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?

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.

---

Most outbound teams find out about deliverability issues weeks too late. 

By then, the damage is done, your pipeline is already melting.

Then what I call the "circle of short pipeline" starts:
→ Reps have fewer deals
→ They desperately want to close the ones that are open
→ They start looking desperate
→ Prospects feel it
→ They ghost you
→ You lose deals you could have won
→ CRM reason: "no decision"

This is why fixing deliverability issues fast is critical.

But the problem is getting visibility on what's actually happening. 

Deliverability depends on multiple factors: technical setup, domain and email reputation, copy, data quality, bounce rates, and more.

This is why we just shipped the Deliverability Hub in lemlist.

One place to see everything:
→ Delivered vs. spam for warm-up emails
→ Delivered vs. bounced for outreach emails
→ Deliverability scores by mailbox and domain
→ Reputation issues spotted early, before they tank your results
→ Filters by timeframe, mailbox, and provider

No more guessing. No more juggling. 
Everything is in one place.

We already have great feedbacks about it, kudos to the team 🔥

Sales-Tech & GTM Systems | Head of Ops @ ColdIQ

Co-Founder @ Workflows.io | Content, Outbound & AI RevOps engines for hypergrowth startups.

With the experience from:

- Working with 200+ companies on their go-to-market motion
- Generating over +8M organic impressions on here
- Closing $5M+ as a full-cycle AE
- Testing 250+ AI sales tools

I noticed three main problems companies face:

- Not enough leads
- Not enough conversions
- No automated systems & AI

Our solutions:

- LinkedIn content 
- AI RevOps workflows
- Automated outbound systems

The best work in most companies lives in people’s heads, dies when they leave, and can’t scale.

I believe the future is structuring knowledge work with living code:

Productizing AI workflows that human experts are already building.

👉 Follow: Dan Rosenthal for AI growth playbooks

👉 Get in touch: DM me on LinkedIn or email me at dan@workflows.io for collaborations.

👉 Visit: workflows.io if you want help implementing end-to-end AI go-to-market systems for revenue growth.

Dan Rosenthal

This Claude Code plugin enables "agent swarms".

Meaning you can manage 10+ sub-agents in one chat.

But more than that, it instills a building methodology into Claude Code that has dramatically improved the quality of my builds.

Here are the 5 steps broken down into skills:

1️⃣ Brainstorm

Clarifies what to build before a line is written:
- Scans your repo for existing patterns via a research agent
- Proposes 2-3 approaches with tradeoffs considered
- Writes an ideation doc with decisions captured

2️⃣ Plan

Turns the ideation doc into a spec the agent can execute:
- Parallel research agents scan your codebase and docs
- An agent analyzes the concept for gaps and edge cases
- Outputs a plan file with tasks, dependencies, and acceptance criteria

3️⃣ Work

Builds out the plan with QA checks:
- Swarm mode spins up parallel agents for independent tasks
- Runs a "system-wide test check" after every change
- Incremental commits only when tests pass

4️⃣ Review

Code review to iron out issues before shipping:
- Multiple agents review the output across all areas
- Findings triaged with P1/P2/P3
- Agent confirms solution doesn't lie within previous context

5️⃣ Compound

Captures every solved problem while the context is still fresh:
- 5 sub-agents extract root cause, the fix, and prevention tactics
- Saves it to a searchable knowledge base inside your repo
- Future sessions search past fixes automatically before planning

-----

The last step is the key.

"Each unit of engineering work should make subsequent units easier,
not harder."

I'm not an engineer.

But this workflow improves practically any build in Claude Code.

And the "swarms"?

Any step can spin up parallel sub-agents to divide the work.

10 independent tasks = 10 agents building simultaneously.

Watching it happen makes you feel like an AI overlord.

This is an open-source plugin comprised of 29 agents.

Absolute game-changer, shout out Kieran Klaasen.

Comment "repo" if you want me to send over the GitHub link.

Co-Founder @ Workflows.io | Growth playbooks using AI

LinkedIn content is the best inbound channel for B2B.

7+ mil impressions personally, 5+ mil for clients.

We've turned LinkedIn content into a science.

Here's a breakdown of our strategy :


1️⃣ Profile Optimization

Hugely underrated aspect to this.

A high-converting profile looks good and clearly explains expertise.

Winning formula:
- Banner: Logo + Tagline + Designs
- Headline: Role @ Company | {{value prop}}
- Custom Button: Visit my website
- About Section: Hook + Social Proof + What + Who
- Featured Section: Get started + Viral BOF post + Lead magnet offer


2️⃣ Lead Magnet Offer

Not everyone wants to book a call right away.

We always setup lead magnets, offering something for free in exchange for emails that can be enrolled into newsletters + drip sequences.

Flow:
↳ Content preview
↳ Tally or website form
↳ Lead capture + routing


3️⃣ Design System

Almost every single one our posts comes with a visual.

The only way we keep up is through a design system.

