Co-founder & CEO @ Ritmoo | Growth Advisor | Leadership Catalyst | GTM Strategist | Led growth in startups from €1 to 100m

I've spent my career helping businesses scale with purpose, transforming ambition into execution and building teams that don't just grow, but thrive.

With a track record of taking companies from €1M to €100M+ in revenue and scaling teams from 10 to 700 people, I've learned that sustainable growth comes down to clarity, trust, and relentless focus. 

Most notably at EVBox, where I served as Chief Growth Officer from 2015 to 2022, I helped lead the business from a small industry player into a global category leader, building a scalable go-to-market engine and a culture of growth.

Today, I'm a fractional growth operator, partnering with high-growth scaleups to architect their go-to-market, sharpen their narrative, and build resilient, high-performing teams. 

I work with companies like SIG, CLEVR, Frends, Dott, vaylens, and more, bringing clarity to chaos and focus to scale.

I'm also the founder of Ritmoo (recently acquired), where we combined expert-led strategy services with lightweight goal management software for fast-moving teams. I'll continue as an advisor through 2026 as Ritmoo enters its next chapter under new leadership.

And I'm the author of Teams in Hell – How to End Bad Management, a practical playbook for building trust, clarity, and adaptability inside modern teams. Available on Amazon: https://www.amazon.com/Teams-Hell-How-End-Management/dp/9090401318/

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🚀 Highlights
• Fractional Growth Operator | Supporting scaleups like SIG, CLEVR, Frends, Dott, vaylens, and more
• 1x Exited Founder | Co-founded Ritmoo (acquired 2025), continuing as advisor through 2026
• Former Chief Growth Officer, EVBox | €5M → €100M+ revenue, 10 → 700 people
• Head of Product Growth, Talentsquare | Built growth strategy through to exit in 2015
• Former Global President, AIESEC | Leading the world's largest youth-led organization
• Angel Investor & LP | Backing early-stage founders via StayingBee, Pal, and Shilling VC
• Author | Teams in Hell (2025), a book on fixing modern leadership from the inside out

🏓 Fun Facts
• Former pro table tennis player with several championships in Portugal
• Proud dad to two daughters with Duracell-level energy

Hugo Pereira

AI won't replace you if you're great at what you do.
𝗕𝗨𝗧... 𝗶𝗳 𝘆𝗼𝘂'𝗿𝗲 𝗵𝗶𝗱𝗶𝗻𝗴 𝗯𝗲𝗵𝗶𝗻𝗱 𝗯𝘂𝘀𝘆 𝘄𝗼𝗿𝗸, 𝗔𝗜 𝘄𝗶𝗹𝗹 𝗲𝘅𝗽𝗼𝘀𝗲 𝘆𝗼𝘂.
 
I'm seeing this play out in real time with my fractional clients.
 
Most of the time they confuse motion with progress.

Instead of shipping 10 things, to focus on the 2 things that could actually drive revenue and retention.
 
The pace increased with AI. 
We're building faster than ever. 
But now we're selective about what we build.
 
Think about it: 
AI can write 10 blog posts in a week. 
Build three email sequences overnight. 
Generate dozens of social posts in an hour.
 
But volume without impact is just noise.
 
AI automates the busy work. 
What's left is either real value creation or nothing.
 
---

Here's what AI won't replace:

→ 𝗦𝘁𝗿𝗮𝘁𝗲𝗴𝗶𝗰 𝘁𝗵𝗶𝗻𝗸𝗶𝗻𝗴
Deciding which 2 things matter more than the other 10 

→ 𝗖𝗿𝗲𝗮𝘁𝗶𝘃𝗲 𝘄𝗼𝗿𝗸
The insight that shifts how people see the problem.

→ 𝗛𝘂𝗺𝗮𝗻 𝗰𝗼𝗻𝗻𝗲𝗰𝘁𝗶𝗼𝗻
The trust that makes deals happen. I just tried out an AI-video SDR, horrible experience. Felt mechanic.

Teams that evolve these skills become unstoppable. 
AI just becomes their lever.
 
Teams hiding behind activity metrics and endless output get exposed fast.
 
Use AI to focus on what actually matters. 
Everything else is just noise.

---

I'm Hugo Pereira, fractional growth operator (CMO/CGO), 1x exited founder, former CGO at EVBox (€1M → €100M+).
 
