Scale revenue with AI & tech

I decided to skip the traditional corporate path & start building in the AI x Sales space at 27. 
Here's the journey so far:

Age 18-21: Business school in Brussels, realized I needed practical experience
Age 22: Coding bootcamp + lucky Bitcoin exit gave me 50K to fund a world trip
Age 23: 12-country world tour learning new skills every month in a new country.
Age 24-26: Growth hacker roles at German startups, learned systems but felt unfulfilled 
Age 27: Co-founded ColdIQ with Mich
Age 28: Hit our first major milestones learning everything the hard way 
Age 29: Scaled to $6M ARR and became Clay's #1 global partner. Running a business that does $477K/month with 30+ team members across 4 continents.

It's been wild. Today through ColdIQ, we help B2B companies build AI-powered sales systems that work. 

We've run outbound for 300+ organizations and generated millions in pipeline.

The best part? We built this entirely remote with people I genuinely enjoy working with. 

Turns out you can have rapid growth AND life quality - you just need the right systems.

If you want to build your own AI sales agency, I teach everything in our ColdIQ Agency Accelerator, the exact playbook we used to hit $6M ARR in 2 years. 

From Clay workflows to hiring A-players to scaling without burning out.

If you're already doing $1M+ ARR and want help scaling your existing business, let's talk about our done-for-you services.

https://coldiq.com/

If you're not there yet, I share everything for free on LinkedIn and in our 7-day email course (in the featured section).

The AI x Sales opportunity is the biggest wealth creation event of our generation. The market is so massive that there's room for everyone to win.

Ready to start your agency? Join 130+ founders in our accelerator.

https://coldiq.com/accelerator-program

I turned 30 earlier this month.

I had no idea what I was doing for most of my twenties.

Moved countries. Started stuff that failed. Said yes to random things just to see what would happen.

Probably looked lost from the outside.

But here's what I think now:

Focusing too early is a trap.

I see people at 22 trying to "find their thing" and lock in fast. Pick the career. Pick the country.

But how do you know what to focus on if you haven't tried enough things yet?

You don't.

So you end up focused on the wrong thing. And you don't even know it.

That's worse than being "lost" for a few years.

Some people skip the messy phase. They lock in early. Look successful at 25. Then wake up at 30 wondering why they're not happy.

They focused, but not on the right things.

I needed those years of trying random things. Not because they all worked. Most didn't. But because now I actually know what I want.

I know which friendships matter. Not trying to keep up with 50 people anymore.

I know where I want to live. Done being the eternal nomad.

I know what we're building with ColdIQ. Done chasing every shiny opportunity.

We tested a lot in 2025. New offers. New markets. Some worked. Some didn't.

But now the picture is clear. We go into 2026 knowing exactly what to double down on.

You can't focus on the right thing until you've explored enough to know what the right thing is.

To the next decade 🥂

Alex Vacca 🧠🛠️

Co-Founder @ ColdIQ ($6M ARR) | Helped 300+ companies scale revenue with AI & Tech | #1 AI Sales Agency

lemlist hit $37M ARR.

Here’s the outbound engine behind it (and why it works so well)↓

Most people think lemlist grew by sending better cold emails.

They didn’t.

They built a system that turns content → intent → enriched data → personalised outreach at scale.

Here’s the exact workflow:

1️⃣ Content that attracts their ICP (not vanity content)

An influencer or internal creator publishes on LinkedIn - but not just any content.

It’s written to attract one specific persona with a problem lemlist solves.

Every comment, like, and share = a signal.
A signal that someone cares about the topic.

They use:

- Jungler to scrape all post interactions
- LinkedIn for content publishing

Because people are already familiar with their brand, reply rates are way higher than pure cold outreach.

2️⃣ Data routing & enrichment

Not every engager is worth contacting.
So they have a system to score, clean, and enrich.

They push all extracted contacts through:

- n8n for data routing
- Clay as the data hub (enrichment, scoring, workflow automation - all in one place)

Scoring includes:

→ Job title relevance
→ Engagement type
→ ICP match
→ Buying power indicators
→ Existing customer check
→ Tech stack + initiatives + recent activity

Here’s the thing nobody talks about:

If the enrichment is bad, the personalization fails.
If the personalization fails, the whole system collapses.

This is where lemlist invested the most time - and where most teams cut corners.

3️⃣ AI personalization & multi-channel outreach

Personalization isn’t “{first_name}, loved your post!”

They use:

lemlist’s AI variables → genuine first-lines for every prospect
Multi-channel sequences → email + LinkedIn for maximum reach

A typical opener:

“Hey {{first_name}}, saw you engaged with our post on {topic}. Looks like you’re focusing on {initiative} — happy to share what’s worked for us.”

Warm context + real personalization + multi-channel = consistent replies.

Teams spend hours “perfecting” cold emails.
lemlist spends hours perfecting context - and lets AI scale the rest.

4️⃣ Meeting booked

Warm, relevant outreach performs.

This is one of the most efficient ways to:

→ Warm up leads
→ Segment the highest quality ones
→ Gently ping them with context at exactly the right time

This is one of lemlist's highest performing outbound plays. It's also a play we love to run at ColdIQ.

They've spent months testing and optimizing this workflow to run on autopilot.

The compound effect takes time, but when it kicks in, it's massive.

If you want to implement something like this - we'll literally run this entire workflow for you, along with other high-converting GTM plays.

