Charles Tenot

CEO @lemlist & lempire. I share what I learn as the CEO of a profitable SaaS growing to $40M to $100M+. Follow me to learn from the journey.

I love Tech, Sales, Marketing and Leadership. 

I share my learnings and thinking on LinkedIn, don't hesitate to follow & interact.

COO / General Manager

Growing lempire from 20M$ to 100M$ while generating 35%+ EBITDA

lempire products: lemlist, lemwarm, Taplio, Tweet Hunter, lemcal - more to come

I have no idea what my kids' life will look like with all this AI. 
But one thing I'm sure of: they need to understand that you can build things that other people use.

So I started vibe coding apps with them.

Last week, we built a cookie spot rating app to find the best spots in Paris.

This weekend, we made a Harry Potter sorting hat quiz (the "Sorting Hat" test).

Each one took about 30 minutes. 
And they're better than most apps you'd find online for the same thing.

I don't know what jobs will exist in 10 years. 
I don't know what skills will matter most.

But kids who grow up thinking "I can build this" will be in a better place than kids who just think "I can use this."

PS: sorry the test is in French

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CEO @ lemlist & lempire

I just watched our PM build a complete feature in 2 hours.

No dev involved.

He used Claude Code to create a working mockup, test all the edge cases, then generated the PRD from the code.

This is how our entire Product team works now.

Here's the process:
→ They download the full codebase locally.
→ They use Claude Code with custom skills we built for coding best practices.
→ They vibe code their features.
→ Build the interface.
→ Test the flows.
→ Catch edge cases nobody thought of.
→ Then they use AI to generate the PRD from the working prototype.

What they deliver to Engineering:
→ A fully functional mockup that devs can test
→ A detailed PRD with user stories already mapped out

This reduces conception cycle by over 50%.

Better product decisions because they can interact with the actual feature.
Fewer bugs because edge cases are caught early.
Less confusion between Product and Tech.

Most Product teams are still writing specs and hoping devs understand.
We're shipping working prototypes before the first planning meeting.

This is what all Product teams will do in the future.

Curious to hear from other Product teams: how are you using AI in your process?

Help needed: if you are looking for a Senior Finance profile, my life partner, Violaine, is available now.

After spending 3 years building a network of kindergarten for children with neuro developmental disorders, she is now available for something new.

Why I recommend her, even though I'm clearly biased:

→ Worked with top Private Equity firms globally
Always recommended afterwards

→ Hybrid experience with Senior Finance roles (M&A, Reporting) and 3 years of entrepreneurship where she ran notably finance for their 50 people business.
She can be both strategic & hands-on, she's not the "ivory tower" CFO.

 → Amazing analytical skills, she notably worked on complex problems in manufacturing, much more complex than SaaS.

 → Great business sense, easy-going, high work ethics

What she's looking for:
→ CFO or Finance Director-level
→ Interim or part-time
→ Open to full time with flexible work location
→ Start date from March 9th

Don't hesitate to like or comment to help me get more reach, thanks a lot 🙏

→ Phone: +33 6 69 25 57 26
→ Email: vsaintromas@gmail.com

As a CEO, I'm almost never a decision maker, yet very few salespeople understand this.

I still get cold called, emailed, 10x per day.

But even when the approach is solid, the best I can do is forward it to someone on my team. 

And most of the time, I won't even do this. 
Just because I don't want to make my team think I have evaluated the solution and I recommend it, and ultimately I'm not the one who makes decisions for teams.

Teams make their own decisions.

The CEO role is about creating alignment, building the best team, and challenge them when needed. 

But I'm not the one who will say "we should buy this."

If your outbound strategy is targeting CEOs, it probably works up to a certain point. 
But past 100 employees, it might not be the best approach, unless you are actually selling to CEOs, but I can count on my hand the number of things that I decide to buy myself.

The person who feels the pain, evaluates the tools, and makes the call is almost never the CEO.  It's the C-Level, the VP or Head Of. 

My advice: don't waste your time on the wrong target.
Map your buying process, find the person who feels the pain, evaluates the options, and owns the budget.
Then spend your time preparing a great outreach for them.

Really happy to see lemlist ranked #1 software in France on G2.

Not because of the ranking itself but because of what it took to get here.

The last few months have been the strongest innovation pace we've ever had. 

And all of it comes from listening to our 20,000+ customers every single day.

Sales is still one of the hardest jobs in most companies. 
No product has made it easy yet. Including ours.

But that's exactly why we keep building.
Let's keep going.

Big up to the team ❤️

I read Cognism "Top 21 GTM Tools" blog post.

Clay wasn't in it. 
lemlist wasn't in it. 
Apollo wasn't in it. 
Salesloft wasn't in it. 
Outreach wasn't in it.
Gong wasn't in it.

The biggest names in GTM. 

All missing from a "top GTM tools" list.

That's not an accident.

When a company publishes a "best tools" list, they're not trying to help you. 

They're running a content play.

The rules are simple: 
→ Include tools that don't compete with you 
→ Include tools that make you look good by association 
→ Never mention the ones that could actually take your customers

So here's the irony.

If you're ON a competitor's "top tools" list, it means they don't see you as a threat.

If you're NOT on it, it means you're the one they're worried about.

Next time you read a "best tools" listicle, don't look at who's on it.
Look at who's missing. ✌️

Yesterday we ran a webinar about how ElevenLabs runs Go-To-Market at 330M$ ARR. 

Over 1,500 people registered. If you missed it and want the recording just drop a comment and I'll DM it.

Here's my human summary of what Jonathan Chemouny shared after 1 year there.