Follow me for straight talk on leadership, growth, and scaling through clarity. Author of 𝘛𝘦𝘢𝘮𝘴 𝘪𝘯 𝘏𝘦𝘭𝘭 – 𝘏𝘰𝘸 𝘵𝘰 𝘌𝘯𝘥 𝘉𝘢𝘥 𝘔𝘢𝘯𝘢𝘨𝘦𝘮𝘦𝘯𝘵.

Fractional Growth (CMO/CGO) | Author “Teams in Hell – How to End Bad Management” | 1x exited founder (Ritmoo)

I'm not the biggest fan of tradeshows, but damn... do I miss attending CES in Las Vegas! 😅

I went 3 times in a row for EVBox between 2017 and 2020, and it was always such a blast. The reason why it worked so is because a lot came together:

1. 𝗤𝘂𝗶𝗰𝗸𝗹𝘆 𝗼𝘃𝗲𝗿𝗰𝗼𝗺𝗲 𝗝𝗮𝗻𝘂𝗮𝗿𝘆 𝗯𝗹𝘂𝗲𝘀
Even if we were feeling a bit of that new year vibe and not ready to get to work, that event would just get tons of us pumped up. 

2. 𝗔𝗹𝗶𝗴𝗻𝗶𝗻𝗴 𝗿𝗶𝗴𝗵𝘁 𝗼𝗳𝗳 𝘁𝗵𝗲 𝗯𝗮𝘁𝗰𝗵
Sales, marketing, product all in one place. Dry runs, pitch practice, late-night dinners debating the future of our industry. You can't replicate this kind of sync easily.

3. 𝗧𝗼𝗻𝘀 𝗼𝗳 𝗶𝗻𝘀𝗽𝗶𝗿𝗮𝘁𝗶𝗼𝗻 
CES is massive. You barely see 1/3 of it as an exhibitor. Most of us got about half-day off to explore it and it was always worth it. 

4. 𝗧𝗵𝗲 𝗽𝗿𝗲-𝗰𝗼𝗻𝗳𝗲𝗿𝗲𝗻𝗰𝗲 𝘁𝗿𝗶𝗽
2-3 days before the show, a few of us would fly in early. Road trips, deep conversations, inside jokes. This wasn't just team building, we were forming culture.

5. 𝗥𝗲𝗮𝗹-𝘄𝗼𝗿𝗹𝗱 𝘁𝗲𝘀𝘁𝗶𝗻𝗴, 𝘄𝗲𝗲𝗸 𝗼𝗻𝗲 𝗼𝗳 𝘁𝗵𝗲 𝘆𝗲𝗮𝗿
Our messaging, product positioning, objections were all tested live in the first week of January. We'd adjust campaigns and priorities on the fly. There wasn't a need to wait for Q2 data.

---

Now, was it expensive? Hell yes!

Hundreds of thousands of euros. 
The stress of shipping hardware from Europe months in advance.
 
But some of our biggest deals started there. 
Context mattered. 
Timing mattered. 

Being present when the industry was exploding... mattered.

---
 
𝗛𝗲𝗿𝗲'𝘀 𝘀𝗼𝗺𝗲𝘁𝗵𝗶𝗻𝗴 𝗜 𝘁𝗼𝗼𝗸 𝘄𝗶𝘁𝗵 𝗺𝗲 𝗮𝗯𝗼𝘂𝘁 𝗺𝗮𝗸𝗶𝗻𝗴 𝘁𝗵𝗲𝘀𝗲 𝗯𝗶𝗴 𝗯𝗲𝘁𝘀:
 
We try too often to calculate ROI on everything we do. 
 
But some of the most critical investments can't be measured in advance.
 
𝘛𝘦𝘢𝘮 𝘮𝘰𝘳𝘢𝘭𝘦 𝘢𝘧𝘵𝘦𝘳 𝘢 𝘬𝘪𝘭𝘭𝘦𝘳 𝘦𝘷𝘦𝘯𝘵? 
Can't forecast that.  

𝘛𝘩𝘦 𝘤𝘰𝘯𝘧𝘪𝘥𝘦𝘯𝘤𝘦 𝘺𝘰𝘶𝘳 𝘴𝘢𝘭𝘦𝘴 𝘵𝘦𝘢𝘮 𝘨𝘢𝘪𝘯𝘴 𝘧𝘳𝘰𝘮 𝘱𝘪𝘵𝘤𝘩𝘪𝘯𝘨 200 𝘵𝘪𝘮𝘦𝘴 𝘪𝘯 4 𝘥𝘢𝘺𝘴? 
Not in the model.  