Drop me a DM👇

These 10 roles didn't exist a year ago.

Now they're replacing entire teams.

I've talked to so many people worried about AI "taking jobs."

Meanwhile, the companies actually hiring are creating new roles that didn't exist 12 months ago.

Here's what they're hiring for:

GROWTH ROLES

1/ Vibe Marketer / Head of Demand Gen

Runs fully automated funnels end-to-end.
Ads → landing pages → emails → workflows.

Stack: ChatGPT, Make, Customer.io, Framer, arcads AI, Fibbler

2/ Social Media Engineer

Uses AI to research what's working, write posts, and distribute across platforms.

Stack: Runway, Midjourney, Ideogram, Make, Taplio, Scripe

3/ Video Content Engineer

Creates high-production video. AI handles the editing, cuts, effects, voices, animation.

Stack: Google Veo, Runway, Arcads, ElevenLabs, Kling AI

4/ Content Engineer

Builds SEO + content systems. Ranks in Google, ranks in LLMs, builds programmatic content machines.

Stack: AirOps, Mentions, Surfer, Ahrefs, AlsoAsked

5/ GTM Engineer

Finds prospects, enriches data, personalizes messaging, runs outbound at 10x the volume.

Stack: Clay, Instantly.ai, Artisan, Expandi, FullEnrich

OPERATIONS ROLES

6/ Ops Engineer

Deletes half your manual work overnight.
Every system → automated. Every process → rebuilt.

Stack: n8n, Flowgent, Airtable, Slack, ClickUp

7/ RevOps & Attribution Engineer

Owns the full customer journey. Tracks anonymous research → pipeline → conversion → retention.

Stack: Attio, Unify, Common Room, Usermaven, Default, Clay

8/ Talent/HR Engineer

Sources candidates, screens them, automates half the hiring process.

Stack: Clay, LinkedIn, Airtable, Ashby, Fetcher

PRODUCT ROLES

9/ Product Engineer

Builds apps without waiting on engineering timelines. AI handles design, code, logic, prototypes.

Stack: Lovable, GitHub Copilot, ChatGPT, Figma AI, Supabase, Guideflow

10/ AI Agent Engineer

Builds agents that run workflows across sales, ops, support, and product.

Stack: Relevance AI, n8n, Voiceflow, Claude

These companies are rebuilding departments around AI-first workflows.

Smaller teams. Higher output.

By 2026, most teams will have at least 5 of these roles.

Which one are you seeing the most demand for?

We just crossed $6,000,000 ARR.

Here's the tech stack that made it happen ↓

1️⃣ Content & Inbound

We generate over 100 warm leads per month via LinkedIn.

These come from my account (45,600+ followers) and the rest of the ColdIQ team (230,000+ followers).

I use:

- Scripe for post ideas + analytics
- Notion as my content calendar to keep me organised

We generated ~50M impressions on X last month, which is honestly wild. And for this we use:

- Typefully to visualize & draft threads: makes the whole process way smoother

I am getting some momentum behind my YouTube, so at the moment I use:

- Two Sony FX30 camera for filming
- Tella for screen & audio recording (super clean output)
- vidIQ to gain inspiration from successful videos, basically reverse engineering what works

We drove 102,000 visitors to our website in the last 90 days. 35,000+ come from SEO alone. We use:

- Ahrefs for keyword research (can't live without it)
- Webflow's CMS to host/publish our articles
- Surfer to optimize our copywriting for search engines

We have 7,000+ subscribers to our newsletter, and growing. We use:

- beehiiv to send our welcome sequence & weekly emails

2️⃣ Outbound Engine

- We identify website visitors with Instantly.ai & Vector 👻
- Based on their firmographics + page visit, we:

→ Email them via Instantly.ai

→ or connect + send voice notes via lemlist

- more personal touch

- For data: Prospeo.io, LeadMagic, Clay, FullEnrich
- For AI research & personalization: ChatGPT, Claude
- For deliverability: a mix of Gmail + Outlook inboxes

3️⃣ Ops & Project Management

- Everything runs in Airtable
- We automate with n8n, Make or Relevance AI, depending on what we're trying to do
- Big-picture process flows? We map those in @Puzzle
- Internal comms → Slack

4️⃣ Sales & Closing

- Calls get booked through Default
- We use Attention to record & summarize meetings
- Proposals: Qwilr (clean, professional, gets signed)
- Banking: Mercury
- Contracts: PandaDoc
- Payments: Stripe

We've spent months testing, tweaking, and optimizing this entire stack to work together seamlessly.

Tech moves fast. Really fast.

New tools drop every week, and what worked 6 months ago might not be the best option today.

I break down the complete stack + how we actually use these tools on my YouTube.

Subscribe here → https://lnkd.in/dKsZpY2D

What tools are you running? Drop them below 👇

Content helped ColdIQ hit $6M ARR.

And this workflow turns every single post into pipeline.

We built a system that converts LinkedIn engagement into qualified meetings.

Here's the breakdown we use at ColdIQ:

STEP 1: CAPTURE ENGAGEMENT IN REAL-TIME

Every like, comment, and profile view gets tracked automatically.

When someone likes OR comments on your post they're basically telling you they actually care about what you're talking about.

We use Trigify.io and Teamfluence™ to monitor all LinkedIn engagement signals.