About ElevenLabs GTM:

→ 330M ARR, +300M in 2 years. Just valued at 11B.
→ Only 400 people. Close to 1M ARR per employee.
→ GTM team is about 100 people.
→ Org is SDR + AE but they call everyone "GTM." 
Limited titles, limited hierarchy.
→ They maximize distributed ownership per country and region. 
They hire founder-like profiles who run their region like CEOs.
→ Top performers come from Finance, even Product backgrounds (👋 Oscar Lanzendorf)
→ Their sales close an average of 20X their OTE 
(source: Carles Reina podcast at 20VC, link in comment)
→ They grew outbound from 5% to 46% of revenue in one year. 
Outbound lets them better target ideal customers and segments.
→ Average deal size ranges from 30K/year to millions for Enterprise.
→ Outbound sales cycle is slightly longer than inbound but average deal size is higher.
→ They receive thousands of inbound leads daily and built an AI agent that answers prospects 24/7.
→ Everyone does outbound, even if you're hired as a potential GM-level.

What enables their incredible success:
→ Very high hiring bar. 4 interviews, harsh panels.
→ They hire for smarts, not experience. 
They don't want people who come with playbooks. 
They want people who can build playbooks.
→ They use AI a lot but will never run things 100% AI. 
Humans think of a creative way to approach an account and craft the message. AI handles things like voice notes or AI-generated video.
→ They meet prospects and customers in-person a lot. 
Jon believes humans should do things AI can't, like building real relationships.
→ LinkedIn and WhatsApp are their primary outbound channels. Quality before quantity.
→ They don't monitor activity metrics. 
They track the number of meetings done with prospects.

And of course, they have an insanely strong product.

I hope you find this valuable. 

If you have a company or GTM person we should invite next, don't hesitate to share.

---

Bonus: we created an agent that was fed on Jon's knowledge and our webinar prep document, I'll share the link with the recording.

cc thanks Rémi Kokabi, Domitille de Saint-Exupéry Rafael Ornia Mitchell

This guy has been in Sales for 20+ years. He helped build Intercom, Lattice, and now ElevenLabs. 

Next week, he'll be sharing his tactics to book meetings in 2026, and how ElevenLabs has been growing by +300M$ ARR in 2 years.

Here are few things I can tell you as a teaser:

→ How they increased the share of outbound from 5% to 30% in 12 months, and how their around 100 reps use lemlist

→ ElevenLabs is hiring "GTM" people. No title, no hierarchy, background mostly from VC or former founders

→ They give a lot of ownership to their sales team, who act almost as local CEOs working in pairs with Product to adapt to local markets

→ They mostly rely on full-cycle Sales handling both Inbound & Outbound. 
He'll explain why they decided not to specialize

→ Jon still does a lot of outbound himself, he built a few very creative tactics notably using AI in his messages. He will share a full breakdown of those that work best

This is certainly the most exciting Webinar we've run in months for anyone on a Sales team, so don't tell me you can't find 45 mins to get all these learnings. 

Link in the comments

And big thanks Jonathan Chemouny for unpacking so much value 🙏
cc Stan Massueras 💙

Intercom

Lattice

ElevenLabs

lemlist

GTM Europe at ElevenLabs

GTM Europe @ElevenLabs

ElevenLabs just closed a $500M round at an $11B valuation. 

They went from $0 to $330M ARR in 3 years (this number will be outdated tomorrow).

Next week, Jonathan, GTM @ElevenLabs is opening the playbook with me.

Here's what makes their approach different.

→ While most companies shifted to async everything, Jonathan gives his SDRs a travel budget to meet prospects in person.

→ While most companies hire junior SDRs to book meetings, he hires ex-AEs to do value selling.

→ While most companies stick to email and LinkedIn, his team uses WhatsApp and AI voice notes to stand out.

→ And while most companies run on gut feeling, Jonathan has an obsessive A/B testing culture where every conviction is forged on the field.

This session is going to be a gold mine on how to build efficient GTM motions in 2026.  
How often can you learn from a real systems that took a company from zero to $330M ARR, and scaled outbound from 5% to 30% of closed deals?

We'll break down:
→ How SDRs evolved from meeting bookers to revenue drivers
→ The inbound vs outbound split and why it matters
→ The key metrics Jonathan tracks daily and how he coaches his team
→ How they use their own product to increase meeting rates
→ Why context beats static lists every time
→ and of course, how they are using lemlist 😈

This is for growth leaders, sales ops, SDR managers, and founders who want to scale revenue the right way.

A 45-minute interactive session with the opportunity to ask live questions directly.
Plus the actual templates and playbooks.

---
I'm excited about this one because it's rare to get this level of access to a company moving this fast.

February 18th.
9 AM PT / 6 AM CET

Link to register in comments.

You can beat 99% of companies by doing a few things well:

→ Set one clear vision and don't change it every 3 months 
→ Say "no" to everything that doesn't contribute to the strategy 
→ Remove low performers after weeks, not years 
→ Use your own product 
→ Talk to customers 
→ Keep reporting light 
→ Lead every meeting from the customer's standpoint

It looks simple written down like this.

But most companies don't have an execution problem. 
They just keep adding layers, processes, and distractions on top of it.

The companies that win aren't doing anything secret. 
They're just not getting in their own way.

I asked someone at ElevenLabs what makes their culture different. 
Their answer helped me understand how they went from 30M to 330M ARR in less than 2 years.

Yanek Brinkmann, one of their GTM team, told me:

"It's the closest you can get to doing your own business while still being in a job."

I've always believed that someone who works like they're running their own business has 10X more impact than someone who's just doing their job.

The difference is ownership. Real accountability. 

The kind you only get from people who actually care.

You'll get more from someone less experienced with insane grit than from someone senior who's just collecting a paycheck.

ElevenLabs understood this. 

And they still operate like that at 400 people.

Imagine 100 GTM people with a founder mindset.
→ Clear ownership on their region. 
→ Working directly with Product to adapt when needed. 
→ Flat org. No titles.

Their reps close 20X their OTE. The industry average struggles to hit 5X.

But this only works if you actually distribute ownership and responsibility. 
Not just talk about it.

I'm convinced this is how world-class companies are built now. 
And they will crush big groups with pyramidal organizations.