𝘛𝘩𝘦 𝘪𝘯𝘵𝘦𝘳𝘯𝘢𝘭 𝘢𝘭𝘪𝘨𝘯𝘮𝘦𝘯𝘵 𝘵𝘩𝘢𝘵 𝘩𝘢𝘱𝘱𝘦𝘯𝘴 𝘸𝘩𝘦𝘯 𝘺𝘰𝘶𝘳 𝘵𝘦𝘢𝘮 𝘭𝘪𝘷𝘦𝘴 𝘢𝘯𝘥 𝘣𝘳𝘦𝘢𝘵𝘩𝘦𝘴 𝘵𝘩𝘦 𝘴𝘢𝘮𝘦 𝘮𝘪𝘴𝘴𝘪𝘰𝘯 𝘧𝘰𝘳 𝘢 𝘸𝘦𝘦𝘬? 
Priceless.
 
A lot of CEOs/CFOs l hate this. 
They want proof before investment.
 
But growth doesn't work that way.
 
You can't A/B test belief. 
You can't pilot commitment. 
You can't run a controlled experiment on culture.
 
The companies that win understand this. 
 
𝗧𝗵𝗲𝘆 𝗸𝗻𝗼𝘄 𝘁𝗵𝗮𝘁 𝗮𝘁 𝘁𝗶𝗺𝗲𝘀 𝘁𝗵𝗲 𝗺𝗮𝘁𝗵 𝗰𝗼𝗺𝗲𝘀 𝗹𝗮𝘁𝗲𝗿. 
𝗧𝗵𝗲 𝗯𝗲𝗹𝗶𝗲𝗳 𝗰𝗼𝗺𝗲𝘀 𝗳𝗶𝗿𝘀𝘁.

---

I'm Hugo Pereira, fractional growth operator (CMO/CGO), 1x exited founder, former CGO at EVBox (€1M → €100M+).
 
Follow me for straight talk on leadership, growth, and scaling through clarity. Author of 𝘛𝘦𝘢𝘮𝘴 𝘪𝘯 𝘏𝘦𝘭𝘭 – 𝘏𝘰𝘸 𝘵𝘰 𝘌𝘯𝘥 𝘉𝘢𝘥 𝘔𝘢𝘯𝘢𝘨𝘦𝘮𝘦𝘯𝘵.

The 1M to 10M ARR journey is not a straight line.
 
A lot of times you read about scaling from 1M to 10M like it's a smooth climb. It isn't.

I've seen companies spike to 5M on momentum, then spend two years stuck there because they never stopped to figure out their actual ICP. 

I've seen others grind through the early millions, then explode once they cracked distribution.

Growth happens in bursts, not steady increments. And those bursts depend entirely on which GTM motion you've mastered.

-

Here's what the journey actually looks like:
 
𝟭. 𝗣𝗿𝗼𝘃𝗶𝗻𝗴 𝘃𝗮𝗹𝘂𝗲, 𝗮𝗴𝗮𝗶𝗻 𝗮𝗻𝗱 𝗮𝗴𝗮𝗶𝗻. 
Early on, you're having deep conversations. Every customer is a case study. 

You're learning who actually needs what you're building. 
Speed doesn't matter (yet) as much as insights do.
 
I made this mistake with my own startup. 

I was obsessing over conversion rates at 80 demos. 

Completely wrong focus. 

I should have been on calls with the 10 best-fit customers, not optimizing funnels.

-
 
𝟮. 𝗧𝗵𝗲 𝗵𝗮𝗿𝗱𝗲𝘀𝘁 𝘀𝘁𝗿𝗲𝘁𝗰𝗵. 
This is where you commit to one channel, one ICP, one repeatable motion. 

Most companies get stuck here because they refuse to walk away from revenue that doesn't fit.
 
You have five use cases. Seven personas. Three markets. 

The board loves the growth. 

But your CAC is climbing and churn is creeping up. 

Nobody wants to make the tough call to say no.

-
 
𝟯. 𝗠𝗼𝗺𝗲𝗻𝘁𝘂𝗺-𝗱𝗿𝗶𝘃𝗲𝗻 𝗴𝗿𝗼𝘄𝘁𝗵. 
Once you crack repeatability, growth compounds fast. 

But only if you built the right foundation. 

This is where community, partners, and deep customer relationships become your flywheel.
 