Most people get that engagement and then just move on to the next post - we actually do something with it.R

STEP 2: INSTANT ENRICHMENT

The moment someone engages, Clay pulls full contact and company data.

Job title, company size, tech stack, funding rounds, hiring signals - all of it happens in seconds.

STEP 3: AI QUALIFICATION

Not everyone who likes your post is actually a good fit prospect.

We use ChatGPT and Claude to score each contact against our ICP criteria.

- Low fit? Filtered out immediately
- High fit? They move to the next step

The AI looks at things like:

- B2B vs B2C
- Geographic fit
- Company size match
- Estimated customer lifetime value

STEP 4: CRM DEDUPLICATION

Before we do anything, we check: is this person already in our system?

Already a customer? Already in active conversations? Skip them completely.

New contact? Push to sequence.

The fastest way to look like an idiot is cold emailing your existing customers.

STEP 5: MULTI-SOURCE EMAIL VERIFICATION

We waterfall through Prospeo.io, FullEnrich, and LeadMagic until we get a verified email.

No single provider has 100% coverage.

But stack three of them together? You're getting close to 95% hit rate.

STEP 6: PERSONALIZED OUTREACH ON AUTOPILOT

Each prospect receives a tailored message via Instantly.ai that references the exact post they engaged with.

Not generic "Hey {firstName}" nonsense.

It's contextual: "Saw you engaged with my post about Clay workflows - we just built something similar for a client in your space that books them 2-3 meetings per week."

STEP 7: MEETING BOOKED

This system generated 144 meetings for us in a single month.

And it runs 24/7 without human intervention because:

- Every piece of content becomes a lead magnet
- Every engagement becomes a qualified opportunity
- The entire conversion happens automatically

If you're posting on LinkedIn without this system you're basically just creating content and hoping meetings happen (which they won't).

That's not how it works in 2025.

The companies winning are the ones that built actual systems to convert attention into pipeline.

Are you tracking your LinkedIn engagement right now?

(We can build this entire workflow for you, plus show you the other plays that got us to $6M ARR)

P.S: Tools don't book meetings. Systems do. And this is the system that's working right now.

OpenAI just sent us this award for passing 10 billion tokens.

Here is what I learnt: being too smart is slowing you down.

The smartest people I know are the slowest to start.

- They read about AI.
- They follow the news.
- They watch the tutorials.

But they don't build anything.

Their logic:

"Why learn this if it's outdated in 6 months?"
"Why build this if a new model does it better?"
"Why start now if everything keeps changing?"

Sounds smart.

But it's actually not.

Here's what actually happens when you use AI every day:

- You learn how it really works.
- You find what it's good at and what it sucks at.
- You build intuition you can't get from reading.

Yeah, some stuff we built 2 years ago is completely outdated and we constantly need to replace old workflows we built.

That's the price to pay but despite that we still learned more than the people who waited and never built anything. 

When a new model drops, we figure out what we can do with it.

Because we already understand the fundamentals.

The people still waiting?

Starting from zero and probably will tell themselves that they will start when GPT 8 will release.

The world moves fast.

You can watch it move.
Or move with it.

10 billion tokens later, I'm glad we moved.

Stop waiting for things to stabilize because they won't.

Just start building.

Everyone else is also just figuring it out.

Alex Vacca

Talks about #ai, #sales, #automation, #salestools, and #leadgeneration

The sales flow that generated $966K ARR.

Nearly $1M in new revenue in 30 days.

Most people see the content - the LinkedIn posts, the videos, all of it. 
But content is just the front end.

Behind the scenes, there's a whole system.

The team posts across LinkedIn daily.

But none of that means anything without closers who can convert attention into pipeline.

That's where Dujam Dunato and Jan Rasmussen Mitjana  come in.

They're the ones handling inbound, qualifying leads, running calls, and closing deals at scale.

Here's the exact sales flow they used to generate $966K ARR in one month:

1/ Pre-call qualification

We only book calls with prospects we know we can help.

Qualification happens automatically through:

- Inbound routing systems
- Video testimonials that build trust before the call
- Website assets that pre-educate prospects

LinkedIn connection automation for long-term nurturing

Tools:

↳ Default - auto-qualification + routing
↳ lemlist - LinkedIn connection automation
↳ VSL - makes sure prospects understand our offer before speaking to us

This removes 90% of the time-wasters and lets the team focus on revenue-critical conversations.

2/ Discovery & research

Before any call, we prepare - but we don’t do it manually.

We use:

a. Automatic prospect intelligence via Clay + Zapier
b. Funding stage + headcount research
c. Stakeholder identification + role tenure
d. Tracking strategic hires, initiatives, and timing signals

Tools:

↳ SPICED (Winning by Design) - call structure
↳ Clay + Zapier - pre-call research + aggregation
↳ Fireflies.ai - real-time AI note-taking + CRM automation
↳ Qwilr - digital sales room + proposals

This means reps walk into every call fully briefed without lifting a finger.

3/ Follow-up & nurturing

For leads who aren’t ready to sign immediately, we run:

a. Automated follow-up sequences with real value
b. YouTube video follow-ups (no boring text-based emails)
c. Multi-threading across LinkedIn to engage all decision-makers

Tools:

↳ Customer.io & Attio - automated follow-ups
↳ LinkedIn - multi-threading workflows
↳ YouTube content from me & Michel - authority-led nurturing

This keeps prospects warm without our team writing endless manual replies.