➡️ Later today, we're sharing more about ElevenLabs's playbook with Jonathan Chemouny. 

Already 1,350 people registered. You can still take your spot, it's free value.
No recording. We want people live and contributing.

Link in comment.

I have data-backed proof that spray & pray doesn't work.

It comes from 350M+ emails and 4.5M LinkedIn messages sent with lemlist over the past months.

This chart represents our 20,000+ customers.

From pre-revenue founders to companies with 300M$+ in ARR and 100+ sales reps.

How to read it:
→ Horizontal axis: our 10 deciles of customers, from the 10% with the worst results to the 10% with the best
→ Each bar: the volume of messages sent
→ Vertical axis (line): the average reply rate

What we see:
There's a clear negative correlation between volume and reply rate.
The fewer messages teams send, the higher their reply rate.

In detail:
→ The first group shows that the bottom 10% aren't sending enough messages, or just lack adoption. They'll probably churn unless they use lemcoach.
→ Then across the other 9 deciles, each one has lower volume and a higher reply rate than the previous one.

If this doesn't show you that it's better to do less but better, I don't know what will.

Spoiler: it's not the spray & pray "AI SDR Agent" that will solve this.

Slack, Figma, Notion, Dropbox, Datadog. They all started PLG. 
None of them stayed PLG. Here's why:

PLG is great for small customers. 

Low CAC, high scalability, self-serve magic. 

But as your product improves, you start attracting bigger companies. 
And enterprise buyers don't convert on PLG products. 
They need help. They need sales.

This is where PLG + Sales-Assisted comes in. 

And I'm convinced it's the ultimate state for SaaS:
→ PLG for small customers. Low CAC, fully self-serve, scales beautifully.
→ Sales-assisted for larger customers. You can segment by geo, industry, company size and organize your team around it.

This combination maximizes conversion across every customer segment.

Since we added a sales motion at lemlist, our growth has never been stronger. 

We grew +70% last year. PLG + Sales-Assisted together.

But here's the hard part:

In PLG, everything is streamlined: credit card payment, automated provisioning and payment retries.

But when sales gets involved, you start dealing with:
→ Custom quotes
→ Custom terms and legal discussions
→ Discounts and approval workflows
→ Custom billing terms and payment methods

You go from a scalable model to a non-scalable model overnight. 

And that's where most companies struggle.

The good news is that with the right tech, you can now build scalable systems even for sales-assisted motions.

On March 11, I'm co-hosting an event in Paris with Lucas Bédout (CEO at Hyperline) and the Business Operations Network to dig into exactly this. 

How to build a hybrid revenue engine that scales.

Free for BON members. 

Link to register in comments.

cc Victoria Dalleau 🙏

Nothing prevents you from sending 10 follow-ups. 
And yes, you'll get more replies.  But it's doing invisible harm to your outreach.

If you look at reply rates by number of follow-ups, the pattern is clear. 
Each follow-up increases your chance of getting a reply. Even a little.

But the incremental gain drops fast. 
After 4 follow-ups, you're barely moving the needle.

And here's what most people miss.

Every extra follow-up increases the chance your leads mark you as spam. 

Not by replying. 
By hitting that little spam button because they're annoyed.

When that happens, it hits your domain and email reputation. 
Your emails start landing in spam more often. 
Not just for that lead. For everyone.

This is the classic trap where short-term gains quietly destroy long-term results.

More follow-ups today = Fewer emails delivered tomorrow.

I have been a CRO with 150+ people and I can tell you that sales coaching is broken because of 3 things:

1/ Managers are never able to see more than 10% of calls from their reps.

2/ Managers are biased, like any human, and I have seen decent performers be treated as low performers because of a poor fit with their manager.

3/ Managers have different methods and preferences, which creates lack of consistency across sales orgs about what good looks like.

And this creates massive frustration.

Reps lose trust in leadership.

Leaders make bad decisions about who to promote or fire.

Good people leave.

And this leads to revenue loss and drop in talent density.

But today, AI can help fixing this.

At lemlist, we now record and transcript all our calls.

Every single one gets evaluated against the same criteria.

We use the SPICED methodology, so AI automatically evaluates all qualification criteria. 

All with Claap.

Things like: Did they surface the impact of the problem? Did they qualify budget properly? Did they ask about decision makers?

Every rep gets a score for each call across all these criteria, linked to actual moments in their calls they can review.

This allows us to significantly improve fairness and consistency.

Feedback is now trusted way more than before.

Because it's based on 100% of their work, not a random sample.

And managers can finally coach with data instead of gut feeling.

AI isn't replacing sales managers. It's making them way more effective.

Sales training just got an upgrade.

Claap

6 examples why short-term growth almost always comes at the expense of long-term growth:

→ Hiring the least worst candidate because you need someone now vs. waiting for the best even if it takes 6 more months. 
Impact compounds. An A-player generates 100X more value than a B-player.

→ Sending 10 follow-ups to squeeze out more replies vs. stopping at 4. 
Each extra follow-up barely moves the needle but increases spam reports. 
Your domain reputation takes the hit and deliverability drops for everyone.

→ Blasting your entire TAM in one month to hit pipeline targets vs. working accounts in waves. 
You get a short spike, then you've burned your brand with every account.

→ Cutting product investment to boost short-term margins or hire more Sales. Customers don't leave immediately. 
They leave 12 months later when a competitor ships what you didn't.

→ Discounting to close a deal before quarter end vs. holding your price. 
You hit this quarter's number, but you've trained the buyer to expect discounts. Next renewal, they push harder. 
They talk to their friends. 
And your average deal size erodes across the whole pipeline.

→ Not promoting a great rep with manager potential because they're bringing in short-term revenue. 
They'll leave 6 months later. And you'll end up hiring someone less good.

Every one of these looks like the right call in the moment. The cost just shows up later.

That said, there are moments where you need to move fast and accept some debt. 