The companies that made it here didn't get there by doing more. 

They got there by doing less—but doing it better.

---
 
Your GTM motion changes at each stage too:
 
→ At $5K ACV, it's all about velocity and content 
→ At $50K ACV, it's thought leadership and events 
→ At $500K ACV, it's brand and expertise of your people 
→ At $1M+ ACV, it's pure relationships and CxO referrals
 
Trying to run a high-touch motion at low ACV kills your margins. 

Running a low-touch motion at high ACV kills your close rates.
 
Most founders try to scale what got them to 1M. 

That's the mistake. 
What got you here won't get you there.
 
The jump from 1M to 10M isn't about working harder. 

It's about knowing when to pause, when to pivot your motion, and when to stop chasing every deal that comes your way.
 
Growth isn't linear. 
Momentum is.

---

I'm Hugo Pereira, fractional growth operator (CMO/CGO), 1x exited founder, former CGO at EVBox (€1M → €100M+). 

Follow me for straight talk on leadership, growth, and scaling through clarity. Author of 𝘛𝘦𝘢𝘮𝘴 𝘪𝘯 𝘏𝘦𝘭𝘭 – 𝘏𝘰𝘸 𝘵𝘰 𝘌𝘯𝘥 𝘉𝘢𝘥 𝘔𝘢𝘯𝘢𝘨𝘦𝘮𝘦𝘯𝘵.

If B2B marketing advice feels comforting, be worried.
 
Comforting usually means it wasn't written for you, it was written for everyone. 

And what works for everyone works for no one.
 
Last week, I joined Dreamdata with Casper (agency founder, 100+ B2B SaaS clients) and Francesca (demand gen director at Legora, legal AI scaleup) to discuss what worked in Marketing in 2025 and will 2026 be about.

Agency view, fractional view, operator view. 

Here're my main highlights summarized 👇
 
𝗦𝗽𝗲𝗲𝗱 𝘄𝗼𝗻 𝗶𝗻 𝟮𝟬𝟮𝟱
• Francesca nailed the current context: "everything, everywhere, all at once." 
• AI let teams ship faster, however standout teams do it without sacrificing quality. 
• The luxury problem for some is when your entire market is in-buying mode, it's about demand capture, not generation.
 
𝗪𝗵𝗮𝘁 𝗹𝗲𝗳𝘁 𝘁𝗵𝗲 𝗽𝗹𝗮𝘆𝗯𝗼𝗼𝗸
• Big trade shows. Done. 
• We all moved budget to owned events where you control the narrative, the audience, and the ROI. 
• Side events next to big conferences can be a good place to test out guerrilla marketing, which still works.
• Traditional paid search is declining hard. Google Ads spend down 70% for some of us. LinkedIn up 120%. The shift is real.
 
𝗪𝗵𝗮𝘁'𝘀 𝘄𝗼𝗿𝗸𝗶𝗻𝗴 𝗻𝗼𝘄
• Thought leader ads on LinkedIn, but evolved. Not just employee posts anymore. Get customers and prospects to post about you.
• Reddit is undervalued, even if tough to make it work.
• YouTube is massive but no one talks about it. 
• TikTok works if you can stomach the creative investment.
• Influencer marketing in B2B. Yes, really. Some of us are paying B2B creators to post about products. It's not cheap, but it works.
 
𝗧𝗵𝗲 𝗔𝗜 𝗽𝗹𝗮𝘆 𝗲𝘃𝗲𝗿𝘆𝗼𝗻𝗲'𝘀 𝗺𝗶𝘀𝘀𝗶𝗻𝗴
• 90% of AI talk is about content workflows. The real win seems more around proactive insights and signals.
• Simple wins in AI can be practical agents (we built a bunch at Frends) that research prospects before meetings, auto-fill lead context when they come in, and push win-wire analysis into Slack. Simple, yet effective
 
𝗢𝗻𝗲 𝗽𝗿𝗲𝗱𝗶𝗰𝘁𝗶𝗼𝗻 𝗳𝗼𝗿 𝟮𝟬𝟮𝟲
• Personalization beats volume. 
• The companies stuck between PLG and enterprise are struggling. Pick a lane.
 
Full conversation on Dreamdata's Attributed podcast, link in comments.

Worth the listen.

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I'm Hugo Pereira, fractional growth operator (CMO/CGO), 1x exited founder, former CGO at EVBox (€1M → €100M+). 

