps from a text prompt. It creates automation workflows in Shopify Flow. It edits your theme without touching code. It removes backgrounds, expands canvases, and generates lifestyle scenes from your product photos. All inside the platform.

The $10/month micro-SaaS apps that solved one small problem? Their value proposition just went to zero.

2.	Your products now sell inside AI conversations.

Agentic Storefronts let you show up directly in ChatGPT, Perplexity, and Microsoft Copilot. One setup in admin and your catalog is discoverable wherever AI shopping happens.

This is a brand new sales channel. And most brands have not even turned it on yet.

3.	You can now simulate buyer behavior before going live.

SimGym uses AI trained on billions of real Shopify purchases to predict how your changes will impact conversion, AOV, and add-to-cart rate. Before a single real customer sees them.

Combined with native A/B testing through Rollouts, you no longer need three third-party tools just to test a homepage layout.

4.	AI image editing is built in.

Background removal. Canvas expansion. Composition adjustments. Lifestyle scene generation. Studio-quality product shots. From your phone.

The brands that were spending $500 per product shoot can now iterate on creative at near zero marginal cost.

Here is what this means for the next 12 months.
The gap between brands that adopt these tools and brands that ignore them is going to widen fast.
Not because the tools are complicated. Because they are simple. And the brands that move first will compound that speed advantage every single week.

For agencies, the implication is even bigger.
If your value is execution, Shopify just automated most of it.

The agencies that survive will be the ones providing strategic direction, creative systems, and performance frameworks that AI can plug into.

Not the ones charging retainers to swap backgrounds and build flows.

The platform is not waiting for anyone to catch up.
Neither should you.

Meta just put a $2 billion AI agent inside your Ads Manager.

Here’s why it’s a waste of your time right now.

Manus AI showed up in the Tools menu last month. No announcement. No tutorial. Just a pop-up asking you to “try it now.”

So we did.

Here’s what actually happens when you click it:

You get redirected to the Manus website. You need to create a separate account. You need a paid subscription after 7 days. And the “integration” is basically a chatbot that reads your ad data.

That’s it.

No campaign creation. No bid adjustments. No budget changes. No creative testing. It can’t touch your account. It just reads it and gives you summaries.

And those summaries? Practitioners are reporting straight-up hallucinations.

One media buyer said Manus told him people were calling from an ad that had no phone number. Then it recommended he optimize for phone calls.

A VP of Media at a major agency said he won’t send a single Manus output to clients because the data isn’t reliable enough.

The free tier burns through credits on a single reporting task. For agencies managing multiple accounts, you’d hit the daily limit before lunch.

Here’s what Manus actually is right now:

→ A reporting assistant with no execution ability
→ An analysis layer that sometimes hallucinates your metrics
→ A paid product sitting inside a free platform
→ A $2 billion bet that hasn’t shipped yet

Meta wants to fully automate ad buying by end of 2026. Manus is the first move. And I believe they’ll get there eventually.

But right now? You’re better off with a solid reporting setup and someone who actually knows how to read the data.

The AI tools that work for Meta advertisers today aren’t the ones Meta is building.

They’re the ones practitioners are building.

Have you tested Manus yet? What was your experience?

Meta just started telling you how much of your ad library it considers duplicate content.

Two new metrics. Creative Fatigue Score. Creative Similarity Score.

Most media buyers have not looked at either one yet.

Creative Fatigue Score tells you how fast your ads are dying. With GEM running the ranking layer, fatigue windows compressed from 4 to 6 weeks down to 1 to 3. 

If you are still on a monthly creative refresh cycle, you are running dead ads for half the month.

Creative Similarity Score is worse. It tells you how many of your ads the algorithm treats as the same creative.

High similarity means higher CPMs. The system penalizes repetition at the Entity ID level. Your 30 "variations" are competing against each other in the same auction for the same eyeballs.

Here is the diagnostic we run at BWM on every account:

→ Export the full ad library
→ Group creatives by visual weight. Same layout, same product angle, same background structure? Same Entity ID.
→ Count actual concepts. Static image. Meme format. Carousel. Lifestyle shot. Founder story. Problem/solution layout. Each one is a genuinely different signal to Andromeda.
→ Ratio check. If your concept count is under 20% of your total ad count, you have a diversity crisis disguised as a creative strategy.