The interesting part is knowing when you're making a conscious trade-off vs. when you're just not seeing the long-term cost.

As a CEO, when people agree with me too easily, I don't take it as a compliment. I take it as something to question.

Things I don't expect from people in the team:

→ Telling I'm right
→ Liking my LinkedIn posts
→ Being overly positive on my ideas and initiatives
→ Nodding in meetings
→ Sugarcoating bad news
→ Using my notes / inputs as is without re-working them
... and certainly not telling me I'm smart, or giving any compliment

Here's what I actually value:
→ Saying what you think
→ Thinking on your own before defaulting to the group
→ Coming to me when you disagree or don't understand, especially when it's uncomfortable
→ Bringing problems early and as they are
→ Having a point of view and defending it

I recently listened to a podcast from an experienced CEO who said his biggest mistake was surrounding himself with people who gave him compliments but weren't truly competent at their jobs.

The best people I've worked with were never those who constantly agreed with me, they were the one who made me change my mind.

This week, a bot fixed its first production bug at lemlist. 

Here's what happened:

A user double-clicked a delete button. That sent two requests at the same time.  The API returned a 409 conflict error.

Our bot detected it in the logs, investigated the root cause, traced the code path, wrote the fix, and submitted a pull request with the right reviewers assigned.

Total human involvement: reviewing and merging the PR.

In the meantime, we also had 3 features shipped to production by... Product Managers.

A year ago, we never thought this would happen so fast.

I was talking to a friend, a developer with 20+ years of experience.
He told me his workflow has completely changed.

Before, he spent most of his time in "flow." Going from one coding step to the next.
Now, he spends more time thinking about the overall architecture. 
Then he works with AI to develop the different parts. Then he reviews the code. Makes sure the logic is right.


And yet, we're still hiring developers.

Because our bet is that the job isn't disappearing. It's shifting. 
And good developers will always be a scarce resource required to build great products.

You could argue AI will improve so fast it won't need developers at all.

My gut says you'll always need people who understand systems deeply enough to work with AI.

But we'll see. What's your take?

Every Tech company board is the same: "We need to go Upmarket"

The reason is usually financial. 

Going upmarket increases "Enterprise Value", because is usually means higher retention.
And of course, investors want to increase enterprise value.

But going upmarket at the expense of losing your historical market isn't always the right call.

You might lower churn. 

But you can lose growth and end up struggling.

This is why at lemlist, we spent over 9 months debating if we should go upmarket or not. 

Because serving small customers was always important to us for many reasons:
→ They trusted us first
→ More customers = bigger brand
→ Small companies can become big ones with time
→ Serving emerging businesses drives real purpose 
→ Startups usually the innovators, they push us to keep improving the product

We finally decided to build lemlist for sales teams and go upmarket, but we decided to do it slowly, not as a pivot, but as a continuous progress of the platform. 

And it paid out because today we have customers from 1 to 150 users.
We have grown by +70% in 2025 while being profitable, and across all segments.

After seeing from the inside 4 different companies go upmarket, I wanted to share my learnings:
Wednesday with Lucas Bédout from Hyperline, we are organising a meet-up in Paris.

Here's a preview of what we'll talk about:
→ Why it took us 9 months to decide between going upmarket or continuing to build a suite for founders 
→ The stages we went through, mistakes we made, and what we did right 
→ Key people we hired (hey Yann Guilleux) 
→ How we run inbound & outbound, and how we use our own product 
→ How we grew the sales team from 1 person (hey Tal Baker-Phillips) to 30+, across 3 areas and 2 roles (AE & Inside Sales) 
→ How we signed our first 100K+customers, coming from 1K$ARPA 3 years befre
→ How we monitor productivity & measure performance 
→ What we built in the product to maximize conversion & score leads 
→ How we organized RevOps & Tools 
→ Our Sales Quota, Payback and how we maintain <3 months payback while adding Sales headcount

Bonus: how we increased ARPA by +30% in one month by changing the wording of one question in our product onboarding 🔥 

Free event. Paris. March 11.
Link in comments.

cc: thanks Antoine Leprince for the organization 🙏

Sending a LinkedIn message in a sequence increases email reply rate by 38%. 
And no, that's not a typo. I'm talking about email replies. 

LinkedIn reply rates are averaging 15%, vs. 1-3% for emails (up to 15X higher)

But here's what we found across 35M leads:

When you add LinkedIn steps to an email sequence, your emails start getting more replies too.

The prospect sees your name on LinkedIn. 
Maybe they check your profile.
Maybe they read your message.

Then your email lands, and you're not a stranger anymore.

That familiarity is worth +38% on your email reply rate.
This data is coming from 35M leads that we analyzed at lemlist.

This is pure facts that multi-channel is the right way to do outbound today, and why we build lemlist to include as many channels as possible.

---

Michel Lieben 🧠

Founder / CEO @ ColdIQ | Scale Outbound with AI & Tech 👉 coldiq.com

I’m (Michel) the Founder & CEO at ColdIQ, a sales prospecting agency (+ we compare the latest sales tech, too!).

We worked with 100+ B2B organizations (including SaaS & Agencies!) and are using Clay, Prospeo, FullEnrich, Instantly, Lemlist, Ocean.io - alongside other great sales tools - to run outbound campaigns that flood 🌊 our (and our clients’) inboxes with interested prospects.


We can help you:

• If you’re a B2B business leader who doesn’t have the time to handle your prospecting engine or to hire and manage salespeople… You can outsource your lead gen to us, and we’ll transparently show you the exact way we run your campaigns. (We’ll provide SOPs, too… if it works so well that you want to build your in-house team).


• If you’re a sales leader or an outbound agency owner: We’ll help you set up the exact systems & tools we use to run automated ‘trigger-based’ campaigns that convert like crazy. 


• And… if you simply want to improve your B2B sales automation skills or learn to run these campaigns yourself, we’ll teach you by building a campaign from scratch together with you —from ‘idea’ to ‘running campaign’ (we’ve done it more than 50 times already, and the rumour says people ❤️ed it).