Follow me for straight talk on leadership, growth, and scaling through clarity. Author of 𝘛𝘦𝘢𝘮𝘴 𝘪𝘯 𝘏𝘦𝘭𝘭 – 𝘏𝘰𝘸 𝘵𝘰 𝘌𝘯𝘥 𝘉𝘢𝘥 𝘔𝘢𝘯𝘢𝘨𝘦𝘮𝘦𝘯𝘵.

Your content team produced 247 pieces last year.
Your best prospects read 3.

That's not a content problem. 
That's a strategy problem.
 
Most GTM teams are stuck in a volume trap. 
More blogs. 
More case studies. 
More webinars. 
More LinkedIn carousels. 

The machine keeps running because stopping feels like quitting.
 
Chances are that your buyer or ideal customer scrolls past 90% of what you publish. 

Not because it's bad. 
Because it's not for them.
Not right now. 
Not precise enough to stop their scroll.
 
𝗠𝗼𝘀𝘁 𝗽𝗲𝗼𝗽𝗹𝗲 𝗱𝗼 𝗻𝗼𝘁 𝗻𝗲𝗲𝗱 𝗺𝗼𝗿𝗲 𝗰𝗼𝗻𝘁𝗲𝗻𝘁.
𝗧𝗵𝗲𝘆 𝗻𝗲𝗲𝗱 𝗼𝗻𝗲 𝗽𝗿𝗲𝗰𝗶𝘀𝗲 𝗮𝗻𝘀𝘄𝗲𝗿, 𝗮𝘁 𝘁𝗵𝗲 𝗿𝗶𝗴𝗵𝘁 𝘁𝗶𝗺𝗲, 
𝗳𝗿𝗼𝗺 𝘀𝗼𝗺𝗲𝗼𝗻𝗲 𝘁𝗵𝗲𝘆 𝘁𝗿𝘂𝘀𝘁.
 
Not another "5 trends in [your industry]" post. 

The one answer to the specific problem keeping them up at night. From someone who's solved it before.
 
𝗪𝗵𝗮𝘁 𝗜 𝗯𝗲𝗹𝗶𝗲𝘃𝗲 𝗶𝘁'𝘀 𝗮 𝗴𝗼𝗼𝗱 𝗲𝘅𝗲𝗿𝗰𝗶𝘀𝗲 𝘁𝗼 𝗿𝘂𝗻 𝗼𝗳𝘁𝗲𝗻:
→ Kill half your content calendar  
→ Talk to 10 customers about their actual questions  
→ Answer those questions with brutal precision  
→ Publish when it matters, not because it's Tuesday
 
Volume is a vanity metric disguised as discipline.
 
Precision is how you build trust.
 
This year, publish less. 
Matter more.
 
---

I'm Hugo Pereira, fractional growth operator (CMO/CGO), 1x exited founder, former CGO at EVBox (€1M → €100M+).
 
Follow me for straight talk on leadership, growth, and scaling through clarity. Author of 𝘛𝘦𝘢𝘮𝘴 𝘪𝘯 𝘏𝘦𝘭𝘭 – 𝘏𝘰𝘸 𝘵𝘰 𝘌𝘯𝘥 𝘉𝘢𝘥 𝘔𝘢𝘯𝘢𝘨𝘦𝘮𝘦𝘯𝘵.

I've seen three types of horrible managers in my career:
1) the Controller, 2) the Ghost, 3) the Firefighter.
 
You've probably worked for at least one of them.
 
- 

𝗧𝗵𝗲 𝗖𝗼𝗻𝘁𝗿𝗼𝗹𝗹𝗲𝗿 is the micromanager. 

Wants updates constantly. 

Reviews every PPT slide down to the font size.
 
He doesn't come from a bad place, he likes being in the details. 

But he confuses being in the details with controlling the output.
 
That makes people anxious. 

They stop thinking for themselves because everything gets second-guessed anyway.
 
He simply doesn't know when to let go.

-
 
𝗧𝗵𝗲 𝗚𝗵𝗼𝘀𝘁 disappears when you need him most. 

Only shows up to take credit.
 
The team works on a big project for months. 

When it's time to present to leadership, he pops up: "I'll handle this one."
 
He might think he's giving freedom. 

But what he's actually doing is abandoning the team without guidance or direction.

-
 
𝗧𝗵𝗲 𝗙𝗶𝗿𝗲𝗳𝗶𝗴𝗵𝘁𝗲𝗿 treats everything like an emergency. 
Every deadline is yesterday. 
Every task is urgent.
 