Components:
Branding
→ Font styles
→ Font sizes
→ Logos
→ Color hex codes

Backgrounds & vectors
→ Light theme
→ Dark theme
→ Icons
→ Boxes

Templates
→ Carousel
→ Cheat sheet
→ Tech stack
→ Workflow


4️⃣ Anatomy of a LinkedIn Post

Before someone clicks "See more", their feed will be:
- 80% visual
- 20% hook

And then when click "See more", your post needs to look:
- Relatable
- Skimmable
- Unique

Here's the formula:

↳ Hook:
- Social proof
- Numbers
- Relevance
- <140 characters

↳ Readability:
- Line breaks
- Bullet points
- F pattern

↳ Tone:
- Casual
- Talk to ONE person
- Maintain "I"/"We"/"You"


5️⃣ Retargeting Flow

There are typically 4 ways we capture more leads on LinkedIn:
- Lead magnets
- Website visits
- Profile views + connections
- Post engagement

We typically stream those sources into Clay.

Every lead gets enriched and cross-checked to HubSpot.

We prompt 1:1 outreach to Tier 1s through Slack notifications + CRM tasks.

And automate outreach to the rest.

Instantly.ai for email.

HeyReach.io for LinkedIn.


6️⃣ Tech Stack

Design & Creative
- Figma (Designs)
- Miro (Wireframes)
- Adobe (Designs)
- Screen Studio (Screen recording)

Content Creation
- Wispr Flow (Speech-to-text)
- MagicPost (AI copywriter)
- Riverside (Podcast recordings)
- Shield (LinkedIn analytics)
- Favikon (Influencer analytics)

Productivity
- Notion (Content PJM)
- Slack (Internal comms)
- Kondo (DM organizer)

CRM & Automation
- HubSpot (CRM)
- Clay (Data enrichment)
- Customer.io (Nurture sequences)
- beehiiv (Newsletter)

Signals
- Jungler (Post engagement)
- RB2B (Visitor identification)
- Tally (Form builder)

Outreach & Prospecting
- Instantly.ai (Automated emails)
- HeyReach.io (Automated DMs)
- Apollo (Manual outreach)

Sales enablement
- Sybill (AI notetaker)
- Cal.com, Inc. (Scheduling)

------

I can thank LinkedIn for allowing me to bootstrap.

There's no better inbound channel for B2B.

I've been obsessed with figuring out ABM.

Companies like 6Sense gave it a bad rep.

But software players like Clay and Seam AI are reviving it.

And service players like Workflows.io who implement the tech + strategy.

Modern ABM isn't just for small TAMs.

It's for anyone selling high-ACV to targeted accounts.

I published this playbook in 2025 covering how we do ABM.

Here's the 2026 version:


1️⃣ ICP model

Start by mining your CRM:

- Enrich every deal to analyze highest-spend customers.
- Interview AEs and CSMs.
- Find commonalities in closed lost.
- Build your ICP around firmographics, technographics, and account fit signals.
- Backtest the model against your CRM.

This is the foundation everything else is built on.


2️⃣ TAM map

Build a broad TAM map from multiple providers:

- Find firmographic fits with Apollo, Sales Nav, or ZoomInfo.
- Find lookalikes using DiscoLike, Ocean.io, or AI Ark.
- Trim the list using qualification agents.
- Aggregate + dedupe + enrich in Clay.


3️⃣ Account research + scoring

Run AI account research for every company on the list.

Then score accounts into tiers:

- Tier 1
- Tier 2
- Tier 3

We use Clay and ChatGPT to automate this.

This gives you an enriched Target Account List (TAL).


4️⃣ CRM integration

All this data now needs to be made accessible to the sales team.

- Look up companies against your CRM.
- Create a CRM property map.
- Create/update companies + contacts with rules.

Your enriched TAL now lives in your CRM.

Focus adspend on Tier 1s with ABM ads via HubSpot + LinkedIn.


5️⃣ Contact sourcing

Source contacts for every qualified account.

Split into three personas:

- Decision Maker
- Champion
- Influencer

Then for each contact:

- Run AI persona research.
- Look up against CRM.
- Create/update contacts with rules.

Upload the entire stakeholder map to your CRM.


6️⃣ Signal tracking

Track signals for every contact and company.

3 categories:
- 1st-Party Signals: Data you own.
- 2nd-Party Signals: Data given exclusively to you.
- 3rd-Party Signals: Public data.

Sync to CRM as custom events/objects.

Route signals to reps based on territory.

Create CRM tasks + Slack notifications.


7️⃣ Awareness scoring

Roll up 1st + 2nd party signals into an awareness score.

5 stages:

- Identified
- Aware
- Interested
- Considering
- Selecting

Automatically update awareness using workflows.

This lets reps split efforts between warm accounts and net new.


8️⃣ Demand gen

Use tiering + awareness for account planning.

1:1 Plays:
- Warm intros
- Personalized microsites
- Event invites
- Manual outreach

1:Many Plays:
- Automated emails
- Parallel dialing
- Retargeting ads
- Webinars
- Social content
- On-site content
- Video outreach
- Connection requests/DMs

Output: GTM Flywheel
___


Final Outcome: accounts mapped + company tiers + stakeholder maps + signals + awareness scores.

Every channel creates signal to activate the other channel.

Leaving no stone unturned to break into market.

taplio

The Battle

Charles Tenot

Dan Rosenthal

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taplio

The Battle

Charles Tenot

Dan Rosenthal

Followers

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Engagements

Likes

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);}Charles Tenot's LinkedIn Performance

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