We've launched hundreds of campaigns, so you don't have to.


Thus - if you: 
- are a B2B service/solution provider making > $50k/month
- provide solutions with Lifetime Value > $10k
- want to shortcut your outbound success


We can help.

Send a DM, and I'll share more details.

Alternatively, reach out to michel[at]coldiq.com 
or via the website 👉 coldiq.com 


__________



And if you're looking to build your top-of-funnel tool stack... 
Check our curated lists of the best outbound tools here 👇

👉 coldiq.com/tools 👈
👉 coldiq.com/ai-sales-tools 👈

Performance-based B2B lead generation 💥 | coldiq.com
→ We help you scale your prospecting activities by implementing outbound sales systems in your business. We take care of sourcing leads, researching your ICP, crafting the sales messages, automating sending and ensuring the high deliverability of messages. We let you focus on what brings money into the business: closing deals.

Can you run your entire GTM with Claude Code?

We're answering that tomorrow.

We use Claude Code for:

Paid media.
Outbound.
Reporting.
CRM ops.

All through AI agents we built in-house and deployed across 70+ B2B clients inside our $7M ARR agency.

On February 26th, we're opening our terminals and showing everything. 
Live.

What we'll cover:

Outbound
→ ICP scoring & signal-based lead prioritization on autopilot
→ cold email sequences built from real performance data
→ AI reply handling in under 2 minutes

ABM/Ads
→ automated campaign creation, reporting & optimization
→ AI agents managing LinkedIn, Meta & Google ads
→ paid media run entirely from the terminal

RevOps
→ campaign diagnostics that took hours, done in 60 seconds
→ live dashboards pulling every data source into one view
→ bidirectional CRM sync: Attio, Lemlist & Instantly

What you'll leave with:

→ how to build your first Claude Code GTM agent from scratch
→ the architecture behind 32 skills, 12 agents & 2,108 files
→ which GTM use cases actually deliver ROI today

We'll demo the agents live.
Then break down the architecture so you can build your own.

Hosted by Ivan Falco (Head of Growth) & Kenny Damian (Head of GTM) at ColdIQ.

February 26th - 1:30 PM EST

In case you missed the event....

Here's the link to the webinar recording - https://lnkd.in/eqNfrT7b

Founder & CEO at ColdIQ | Tomorrow’s GTM Systems, Built for you 👉 coldiq.com

The anatomy of a $7M ARR lead gen agency:

From Marketing → Sales → Client Delivery ↓

Every step. Every tool. Every person behind it: 

1️⃣ Marketing Engine (40,000+ visits/mo)

A. LinkedIn (~10,000 visits)

20+ people in our team (~300K followers) post a combined 150+ times around prospecting, AI & GTM.

Ada, Pilar & Maria Luisa design our infographics.

Useful tech: Taplio, Scripe.


B. SEO (~12,000 visits)

Yevhen runs our programmatic SEO.

We publish:
- Standard blog articles
- Programmatic pages via AirOps
- Free mini-tools built with Claude Code (made by Sacha)

Useful tech: AirOps, Ahrefs, Claude Code, Webflow


C. Paid Ads (~4,000 visits)

Ivan runs our paid campaigns across LinkedIn, Meta & Google.

~$10K/mo to experiment across channels.

Useful tech: Airpost, Fibbler, Usermaven


D. Cold Outreach (~3,000 visits)

Kenny handles our outbound campaigns:

We run several plays, including:
- Value-based lead magnet campaigns
- Inbound-led outbound
- Lookalikes companies

All built on targeted lists of < 5,000 hyper-enriched prospects. 

Useful tech: Clay, Instantly.ai, lemlist, Prospeo.io, FullEnrich, Apify, Wiza, Common Room, PredictLeads


E. Others (~11,000 visits)

Monika runs our beehiiv newsletter.
Alex creates YT + IG videos.
Harry powers our webinars.


2️⃣ Lead Capture

To convert traffic, we run:

- Midbound, Vector 👻 to re-engage anonymous visitors.
- Email marketing via Customer.io.
- Lead magnet e-books pop-ups.
- Mini-tools to capture emails.

All data flows through n8n → scored via Clay + OpenAI + PredictLeads.


3️⃣ Sales Engine

Jan & Dujam close our deals.

These 2 are machines, and there's a healthy (or not 😅) competition that makes them both close much more.

Most deals are sales-led. 
2-3 Google Meet video-calls. 
$5- $10K/mo packages.

The flow =

- Precall: case studies, VSL, free video content → prospects qualified via Default.
- Discovery call: AE connects with prospect, sends connection request.
- Enrichment: lead research via Clay (funding, headcount, tech stack, tenure, reports).
- Proposal → (follow-up) → Closed Won

Useful tech: Attio (CRM), Attention (AI meeting notes), Hyperline (CPQ), Qwilr (proposals), Stripe (payments).


4️⃣ Client Delivery

Soheil leads our Service Delivery team, which sometimes onboards over 30 new clients in a quarter.

To stay on top of it, we:

- Automated onboarding processes via n8n.
- Synced GSuite ↔ Supabase ↔ Stripe ↔ Slack.
- Automated admin tasks (= Slack invites, sending onboarding links, secondary domains) 

…so our GTM Engineers only focus on what adds value to clients (custom ICP matrix buildout, creative campaign ideas, copy…)

Useful tech: Airtable, n8n, Slack, Google Suite, Supabase


Didnd't get enough space to go as deep as I wanted on each component… but the infographic below breaks it down visually.

Which part of this engine would you like more details on?

P.S: Wanna grow your agency? We have a coaching program that teaches exactly that 👇

Imagine only cold emailing leads who WANT to buy from you…

The closest way to do so? Leveraging buying signals:

The idea is that these signals help you:
- find relevant reasons to initiate contact
- re-activate existing prospects at the perfect moment
- surface new challenges to address in your messaging

… and much more.