He's the one driving burnout. 

Always pushing, pushing, pushing, and never setting the right pace.
 
Sometimes you need high speed. 

But you also need space to rest, step back, and see if what you're doing actually matters.
 
These three managers show up everywhere. 

I've worked with all of them. 

I've coached leaders who were all of them without realizing it.

---
 
𝗜𝗳 𝘆𝗼𝘂'𝗿𝗲 𝗱𝗲𝗮𝗹𝗶𝗻𝗴 𝘄𝗶𝘁𝗵 𝗼𝗻𝗲:
 
→ 𝘛𝘩𝘦 𝘊𝘰𝘯𝘵𝘳𝘰𝘭𝘭𝘦𝘳: Ask for clear decision-making authority in specific areas so you can own outcomes, not just tasks. 

→ 𝘛𝘩𝘦 𝘎𝘩𝘰𝘴𝘵: Create regular check-ins and document decisions, make visibility a system, not a favor. 

→ 𝘛𝘩𝘦 𝘍𝘪𝘳𝘦𝘧𝘪𝘨𝘩𝘵𝘦𝘳: Push back on urgency by asking, "What's the cost if this waits 24 hours?". Most fires aren't real fires.

Bad management isn't about bad people. 
It's about unexamined patterns that destroy teams. 
Recognize the pattern, break the cycle.

---
 
I'm Hugo Pereira, fractional growth operator (CMO/CGO), 1x exited founder, former CGO at EVBox (€1M → €100M+).
 
Follow me for straight talk on leadership, growth, and scaling through clarity. Author of 𝘛𝘦𝘢𝘮𝘴 𝘪𝘯 𝘏𝘦𝘭𝘭 – 𝘏𝘰𝘸 𝘵𝘰 𝘌𝘯𝘥 𝘉𝘢𝘥 𝘔𝘢𝘯𝘢𝘨𝘦𝘮𝘦𝘯𝘵.

There’s no shortage of B2B marketing advice for 2026. Clarity is the scarce resource, and tomorrow you might get some.
 
Tomorrow I'm joining Dreamdata for a live session on what's actually working in B2B marketing, and what's quietly dying.
 
An honest conversation with Francesca (Legora), Casper (SparkForce), and Steffen (Dreamdata) on what worked in 2025 and what B2B marketing trends, tactics, and bets to place for 2026.
 
---

Here’s a preview of the takes I’ll be bringing up 👇
  
𝗪𝗵𝘆 𝗴𝗮𝘁𝗲𝗱 𝗰𝗼𝗻𝘁𝗲𝗻𝘁 𝗶𝘀 𝘀𝘁𝗶𝗹𝗹 𝗵𝗼𝗹𝗱𝗶𝗻𝗴 𝘁𝗲𝗮𝗺𝘀 𝗯𝗮𝗰𝗸 
Teams complain about MQL quality or focus, yet keep hiding value behind forms. I’ll share when to gate (rarely) and why value-first beats friction every time.
 
𝗧𝗵𝗲 𝗔𝗕𝗠 𝗽𝗹𝗮𝘆𝗯𝗼𝗼𝗸 𝘁𝗵𝗮𝘁 𝘄𝗼𝗿𝗸𝗲𝗱 𝗮𝘁 Frends 
Industry-specific content, owned events, and employee/expert-led thought leadership, backed by targeted sponsored ads to ICP. Executed by buyer, region, and context. (Case here, thanks TGS: https://lnkd.in/efCuChDq)
 
𝗔𝗜 𝗶𝘀 𝗰𝗿𝗲𝗮𝘁𝗶𝗻𝗴 𝘀𝗹𝗼𝗽. 𝗧𝗵𝗮𝘁'𝘀 𝘆𝗼𝘂𝗿 𝗼𝗽𝗽𝗼𝗿𝘁𝘂𝗻𝗶𝘁𝘆. 
Most content won’t matter, and you’ll still produce it. Accept that. The real question: will you bet on 1–2 pieces with enough care that people actually want to read?
 
𝗪𝗵𝗲𝗿𝗲 𝗔𝗜 𝗮𝗰𝘁𝘂𝗮𝗹𝗹𝘆 𝘄𝗶𝗻𝘀 
AI doesn’t win by mass-producing listicles or scaling lazy outbound. AI wins when it 𝘤𝘰𝘮𝘱𝘳𝘦𝘴𝘴𝘦𝘴 𝘵𝘩𝘪𝘯𝘬𝘪𝘯𝘨, not when it replaces it.  When it helps teams spot patterns faster, pressure-test ideas, sharpen POVs, and move from insight to execution with less friction. 
 