4/ Why this closed $966K in one month

Qualification: Only the right people reach our closers
Education: Prospects arrive informed, reducing friction
Automation: Reps spend their time selling, not admin

Content: LinkedIn + YouTube turn strangers into warm, ready-to-buy leads

If you have any questions, feel free to drop any of the guys above a message!

4 GTM agents that save 2-5 hours per client every day.

They run:

Prospecting, content
AND market research on autopilot.

Most teams think AI is about writing faster. It's not.

It's about eliminating the 80% of GTM work that never should've been manual in the first place.

Here's the system:

AGENT 1: LEAD RESEARCH AUTOMATION

Manual prospecting is dead.

Every company profile gets captured, enriched, and scored automatically.

Pipeline:

- GhostGenius captures profiles
- We filter by credibility signals (200+ followers, real website, actual activity)
- GPT scores each profile against our ICP (in real time)
- LinkedIn IDs dedupe contacts so we never hit the same prospect twice

Clean, qualified prospects → straight into Google Sheets for outbound.

AGENT 2: LOCAL PROSPECTING ENGINE

Apify pulls local businesses from Google Maps.
Raw Google Maps data is a mess. Half the info is missing or outdated.

The fix:

- Google Search API fills missing metadata
- We scrape each website for keywords, offers, tech stack
- GPT classifies and enriches the business profile
- We extract missing emails, numbers, contact pages

Export to Airtable or Sheets → done

This turns low-quality data into sales-ready records.

AGENT 3: BRAND CONTENT GENERATOR

Drop a brand brief into a Google Form. Wake up to:

- LinkedIn posts
- Carousel copy
- Newsletters
- Hooks
- CTAs
- Variations
- TOV matched drafts

All written in your style, using your positioning.

Drafts go straight into Notion or Google Docs, ready for a 10 minute edit.

AGENT 4: REDDIT INTEL COLLECTOR

This one is my unfair advantage.

Most GTM teams ignore Reddit.
But it’s where your prospects say the things they’d never admit on a sales call.

Pipeline:

- Input a brand or website
- GPT identifies ICP signals
- Reddit API scrapes relevant threads
- GPT summarises pain points, the language prospects use, their frustrations, what they actually care about
- A daily insight report sent to your inbox

This is the closest thing to reading your market’s mind.

THE RESULT: AUTOPILOT PIPELINE

These 4 agents work together to create a system that runs 24/7:

1. High-fit leads → already in your CRM
2. Weekly content → drafted before you wake up
3. Market intelligence → delivered before your first coffee
4. Zero hours wasted on research, scraping, or repetitive admin

You’re not “doing more.”
You’re just letting the system do what humans shouldn’t.

And here’s the real shift:

> Companies scaling in 2025 aren’t hiring more SDRs.
> They’re eliminating the work SDRs used to do.

If you’re still manually researching prospects and writing content from scratch, you're working 10x harder than necessary.

We build these exact workflows in n8n - plus the other automation plays that save 15+ hours per week, per team member.

Which one are you building first?

4 GTM n8n Agents 

Here’s what our numbers look like today:

→ $6,000,000 ARR
→ $40k–$80k new MRR added each month
→ Predictable pipeline month after month

All powered by a GTM funnel that took us 18 months to refine.

Here’s the full breakdown, the exact one we still use internally.

1️⃣ Awareness (the volume engine)

Not every impression is equal, but volume absolutely matters.

Here is how we look at it:

Visibility → Leads
Leads → Meetings
Meetings → Proposals
Proposals → Revenue

Here's what we're generating right now:

100,000+ quarterly website visits (SEO + Paid)
2.5M–3M monthly impressions on LinkedIn
5K–20K monthly YouTube views

Tools:

→ Taplio, Scripe, Notion (content)
→ AirOps, Ahrefs, Surfer (SEO)
→ Fibbler, arcadsAI (paid)

2️⃣ Interest

Getting seen is easy. Getting buyers to take action is what separates good from great imo.

So we increase conversion rates by:

→ Running monthly webinars (warm nurturing at scale)
→ Sharing lead magnets that educate
→ Using one-step smart forms to auto-route leads instantly
→ Identifying anonymous visitors and re-engaging them (this one's a game-changer)

Tools:

→ Instantly.ai, Vector 👻, Midbound (visitor ID)
→ Default (automated routing)

3️⃣ Consideration

Attention doesn't convert unless buyers understand what you do.

So we:

→ Built multiple VSLs that explain the offer clearly
→ Share success stories with full breakdowns of how we did it

Tools:

→ Wistia (VSL hosting + video testimonials)

4️⃣ Conversion

At this stage we talk to more qualified leads, more often.
Here's how we maximize conversion:

Email nurture sequences keeping the pipeline warm
Automated outreach to high-potential accounts
More open slots for sales calls
Consultative selling on Google Meet

Tools:

→ Clay, OpenAI (lead scoring + segmentation)
→ Customer.io, lemlist, Instantly.ai (outbound + nurture)
→ Attention, Attio (meeting intelligence, pipeline analytics)
→ Qwilr, PandaDoc (proposals, contracts)

Is it perfect? No.
Does it work? Very well.

This GTM system powers our growth month after month. We're always iterating, always improving.

What would you improve? 👇

Behind Snowflake's $4B ARR...