There are several categories of signals:

1️⃣ First-Party Signals

↳ = Intent data gathered from your own business ecosystem.

These are prospects who already know you, actively taking steps like:

- utilizing your product
- browsing your website
- subscribing to your email list
- interacting with your brand on social platforms

Platforms that help you capture these signals include:

1. LinkedIn Signals: Clay, Expandi.io, Trigify.io, Jungler

2. Website Visitors: Instantly.ai, Clay, Midbound, Vector 👻

3. Product Usage: Common Room, Mixpanel, Pocus, PostHog

4. Call Transcripts: Attention, Fireflies, Claap

5. Gated Content: Distribute, Gamma


2️⃣ Second-Party Signals

↳ = Intent data sourced from your ecosystem, shared by partners.

Generally, prospects who have engaged with:

- your brand on a partner platform (e.g: checking out your listing on G2)
- your company, while employed at a different organization
- a partner of yours with an overlapping customer base

Examples include:

6. Champion Tracking: Clay, Common Room, Unify, UserGems 

7. Affinity Signals: Crossbeam, Reveal, The Swarm 🔆, PartnerStack

8. Ad Engagement: Fibbler, ZenABM, Factors AI

9. Software Marketplaces: G2, Capterra, ColdIQ


3️⃣ Third-Party Signals

↳ = Intent data sourced from external providers.

Thus, public signals indicating companies might benefit from your solution.

Examples include:

10. Technographic Data: Clay, PredictLeads, HG Insights, BuiltWith, Similarweb

11. Funding Announcements: PredictLeads, lemlist, Clay, Crunchbase, Owler, PitchBook, 

12. Web Data Agent: Claygent, Parallel Web Systems, Tavily, Common Room, Unify, Linkup, Perplexity, Manus AI

13. Job Openings: Common Room, PredictLeads, Clay, LoneScale, Mantiks, TheirStack, Lemlist

14. Custom Scraping: Apify, Firecrawl, Claygent, Instant Data Scraper

15. News Monitoring: PredictLeads, Google News, Exa

16. Ads Activity: Apify, Adyntel, Ahrefs

17. Firmographic Data: Prospeo, Wiza, Exa, DiscoLike

18. Lookalike Search: PredictLeads, DiscoLike


P.S: What’s your preferred tool for monitoring buying signals?

We recently crossed $7M ARR.

Here’s every tool we use to run our business:

1️⃣ Content Engine

LinkedIn generates 100+ leads for us every month.

This includes my account: Michel Lieben [67,000+ followers] 
+ other team members [300,000+ followers combined]. 

I use:

- Taplio for content inspiration & ideation.
- Notion for content planning & calendar.
- Scripe to draw inspiration from specific creators.

I crossed 2,200 YouTube subscribers from 15 videos. 

I use:

- Tella for async video production.
- vidIQ for content discovery & ideation.

We ship 2 articles/week and attract 100,000+ visitors quarterly.

30% now comes from SEO, thanks to free mini-tools we built for lead gen, & programmatic pages we created at scale. 

We use:

- Claude Code to build these out.
- AirOps for programmatic SEO.
- Ahrefs for keyword research.

We have ~10,000 active newsletter subscribers with 40%+ open rates. 

We use beehiiv to send our weekly issues.


2️⃣ Outbound System

We deliver Outbound & GTM services to 80+ B2B clients.

Our entire outbound engine runs on Clay for:

→ Enrichment
→ Personalization
→ Prospect research
→ Workflow automation
→ Signal-based targeting

We also use Claude Code for list building, email copywriting, and automating campaign creation.

Plus specialised tools for:

- AI Agents: Relevance AI, n8n.
- Outreach: Instantly.ai, lemlist, Expandi.
- Lead Sources: Prospeo, Apify, Exa, Openmart.
- Contact Data: Wiza, FullEnrich, Prospeo, LeadMagic.
- Intent + Retargeting: PredictLeads, Common Room, Vector 👻, Fibbler, Midbound


3️⃣ Operations Stack

Our team includes 35 FTEs & ~12 Fractional Freelancers.

We use:

- For internal automations: n8n, Claude Code

- For internal database & documentation: Airtable, Notion, Supabase

- For team communication: Slack, Google Meet, Norrsken Barcelona (office by the sea 🌊)


4️⃣ Inbound Funnel

We book ~100 qualified B2B meetings monthly. 

We use:

- Default (lead routing)
- GA4 + Wistia (analytics + VSL)
- Usermaven (analytics & attribution)
- Webflow & Vercel (website hosting)

For re-engagement:

- Customer.io (email marketing)
- Kondo: Superhuman for LinkedIn DMs (LinkedIn inbox management)


5️⃣ Sales Stack

We closed +$1,000,000 in new ARR last month. We use:

- Attio (CRM)
- Qwilr (proposals)
- Attention (AI meeting notes)


6️⃣ Billing & Finance

We’re integrating Hyperline for billing our productized offerings. It handles quoting, invoicing, and payment collection in one.

On top of that, we use:

- Ramp (expense & treasury management)
- Stripe, Revolut, Mercury (billing + banking)


P.S: What’s one tool we should absolutely try?

GTM Engineer is the hottest role in tech sales. We ramped up 100+.

Today, we’re launching a marketplace to help you hire them.

Now there's a reason why this role has exploded over the last 2 years:

A single strategic GTM Engineer can replace 5+ extra hires by owning the full data lifecycle:

- Data Aggregation: pulling signals from CRMs, intent data, databases, and 5+ sources
- Data Enrichment: filtering, scoring, and qualifying leads with AI agents and waterfall enrichments
- Data Activation: turning all of it into pipeline through outbound, RevOps, content & ads

The best ones master tools like: Clay, Apify, Claude Code, Relevance AI, lemlist, Instantly.ai, Expandi, PredictLeads, Common Room, Attio, AirOps... stitching them together into workflows that outperform entire teams.