𝗖𝗼𝗺𝗺𝘂𝗻𝗶𝘁𝘆-𝗹𝗲𝗱 𝗯𝗲𝘁 𝗶𝘀𝗻'𝘁 𝗼𝗽𝘁𝗶𝗼𝗻𝗮𝗹 𝗮𝗻𝘆𝗺𝗼𝗿𝗲 
Partner ecosystems, customer communities, and expert visibility are the backbone of pipeline creation. In any B2B SaaS model. Now, more than ever.
 
If you're a GTM or marketing leader tired of recycled takes and want to hear what's breaking, what's working, and what to bet on in 2026, join us.
 
Link in comments.

---

I'm Hugo Pereira, fractional growth operator (CMO/CGO), 1x exited founder, former CGO at EVBox (€1M → €100M+). 

I write about leadership, growth, and scaling through clarity. Author of 𝘛𝘦𝘢𝘮𝘴 𝘪𝘯 𝘏𝘦𝘭𝘭 – 𝘏𝘰𝘸 𝘵𝘰 𝘌𝘯𝘥 𝘉𝘢𝘥 𝘔𝘢𝘯𝘢𝘨𝘦𝘮𝘦𝘯𝘵.

CEO at Slite (YC18) | We build the first knowledge base on autopilot, in remote since 2016!

I'm the founder of Slite & Super (YCW18) 👉 Super.work 

Super.work turn all your company data into answers & AI agents for your whole team.

It comes with the recipes and tools for your team to get instant benefit from AI at work

Slite is your team dead simple yet crazy powerful knowledge base, since 2017 🔥

I'm fortunate to lead a diverse team of exceptional individuals spread across 10+ countries 🇮🇳 🇬🇷🇱🇹 🇦🇷 🇬🇧 🇳🇱 🇫🇷 🇳🇴 🇺🇸 🇪🇸 🇩🇪 🇨🇦 🇵🇹 . Our journey includes going through YC W18 batch, raising $15M+ in funding from top-tier investors like Spark Capital and Index Ventures, and serving tens of thousands of teams monthly.

Christophe Pasquier

$46M valuation at last raise.
$15M invested.
$4M+ ARR with 50% YoY growth and 115% NRR.
At these numbers, we could exit for a 5-12x multiple depending on strategic interest.

In any scenario, I'd walk away with a meaningful payout.
So why don't I?

Every time I think it through, I ask: what would I actually be trading?

1/ I get to pick and grow an - incredible - team
Most exits come with earn-outs and culture shifts that grind people down. I've seen it happen countless times with friends.

Our team is exceptional, it's a luxury I have to maintain this group of people around me happy and deliver incredible work. I'm not willing to trade that for a payout if we all land in the wrong place and lose this.

2/ We have the chance to push our category to new frontiers
We're years ahead in knowledge management and enterprise search, shipping things no one else has.

We did it in the last years, and will do it again in 2026.

Acquisitions rarely protect that kind of momentum and innovation is usually the first thing to die. And if that was the case, it would be the worst place to work for me.

3/ We're in a lucky position
We're profitable, extremely ambitious, and all this with low pressure. That's a very rare place to be in. Trading independence for someone else's roadmap doesn't make sense when you're already on solid ground.

This is one of the hardest question to navigate as a founder, I would never have written this even 2y ago, and I might be in a different place in a few years. Today I feel blessed to think this way.

Curious to hear about fellow founders, do you have an "exit strategy" or do you feel the only way to succeed as a founder is to be 100% commited?

PS - If you're a founder and thinking of this topic, one truly great book to check is "Lost & Founder" by Rand Fishkin

CEO Slite & Super (W18) | Most accurate search & workflows on team data

We caught 3 permission bugs this weekend that staging would never find.
My CTO wanted to build the system that made this possible for years, now I get why.

When you're refactoring permissions logic on a mature codebase, you can't test every edge case. Staging doesn't have realistic org structures. Unit tests can't cover thousands of users with nested team hierarchies.

Here's what we're running at Slite.

When we want to ship critical changes, we run two versions of our code in parallel.

The proven production system handles the actual response. New system processes the same request silently on the same inputs, testing changes, logging the results for us to see if we missed anything.