The fix is not more ads. It is more different ads.

A headline swap is invisible to the retrieval engine.
A format change is not.

The brands we work with that keep CPMs stable are feeding Andromeda 10 to 15 distinct concepts inside simplified campaign structures. One campaign per objective. Broad targeting. Let the creative do the targeting.

Because in 2026, creative is targeting.

Pull up your ad library today. How many genuine concepts do you count?

I asked my ad account a question yesterday.

It answered.

Not through Ads Manager. Not through a dashboard. Not through a report someone built in Google Sheets.

From a terminal window on my laptop.

“What’s my best performing ad set this week by cost per purchase?”

Three seconds later, I had the answer. With context. With recommendations on what to scale and what to cut.

Then I said: “Pause everything above a $42 CPA.”

Done.

No clicking through campaigns. No filters. No bulk editing.

One sentence.

Here’s the setup:
Claude Code. Anthropic’s AI coding tool that lives in your terminal. You connect it to a Meta developer account and an access token. Now it can read and write to your ad account through the API.

But that’s just the foundation.

The real power is in skills. Custom instruction sets you build on top of Claude Code that teach it how to think about your specific ad account.

We’ve built skills for creative performance analysis. Budget reallocation logic. Diagnostic frameworks that flag exactly what’s broken and why.

You’re not just pulling data. You’re having a conversation with an AI that understands Meta ads strategy, has access to your live account, and can execute changes on the spot.

Ask it a question. Get an answer. Tell it what to do. It does it.

The brands that figure this out first won’t just save time.

They’ll operate on a completely different level than their competitors.

If you want to see how this actually works, DM me “TERMINAL.”

Nobody is an expert in AI ecommerce yet.

Not me. Not the guy selling you a $997 course on it.

The difference is I’ve been building for 18 months straight.

Some of those systems are already obsolete. Rebuilt them. Some have been updated 4 or 5 times. That’s the game right now.

Here’s what’s actually running inside our agency today:
Agents handling video editing.

Daily briefings generated before my team opens their laptops.

Client updates written and delivered automatically.
Google Ads audits. Meta Ads audits. Both agentic.

Daily media buying recommendations pushed to every buyer.

AI creative strategy mapped to dynamic matrices.

Cold outbound. 

Reactivation flows. 

Reporting dashboards.

All of it connected to one infrastructure layer.
Millions of tokens processed per day. Not in theory. In production.

The course creators screaming about AI have never run a single agent in a live client environment. They watched a YouTube video and built a slide deck.

Building AI systems for ecommerce isn’t a knowledge problem.

It’s a reps problem.

You have to build, break, rebuild, and run these things against real data with real dollars behind them.

That’s the only way to learn what actually works right now.

What AI systems are you actually running in your business? 

Not thinking about. Running.

Everyone’s chasing Claude skills and Cowork tutorials right now.

Building custom GPTs. Sharing OpenClaw repos. Posting about their latest prompt.

Cool. But that’s not where the real value is.
The real value is using these tools to build actual infrastructure for your business.

We just finished an internal app called BWM Systems. It runs our entire agency.

Here’s what’s inside:
Agentic daily recommendations running 24/7 analysis through a worker.ts deployed on Render. It never stops. It never sleeps. Every morning our team wakes up to fresh insights on every account.

Creative strategy mapped to dynamic matrices built on our database structure. It identifies top performing angles, hooks, tone of voice, and visual patterns across every client. Not gut feelings. Real data.

A bulk ad launcher that pushes directly into Meta through the API. Creative and copy sitting in a queue, ready to go live the second a client approves assets in ClickUp.

One app. One system. No more jumping between 3 different LLMs to get work done.

The people winning with AI right now aren’t the ones with the best prompts.

They’re the ones building systems that compound.
Skills are a starting point. Infrastructure is the destination.

If you want to see behind the scenes of how we built this, drop “BTS” in the comments and I’ll show you.