$2.4B generated by SDRs alone.

They have a crazy 5 step system that warms every account before outreach happens.

Snowflake turns every SDR into a closer by making sure prospects already know who they are before the first touch.

This is the framework behind their 46% meeting rate (vs 17% in regions that ignored it):

1/ Collaboration

Snowflake run one GTM strategy, one account list, one message, one goal.

Marketing feeds Sales insights they can act on.
Sales executes within 14 days.

Most companies operate in silos. Snowflake operates as a single unit.

2/ Intelligence

60% of buying research happens anonymously.
Snowflake listen and act on intent signals.

So...

First-party signals like website visits, email engagement, product usage.
Third-party signals like competitor research, job changes, funding rounds.

They use tools like Bombora to flag "high-propensity" accounts - which convert 4x better than random CRM leads.

3/ Activation

When an account shows buying intent, Snowflake launches a 3-week sequence:

Weeks 1-2: ABM warms the account with tailored content, ads, emails, and microsites.
Week 3: SDRs reach out.

Prospects are then familiar with Snowflake before they make contact.

36% meeting rate for pre-warmed accounts vs 10% for pure cold.

That's 3.6x more meetings without sending more messages.

4/ Engagement

Snowflake hits accounts from multiple angles, but always with one consistent story.

- Personalized emails
- LinkedIn outreach
- Custom microsites
- Calls

Their personalized microsites alone deliver 4x higher meeting rates than generic ones.

Nothing feels random.
Every touch reinforces the same message.

5/ Optimization

Every two weeks, ABM, SDRs, and AEs run alignment sessions.
From this, they can see:

- What's resonating
- What's stalling
- Which accounts are warming up
- Which messages are working

Snowflake doesn't track attribution.
They measure impact at the account level and optimize the entire system together.

The results?

- 2-4x more meetings on ABM accounts
- Deals close 2x faster
- Top-tier accounts convert 5x better
- 40% of Tier A accounts turn into pipeline (vs 10% for non-ABM regions)

Snowflake obviously has a huge budget.
But most teams don't need 300 SDRs or their budget to use this.

You just need the sequence:
Align Marketing, SDR, and Sales on shared account goals.

Track first-party intent - website visits, email engagement, product usage.
Warm accounts two weeks before outbound.

Are you warming accounts before you reach out?

Snowflake Outbound Strategy Breakdown 

Our $550K/month sales engine runs on 9 tools.

Here’s exactly what’s in the stack.

(Pick 1 to 2 tools per category.)

1. Start with clean data
↳ Everything starts with clean data (who you're going after and why).

My top picks:

- Openmart - Solid for local and small business sourcing
- Clay - Enrichment, AI agents, and intent all in one place
- LinkedIn Sales Navigator - Still the goldmine for B2B targeting
- Ocean.io - Great for niche segmentation + lookalike audiences

2. Enrich your contacts
↳ Best outbound in the world doesn't matter if you're bouncing. Get verified emails and keep your bounce rate under 3%.

Good options:

- Prospeo.io, LeadMagic - Great for fast enrichment
- FullEnrich, Clay - Waterfall enrichment made easy

Bonus: Relevance AI if you prefer building flows with agents

3. Track buying intent
↳ Signals help you reach out when timing is right.

Tools worth watching:

- Common Room - Tracks a wide spectrum of buyer signals
- Unify - Intent, AI agents, and orchestration in one place
- PhantomBuster - Arguably the best for social intent

4. Engage across channels
↳ Now that your list is ready, start conversations that convert.

Channel tools:

- Instantly.ai & Smartlead - Email deliverability + volume
- lemlist - Multichannel, creative campaign builder

Also watching: Woodpecker.co (now supports Claude-native campaigns).

5. Move pipeline forward
↳ Tools to help you close, track, and repeat.

Helpful stack:

- Attention - Call intelligence + meeting transcripts
- Default - Automates inbound lead routing
- Attio - A modern CRM for deal tracking
- Breakcold - Personal 1:1 social selling
- Qwilr - Beautiful, shareable proposal docs

The tech stack behind our $550K/month isn't about having the most tools. It's about having tools that actually integrate.

Pick your stack based on what works together (not what's trending on Twitter this week).

What's the one tool in your stack you actually can't live without?

138 meetings from 144 LinkedIn posts (that's almost 1:1).

Here's our $6M ARR workflow:

Step 1: Content volume that converts

We published 144 LinkedIn posts last month. Not random content, everything's built around ICP pain points.

We're using Taplio and Scripe for inspiration, but we're analyzing what books meetings. We look at hooks, visuals, and formats from posts that converted.

Step 2: Paid amplification with actual ROI tracking

$5,100 in LinkedIn Ad spend generated 155K extra impressions at $33 CPM. But we ONLY boost organic posts that have already booked meetings.

We track which persona converts from each post type, then push those winning posts to that exact audience.

Step 3: Intent capture across every touchpoint

This is where most agencies lose pipeline. We're tracking everyone who shows intent but doesn't book.

Tool stack breakdown:

Website visitors: Instantly.ai, Midbound Vector 👻 and Common Room for anonymous visitor identification.

LinkedIn engagement: Trigify.io and Teamfluence™ for social signal monitoring

Step 4: AI-powered lead scoring in Clay

Every lead gets routed to Clay for intelligent scoring. We use Claygent for lead research, then OpenAI to segment into 3 tiers based on fit and timing.