The problem? Finding these people is still surprisingly hard.

Companies come to us every week looking to hire the kind of GTM talent we’ve built at ColdIQ. 

But they don’t know where to start. 

Meanwhile, talented operators are looking for their next opportunity in a space that’s evolving fast.

So we built something to fix that: 
→ A dedicated talent marketplace for GTM roles.

This isn’t a typical hiring agency. 

Our marketplace is integrated directly with ColdIQ, which means we’re already plugged into a network of world-class GTM operators. 

We know who’s out there, what they’re good at, and what they’re looking for.

Whether you’re hiring or exploring your next role... the process starts the same way.

P.S: Interested in hiring or getting hired? 
Link to the form is in the comments 👇

I tried way too many AI Sales tools in 2025

Here are the categories I’m closely monitoring in 2026:

1/ Workflow Builders

Why?

↳ They allow you to create advanced, multi-step, automated prospecting workflows.

Example use-case: Running a signal-based Clay campaign that ranks leads, segments them into several tiers, adds an AI-personalized first line… and then pushes contacts to your preferred sequencer. 

Examples include:

→ n8n
→ Clay
→ Outbond
→ Relevance AI
→ Enginy (formerly Genesy)


2/ MCPs

Why?

↳ They allow AI agents to execute actions by connecting to your tools. Without you needing to manually open them.

Example use-case: Connecting Claude MCP to Google Calendar so that it…

1. Checks how many sales calls you have today
2. Researches each prospect
3. Provides relevant talking points for the qualified ones…
4. Cancels meetings with unqualified leads.

All that, without opening your calendar app.

You can prompt via tools such as:
→ Cursor
→ Claude Code

And connect to your apps using:
→ Docker, Inc
→ Pipedream
→ Composio


3/ AI Coding Tools

Why?

↳ They enable you to write code in plain English. These can be leveraged to build complex workflows.

Example use-case: Build a phone number finder to collect email addresses.

My personal favourites include:
→ Cursor
→ Claude Code
→ OpenAI Codex

Other platforms include:
→ Warp
→ Cline
→ Replit
→ Lovable
→ Windsurf


4/ All-in-One Sales Platforms

Why?

↳ They consolidate all essential cold outreach capabilities into one software.

Example use-case: Warming up domains, assembling a lead list, monitoring relevant signals, enriching contact data & automating outreach within a single platform. 

Examples include:

→ Instantly.ai
→ Expandi
→ Artisan
→ lemlist


5/ Sourcing Agents

Why?

↳ They gather data autonomously, given a set of prompts.

Example use-case: Sourcing a list of Sales Leaders, based in SF, in VC-based startups that have > 5X’d revenue 2 years in a row within the last 3 years… by simply telling Exa, in plain English, that this is the list you’re looking to build.

Examples:

→ Parallel Web Systems
→ Relevance AI
→ Claygent
→ Linkup
→ Tavily
→ Apify
→ Exa


6/ Conversation Intelligence

Why?

↳ They record meetings & surface relevant insights from your business conversations.

Example use-case: Reviewing your latest 100 sales calls via Attention’s agent to identify the most frequent objections your sales team receives from prospects.

Examples:

→ Momentum.io
→ Fireflies.ai
→ Attention
→ Claap


7/ Signal Platforms

Why?

↳ They track intent signals to help you uncover prospects in buying mode.

Example use-case: Monitoring previous product buyers (champions) in Common Room, to pitch your solution when they move to a new company (that doesn’t use your product yet!)

Examples:

→ Common Room
→ PredictLeads
→ TheirStack
→ Clay

P.S: What AI Sales software category are you betting on in 2026?

AI Sales Categories (2026)

I asked 62 GTM leaders running $1M+ orgs what tools they use.

One tool showed up in 71% of stacks:

MOST MENTIONED:

- Clay (71%)
- n8n (48%)
- HubSpot (39%)
- Instantly.ai(35%)
- HeyReach.io (35%)
- Apollo (35%)
- LinkedIn (32%)
- Attio (32%)
- Prospeo (29%)
- Lovable (29%)


FEATURED STACKS:

Nikola Sokolov (CEO, influencers.club) - 54 tools
↳ Clay, Instantly, HeyReach, n8n, HubSpot +49

Charles Tenot (CEO, lemlist) - 40 tools
↳ Clay, n8n, Apollo, Ahrefs, HubSpot +35

Jaspar Carmichael-Jack (CEO, Artisan) - 25 tools
↳ HubSpot, Gong, Lovable, Ahrefs, Artisan +20

Benjamin Douablin (CEO, FullEnrich) - 19 tools
↳ HubSpot, Instantly, HeyReach, n8n, FullEnrich +14

Eoin Clancy (Head of Growth, AirOps) - 17 tools
↳ AirOps, Lemlist, Clay, Common Room, Attention +12

Kai Brandt (CEO, Enginy (formerly Genesy)) - 17 tools
↳ HubSpot, Claude, Ahrefs, Lovable, Loom +12

Pierre Herubel (Co-Founder, Content Path) - 15 tools
↳ Clay, Claude, Attio, Lemlist, Webflow +10

Roq Xever (Founder, PredictLeads) - 15 tools
↳ HubSpot, Clay, Claude, Cursor, Lusha +10

+49 more stacks broken down on our "tech stacks" page.
(Link in the comments)

P.S: Any tools surprise you?

44 data sources to find prospects in any niche...

...and 7 different ways to source this data:


1. Leverage sourcing agents

Use platforms like Airtop, Clay, Exa, Perplexity, Manus AI or Relevance AI and describe in plain/natural language what you're looking for.

Their agents handle the rest.


2. Use 'standard' B2B databases

Use filters such as “job title”, “location”, “employee count”, “headcount growth” within standard databases like Prospeo, Wiza, Apollo, LinkedIn & DiscoLike 

…or using niche databases like Openmart, influencers.club… 

to find your target data.