Every AI ad tool I've tested over the last 6 months has one thing in common.

They generate creatives. That's it.

No strategy behind what gets made. No way to launch it. No analysis on what's working. Just more ads you still have to figure out what to do with.

So we stopped waiting for someone to build what we actually needed.

And built it ourselves.

This week we shipped:
→ Strategist — AI creative strategy that builds concepts from your brand data, not generic prompts 
→ Agent Insights — daily AI analysis of what's working and why across your entire account 
→ Launch Pad — push ads directly into Meta from the platform. No downloading. No uploading. No Ads Manager. 
→ Campaign Ads — see every live ad mapped to performance data in one view → Sprint Planner — plan your next wave of creative tests with structure, not guesswork

This isn't an AI tool that gives you more to do.

It's the system that replaces half the workflow your team is doing manually right now.

We're opening early access to a small group to test it.

Comment "FEATURES" and I'll send you the details.

The founders scaling fastest right now are not better at Meta ads.

They are better at seeing what is happening inside their ad account without depending on anyone else.

Claude Code is a tool that runs on your computer. You talk to it in plain English. It reads your files, your exports, your data, connects to your Meta account. No dashboards. No waiting.

Here is what that looks like for a Shopify brand running Meta ads:
→ Connect via your Meta developer account via access token.
→ Ask it questions the way you would ask your strategist. "Which creatives are above our CAC target this week?" "Where is frequency spiking?" It answers with your actual numbers.
→ Build reusable audit frameworks so every review follows the same standard. 

No drift between analysts. No blind spots.

This does not replace your team. It gives you visibility you have never had before.

The founders who understand their own data make faster decisions. Faster decisions compound.

Have you tried this yet?

If you want to try this, leave a comment down below or shoot me a DM!

Most brands think they’re testing 15 creatives. Andromeda thinks they’re testing 3.

Here’s what’s actually happening inside the algorithm.

Meta groups creatives by visual similarity using Entity IDs. If the layout, imagery style, and visual weight are too close, they get bucketed together.

Different headline. Different color. Different CTA button.

Doesn’t matter. Andromeda sees the same ad.

That means your 15 “variations” are competing against each other in the same auction. Higher CPMs. Worse distribution. Faster fatigue.

The fix isn’t more ads. It’s more concepts.

A static image, a meme format, a carousel, a lifestyle shot, a founder story, a problem/solution layout. Those are genuinely different to the algorithm.

Color swaps and headline tweaks are not.
Most accounts we audit are running 10-20 ads that Andromeda treats like 3-4.

Then they blame the platform for rising costs.
The platform isn’t the problem. The creative diversity is.

How many genuinely different concepts are you running right now? Not ads. Concepts.

Vibecoding won’t save your business.

Everyone on YouTube makes it look like a weekend project.

“Just talk to the AI and it builds your app.”

Here’s what they don’t show you.

18 months.

Deep inside GitHub repositories.

Debugging systems at 1am after my kids go to sleep.

Rebuilding entire workflows because one API change broke the chain.

That’s the real cost of building something that actually works in production.

But here’s what those 18 months gave us.

We built a fully agentic ecommerce agency from the ground up.

Not a few automations duct-taped together.
A real operating system.

AI-powered content creation that runs on a schedule.

Static ad generation at scale pushed directly into Meta.

Agentic media buying that flags problems before they cost money.

A cold outbound system that fills our pipeline without a single manual email.

A reactivation engine connected to GoHighLevel that re-engages every old prospect automatically.
Every layer talks to the next.

Every system runs whether I’m at my desk or not.
And the only reason I could disappear into the code for 18 months is because I have a team that kept driving results for our clients every single day while I built.

That part doesn’t get enough credit.

Here’s the real takeaway.

Vibecoding is powerful. But it’s not plug and play.
The gap between a demo and a deployed system that handles real data, real clients, and real money is enormous.

Most people quit in that gap.

The ones who don’t end up with something their competitors can’t copy.

If you’re building AI systems for your agency or brand and want to compare notes, drop what you’re working on in the comments.

If you want a video on the whole things, comment “vibe code” and I’ll send it over.

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