Different tiers get different outreach strategies. A Tier 1 lead gets way more personalization than a Tier 3.

Step 5: Data enrichment that works

Prospeo.io and LeadMagic for emails, FullEnrich for phone numbers - all happening inside Clay so we don't lose context.

Step 6: Multi-channel re-engagement based on score

This isn't random outreach. Every message is contextual, every touchpoint provides value.

The results that matter:

- Made us 557k in revenue for October
- Team grew to 30+ FTEs
- 750+ meetings booked in 2025 already
- One client: $272,600 closed at 7X ROAS in 90 days

The system works because it's not just outbound - it's orchestrated revenue generation across every touchpoint where your buyers show up.

We're adding this GTM workflow FREE for the next 3 ghostwriting clients (15 of 18 spots already taken). Comment 'CONTENTIQ' to grabs yours ☝️

Cold email got us to $6M ARR.

LinkedIn Ads took our results to an entirely different level.

People keep asking me which one generates more leads.

We have run cold email for over 200+ B2B companies - and layered LinkedIn Ads on top.

1/ What it takes to make each one work

LinkedIn Ads

You win or lose on:

- Audience targeting
- Scroll-stopping creative
- Landing pages that convert

If one piece breaks, the whole thing falls apart.

Cold Email

The game is all about:

- Short, punchy messaging
- Clean personalization
- Perfect infrastructure

Nothing else matters if your email doesn't reach the inbox.

2/ Speed to results

LinkedIn Ads:

Slow start. Setup, approvals, creative testing, landing page tuning.
Takes time but compounds fast once you find a winner.

Cold Email:

Instant.
If your domain + infra + offer are dialed in, you can book meetings on Day 1.

3/ Cost to reach 10,000 prospects

LinkedIn Ads:
~$1,500–$2,500
(depends on creative + ~$30 CPM)

Cold Email:
~$500–$1,000
(infrastructure + data + sending tools)

Pretty similar, but cold email has more moving parts.

4/ The stacks that work

LinkedIn Ads Stack

Figma, CapCut → creative
Default, Zapier → routing + workflows
Fibbler, Usermaven → attribution + analytics

Cold Email Stack

Instantly.ai, lemlist → sending
ColdIQ infra + Instantly → domains, warmup, deliverability
Wiza, LeadMagic, Prospeo.io, FullEnrich → data + enrichment

5/ Personalization depth

LinkedIn Ads:

Segment-level personalization.
Everyone in “Sales leaders in AI SaaS” sees the same creative.

Cold Email:

True 1:1 personalization.

- Individual pain points
- Individual triggers
- Individual context

6/ Deliverability & visibility

LinkedIn Ads:

95–99% visibility
Guaranteed. They see it.

Cold Email:
60–70% inbox placement if your infra is world-class.
Spam risk always exists.

7/ The real challenge with each

LinkedIn Ads:

Finding the perfect creative + offer + landing page combo.
Most people burn budget before they get the formula right.

Cold Email:

Deliverability.
The technical side is what kills most campaigns.

So which one works better?

Cold email is:

→ Faster
→ Cheaper to test
→ Easier to personalize

LinkedIn Ads are:

→ More scalable
→ More visible
→ More predictable

We run both because they multiply each other:

Cold email drives conversations.
LinkedIn Ads creates familiarity.
Together, reply rates go up, CPL drops, and close rates jump.

What are you running right now - LinkedIn Ads, cold email, or both?👇

Had lunch with Charles Tenot from lemlist last month.

The main takeaway is not the $40M+ ARR or the Claap acquisition.

It's how generous he is with his time.

You'd expect someone running a company this size to be impossible to reach.

The best operators I know are ruthless about time blocking. They protect their calendar like their life depends on it and are great at saying no to most things. And yet Charles still makes time to help people.

A year ago, we had a tough decision to make about promoting someone to Head of Sales. We reached out to Charles. He jumped on a call the same week and walked us through how they handled similar decisions at lemlist.

Any question about growth, team structure, scaling challenges, he's always ready to share what he has learned.

lemlist started with $1,000. Guillaume Moubeche bootstrapped the whole thing. They turned down $20M and $30M investment offers because they wanted to stay independent.

Charles took over as CEO when they hit a plateau. Since then, he's nearly tripled their ARR and built a team of 100+ people.

Now they just acquired Claap for $25M. No VC money. Just profits from a business they built the right way.

The lesson here isn't about revenue numbers.

It's that you can scale to $40M+ and still be the kind of person who makes time to help people.

Congrats to the entire lemlist team on the Claap acquisition.

One of the best bootstrapped stories in European SaaS.

P.S. I want to pay this forward. Every month, I'll pick one person to do a free consulting session with. If you're building something and need advice on growth, outbound, or scaling your team 👇 drop a comment below.

I’ve hired over 50 people and wasted more than $200K on the wrong ones.

It wasn’t a “talent problem.”
It was a me problem - I was hiring using the wrong criteria.

Until I learned the only hiring framework I still use today:

It's called the Pyramid of Talent.
It maps every person into 5 levels based on one thing:

How much direction they need to do great work.

I used to hire based on resume or "vibe”
This framework changed that for me.

Here's what I do now:

Level 1: Liability

Even when you tell them exactly what to do, they mess it up.
They need constant supervision and still deliver bad quality work.