3. Target by technology

Use APIs like PredictLeads, or platforms like TheirStack, BuiltWith & BuyerCaddy to find companies using a specific technology.

Their use of this tech should suggest they’re a great lead for you.


4. Target companies showing buying intent for your offering category.

Monitor companies’ activity, including:
- Job openings
- Funding events
- Social engagement
- Tech/software changes

Via tools like Clay, PredictLeads, Common Room, and Trigify.io to infer potential buying willingness. 


5. Custom data extraction

Extract data from popular websites, specific pages, or any site using Apify actors or tools like Instant Data Scraper, Firecrawl, ZenRows & Airtop.


Once you sourced your target people & companies, you’ll want to:

→ Find their email addresses & phone numbers with point solutions (e.g: Prospeo, Wiza, LeadMagic) or…

→ Find their contact data via data waterfalls (e.g: FullEnrich, Clay, Enginy (formerly Genesy), Outbond)

More details included in the carousel below ↓

P.S: Who's your go-to to source accurate B2B data?

44 Data Sources

27 APIs to turn Claude Code into a lead generation machine:

1. PredictLeads

Example use case: use PredictLeads' API within Claude Code to monitor signals on target accounts such as hiring surges, funding rounds & tech installs.

2. LeadsFactory

Use case: find people by job title by providing a LinkedIn company URL as an input.

3. Exa

Use case: Describe your ICP in plain English and let Claude Code search the web semantically to find matching companies.

4. Jina AI

Use case: feed Claude Code any URL via Jina's API to convert the page into clean readable text (so that you can then extract prospect info, pricing data or company intel & mor)e.

5. Wiza

Use case: feed Claude a list of leads and Wiza's API finds verified emails and phone numbers.

6. Prospeo

Use case: build lead lists, find emails & find phone numbers via Prospeo's API

7. FullEnrich

Use case: run Claude Code's enrichment step through 15+ data providers in a waterfall to find verified emails and phones that single-source tools miss

8. Apify

Use case: let Claude Code run pre-built scrapers for social media profiles, company pages, Google Maps & other platforms.

9. Trigger.dev

Use case: let Claude Code kick off long-running GTM workflows (batch enrichment, multi-step sequences, CSV processing) that run reliably

10. lemlist

Use case: connect Claude Code to your multichannel outreach tool to automate outbound campaign creation.

11. Instantly.ai

Use case: let Claude Code push enriched leads into cold email campaigns.

12. Google Analytics

Use case: ask Claude Code to pull your website traffic, conversions and channel data to gather insights on your GTM activities.

13. DataForSEO

Use case: let Claude Code pull SERP rankings, keyword volumes and competitor data to fuel your SEO content strategy without touching a dashboard

14. Logo.dev

Use case: let Claude Code fetch any company's logo by domain to fill your sales decks or branded visuals.

15. fal

Use case: ask Claude Code to generate ad creatives, social visuals or video assets on demand using 600+ AI models through a single API call


...ran out of space here, but there are 12 more in the slides 👇


P.S: What's your favourite GTM API for Claude Code?

Top 27 GTM APIs for Claude Code

Snowflake hit $4,000,000 ARR with 60% of its pipeline generated by SDRs.

Here’s their strategy (and how you can reproduce it):

First, you need to ensure your departments collaborate towards the same objective.

For Snowflake: Marketing, SDRs & Sales sit under ONE SINGLE team.

They ran the experiment for specific regions.

- The ones that did it had up to 46% meeting rates.
- The ones that didn’t do this had 17% meeting rates.

1️⃣ Alignment

Marketing & Sales operate hand in hand.

Marketing collects insights to be leveraged by the sales team.
The sales team executes on them within 2 weeks.

Seems obvious, but truth is most companies have these 2 teams working in silos.


2️⃣ Intelligence

Snowflake leverage signals a lot.
Their rationale is to get in front of prospects as soon as they’re exploring their use cases.

They do that via:

- Third-party intent signals (job changes, funding rounds, web searches)

And further down the funnel via:
- First-party intent signals (product usage, email clicks, website visits).

They rely on tools such as Bombora to detect accounts showing interest in the background. I’d suggest leveraging Clay, PredictLeads or Common Room for this.

Accounts flagged as “high intent” convert 4x better than standard accounts in the CRM.


3️⃣ Activation

When accounts display enough buying intent, Snowflake’s teams deploy their “1-2 punch” play.

That is:

Weeks 1 & 2: ABM team nurtures target accounts with personalised campaigns (ads + emails + dedicated landing pages)

Week 3: SDRs jump in with outbound.

By the time an SDR cold calls a prospect… they’re already not cold anymore.

Result = 36% meeting rates on pre-warmed accounts (vs. 10% on cold)

4️⃣ Engagement

They reach prospects everywhere they are.

→ Calls
→ Cold Emails
→ LinkedIn DMs
→ Custom microsites

True multichannel orchestration.

(I’d suggest leveraging a platform like lemlist to replicate this omnichannel engagement)

5️⃣ Optimisation

They continuously iterate on what works and what doesn’t.

Performance metrics get shared between the teams in bi-weekly alignment meetings.

ABM, SDRs, & AEs are all informed of what works in terms of messaging & targeting.

But they don’t try to attribute who’s responsible for the deal precisely.

Instead, they measure impact at the account level and optimise the entire funnel together.

The outcomes speak for themselves:

→ Deal velocity multiplied by 2.
→ Tier-1 accounts convert 5x better.
→ 2-4X more meetings on ABM accounts.

… and you don’t need Snowflake’s budget or 200+ SDRs to start executing on it.

You can start by:

- Aligning marketing & sales on shared objectives.
- Tracking buying signals 
- Launch ABM campaigns 2 weeks before starting outbound.

… and measure impact at the account level.

And if it feels like too much at once, send a DM… we’ll help you implement this system.

P.S: This workflow breakdown comes from Elric's newsletter.

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