Fire fast. Don’t negotiate with yourself. 

Level 2: Order Taker

You tell them what, how, and when.
Then it gets done.

This is where 80% of hires live.
They're reliable but need clear direction every single time.

Level 3: Problem Solver

You give them the what.
They figure out the how.

They work independently, ask good questions, and execute without handholding.

Level 4: Systems Thinker

You show them the problem.
They build the entire system to solve it—people, process, everything.

These people don't just solve today's problem.
They make sure it never happens again.

Level 5: Superstar

They identify the problems before you do.
And solve them without being asked.

They see around corners.

Before I kept hiring Level 2 people and giving them Level 5 tasks.

Or worse…

I hired Level 5 people and gave them Level 2 tasks.
Micromanaged them with SOPs for everything.

Both = expensive mistakes.

Here’s what I would recommend:
Match the level to the task BEFORE you hire.

Stop hiring "generally good people" and hoping they fit.
Start hiring for the SPECIFIC level the role requires.

Before I hire or delegate anything, I ask:

"What level does this task actually require?"

Then I only interview people at that level.

What level do you hire for most?

PS: Shoutout to Luca Carrese our Superstar

How I'd build a repeatable outbound system if I had to start from scratch:

(There's a public database of your competitor's churn reasons... and most teams aren't using it)

1/ I'd start by scraping competitor reviews

You can use G2. Or Capterra. Or Trustpilot.

And it's full of pain points, written by people actively looking for a better option.

Focus on 2–3 core competitors with a decent number of reviews.

It's a goldmine. You'll find everything from UI complaints to missing integrations to slow support.

Tools you can use:
- n8n / Make (for scraping)
- Apify / PhantomBuster (pre-built scrapers)

2/ I'd extract pain themes using AI

We don't read these manually.

We use ChatGPT to group complaints into themes:
- Feature gaps
- Support response time
- UX or onboarding issues
- Security concerns
- Pricing

You now have a live database of what your prospect hates about their current tool.

Tools you can use:
- ChatGPT (for clustering complaints)
- Google Sheets (for organizing themes)

3/ I'd align those complaints with my actual positioning

Map those complaints to your actual value props.

Here are 3 examples:

a. If their reviews mention "hidden fees," and your pricing is transparent, lean into that.
b. If they complain about integrations you support, name them.
c. If support is a weakness and you have a live-chat SLA, say it.

Now you're not just pitching. You're presenting a clear solution to a known frustration.

Tools you can use:
- Loom (for quick demo videos)
- Your pricing page / integration docs (as proof points)

4/ I'd launch targeted outbound

Once we know who's unhappy and why, we push that data into:
- Clay (for enrichment + personalization)
- Instantly.ai (for sending)

The messaging angle is already validated, and the frustration warms the list.

You're simply showing up with a better option.

Tools you can use:
- Clay (enrichment + personalization)
- Instantly.ai / Smartlead (for sending)

5/ I'd automate it into a system that runs weekly

We've built versions of this using:
- n8n (for scraping)
- ChatGPT (for clustering complaints)
- Google Sheets (for inputs)
- Clay + Instantly.ai (for execution)

It runs weekly. We review angles, update copy, and refresh the list.

Once it's live, it becomes one of your highest-converting outbound motions.

Why? Because you're hitting real pain points with a proven better solution.

Tools you can use:
- n8n / Make (workflow automation)
- ChatGPT (analysis)
- Google Sheets (central hub)
- Clay + Instantly.ai (execution)

6/ I'd run this consistently

This works across industries, and especially well in crowded SaaS categories.

But it requires setup. And it requires letting the system run long enough to see results.

Give it a shot.

P.S: Questions? Drop them below or DM me. Happy to unpack any step. 👇

AI agents are replacing entire GTM workflows.

So I tested 50+ of them to see which ones perform.

Most perform great in demos.

Then I plug them into our workflows and... not so much.
So I ran them through everything we use at ColdIQ.

Research, enrichment, outbound, scoring, support - the whole lot.

Some were fine. Most were absolute garbage.

So we consolidated everything the team found, compared notes, and built a list of the ones that consistently delivered.

Here's what worked... ↓

1️⃣ Sales Agents

- Artisan
- Valley
- Topo (YC W24)
- AiSDR

2️⃣ Research Agents

- Claygent
- Airtop
- Attio

3️⃣ Customer Service Agents

- Intercom
- Parahelp
- Forethought
- Sierra

4️⃣ Visual Agent Builders

- n8n
- Relevance AI
- Lindy
- Wordware (YC S24)
- Dify
- Taskade

5️⃣ Marketing AI Assistants

- Tome
- Aomni
- Copy.ai
- Jasper

6️⃣ AI Executive Assistants

- Fyxer AI
- Tasker AI
- Shortwave

7️⃣ Enterprise Development Platforms

- StackAI
- Microsoft Autogen
- LlamaIndex
- CrewAI
- LangChain
- Cohere

8️⃣ Ready-Made Agent Libraries

- Beam AI
- Sintra
- Lyzr AI

What agent tools am I missing from this list?

Drop them in the comments, always looking to test new ones.

P.S. Give Kenny Damian a follow. He's the goat when it comes to AI agents.

ColdIQ made 557k in revenue last month.

80% came from content.

Not ads.
Not cold calling.
Content.

Last month we launched ContentIQ - the system behind all of it.

Most people talk about “posting more.”

I want to show you what actually drives revenue.

Here’s the full breakdown of how we do it at ContentIQ 👇

1️⃣ Content foundation (the part everyone skips)

Before the engine runs, we build the infrastructure.

Phase 1: Onboarding

The non-negotiables:

- 1-hour strategy call → sharpen positioning
- Content audit → reality vs perception
- Voice capture → so your content sounds like you
- ICP definition → clarity = revenue
- Content calendar → narrative arcs, not random posts
- Community channel setup → where engagement compounds

Tools:
Gmail, WhatsApp, Slack
Attention.ai, Circleback, Loom
Clay, ChatGPT
Asana, Notion, Monday

This foundation is 70% of the results.

Phase 2: The content engine

Two tracks running in parallel:

Track 1: Creation

- Bi-weekly founder interviews
- Extract ideas, frameworks, stories
- Weekly content plans
- Graphic design
- Approval flow

Track 2: Production

- Finalised + delivered in 2–3 days
- Speed = momentum. Momentum = revenue.

Tools:
Canva, Figma, Adobe
Taplio, Scripe
(plus everything from Phase 1)

2️⃣ Lead tracking & scoring

Most companies post and hope for the best.

We post and measure.

We track:

- Profile views
- Impressions
- Comments
- Saves
- DMs (highest intent)
- Engagement depth

We run ICP 1 and ICP 2 separately.

Because:

A profile view ≠ a profile view.
A comment ≠ a comment.
A DM ≠ a DM.

We score each action so we know who is engaging and how qualified they are.

Tool: Teamfluence™

3️⃣ Automated outreach (the secret sauce)

All that engagement data flows into the automation stack.

Here’s what happens behind the scenes:

1. High-intent signals identified
2. Lead enriched with additional data
3. ICP-fit scored
4. Personalised outreach triggered
5. Across email + LinkedIn

The system does the work.

Tools:
Clay
Attio
Common Room

4️⃣ The Funnel Architecture

Most teams do ONE thing and wonder why they plateau.

Here’s the full blueprint:

→ LinkedIn content = Awareness + credibility
→ Engagement tracking = Intent identification
→ Automated outbound = Intent → conversations → revenue

When all three connect, you stop “posting content”…
and start building a pipeline engine.

---

5️⃣ The offer

For the first 10 signups to ContentIQ, we’re giving you:

The entire automated outreach machine
+
The full content engine.

Not just posts.
Not templates.
The whole workflow that built our business.

Here is the link: https://lnkd.in/ddStnRu3
(And yes… this is where it gets really good 👀)

Lemlist's CEO showed us how they built a $37M ARR SaaS.

One thing stood out.

Every part of their growth has a system behind it.

Here's the breakdown:

1️⃣ Content Engine

Their team has 300,000+ combined followers on LinkedIn.

And it's not random. It's coordinated:

- Guillaume Moubeche
- Charles Tenot
- Kévin Moënne-Loccoz
- Lucas Perret
- Tal Baker-Phillips
- Erwan Gauthier

Each owns a lane (growth, SaaS, CEO lessons, etc.)

Plus 200K+ monthly SEO visitors.

Stack: Figma, Storyblok, Taplio, Ahrefs, Semrush

2️⃣ Outbound Engine

Yes, they use lemlist.

But there's a lot more behind it:

Data: Apollo, Prospeo.io, BuiltWith, Crunchbase
Intent: LoneScale, Snitcher, G2
AI: Dust, Clay, OpenAI, Claude, Mistral

They find buyers before they start looking.

3️⃣ Product Infrastructure

200K+ monthly visits → 7–8% convert → 15,000+ signups/month.

Stack: BigQuery, Google Cloud, Holistics, RudderStack,Replit, Mixpanel

4️⃣ Revenue Ops

Last month their sales team closed $685K ARR.

Sales: Hyperline, Claap, lemcal, HubSpot
Marketing: Customer.io, Default, Webflow
Finance & Support: Stripe, Qonto, Pennylane, ProfitWell, Intercom
Team: Slack, Notion

This is what $37M ARR ops looks like.

What part of their stack surprised you?

taplio

Alex ️'s Linkedin Analytics

Alex Vacca 🧠🛠️

Performance ScoreAlex Vacca 🧠🛠️'s LinkedIn Performance

What is Alex talking about?

Who is engaging with Alex

Alex Vacca 🧠🛠️'s Best Posts (last 30 days)

Ready to grow your LinkedIn presence?

taplio

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Alex Vacca 🧠🛠️

Performance Score.css-goub6s{font-size:var(--chakra-fontSizes-md);font-weight:500;color:var(--chakra-colors-gray-600);display:block;margin-top:var(--chakra-space-1);}Alex Vacca 🧠🛠️'s LinkedIn Performance

What is Alex talking about?

Who is engaging with Alex

Alex Vacca 🧠🛠️'s Best Posts .css-1emoo84{font-size:var(--chakra-fontSizes-md);font-weight:400;color:var(--chakra-colors-gray-600);}(last 30 days)

Ready to grow your LinkedIn presence?

Alex ️'s Linkedin Analytics

Performance ScoreAlex Vacca 🧠🛠️'s LinkedIn Performance

Alex Vacca 🧠🛠️'s Best Posts (last 30 days)