Every permission check hits both:
- Same input (user, resource, action)
- Old system returns what the user sees
- New system computes what it would return
- Compare outputs, log mismatches

This weekend it caught 3 critical issues this way, that our developer environment would never surface because test data isn't always able to cover all the edge cases of massive orgs.

My CTO dreamed about this for years. My inner nerd is so happy we're getting there.

I spent 7+ years forcing PLG on Slite.
Super has been SLG from Day 1.
Thing is - there was only one right choice from the beginning. I didn't know how to make the call.

Everyone treats PLG vs SLG like a philosophy. It's not.
Here's how I think about it now:

1/ The viral loop test
Ask one question: Will each free user naturally bring 10 more?
Not through referral programs. Not through incentives. Organically. Because the product spreads by being used.
Lovable has this. Figma had this. Slack had this.
If you don't have a natural loop, PLG becomes a leaky bucket you're constantly filling.
And that's 90% of B2B companies.

2/ The contract math
For SLG, the test is simpler:
Can you sell yearly contracts starting around $15k+?
If yes, the 1:1 time is worth it. If no, you can't afford the sales motion anyway.
PS - the number depends on your retention and LTV, but the principle remains.

3/ The setup question
This one matters more in the AI era:
Does your product require dedicated time helping customers configure it?
If setup is complex and ongoing, you need the price point that justifies it.
And if that setup isn't temporary (something you're fixing with better product), then you're sales-led whether you like it or not.

4/ It's been decided for you, already.
But stop treating this like a strategy decision.
Look at your product. Look at your price. Look at your loops.
The motion is already there. Your job is to recognize it.
Super was SLG from Day 1 because the product demanded it.

Not smarter. Just listening.

Our Super homepage looked slick in dark mode. Conversion dropped.


I'm in love with the brand we developed for Super. Dark backgrounds, beautiful gradients, space-themed colors, the whole nine yards. Our design team crushed it.

But we developed it before our May public launch. Since then our # of users exploded and we saw the best ones - by far - being non developers.  

They're ops managers, support leads, sales teams - normal people here to get instant answers and accelerate the rest of their work. 
And we attract more and more of these persona too!

Problem is, we see our demos generating terrific impressions but our homepage conversion rate dropping. 
We looked at this and emitted the hypothesis that our ICP might not want a terminal aesthetic. And that maybe, the whole vibe of Super.work felt like not thought for them.

So let's see! We ship our new homepage (the right one) next week, with this and a simplification of our value prop. 

We'll see what it gives, and place your bet, will it work? Is this worth challenging the whole visual brand?

Last year - I made a resolution
Share what feels uncomfortable.

We only see wins and launches and funding rounds on Linkedin.
Never the pivots, the hard calls, the tough bets.

So I decided to share just that - all the real things behind building.
And last month, you all were incredibly kind to me.

I got so many messages about how my posts resonated with people.
And what made it special was

Many of the messages were from founders and builders I deeply respect.

Experienced founders who'd done millions in ARR and share similar challenges, some we rarely see shared in the open.

New founders who found it comforting to know that mistakes are a big part of building.

I realised that the internet has been making all the real builders feel inadequate when building is messy, slow, and HARD - all at the same time.

In 2026,
It's my resolution to double down on the honesty
No corporate speak, no inflated metrics
I'll share things I do everyday, and the things I learnt after years of expensive mistakes.

And in case you don't know
I'm Chris, co-founder at Slite (a beautiful Knowledge Base) and Super.work (best AI search on all your team's tools).

We're a 20 person remote team, profitable, globally-distributed, and building 2 products we're really proud of.

I'm gonna publicly share the real stuff even more this year.
Follow if you'd like to come along for the journey.

We throw dinners with top tier operators every month.
Last week was our 3rd edition with Chiefs of Staff in Berlin, here are the nuggets.

→ What is a Chief of Staff?
If you're not familiar with this, quick catch up: they're one of the most interesting roles emerging in tech startups and scaleups in the last 5 years. 
Usually a Chief of staff is attached to one of the C level and acts as their right wing: they'll work on their project, with their authority, but with much more time to properly execute. But they - for the large majority - don't have people to manage.

I absolutely love this role: think of it like some of the smartest folks in the company, with the authority of the CEO, here to solve the hardest cross functional problems hurting teams every day but owned by no one. 

→ When CoS act as silo-breaker
One of the best story of this evening, one of our guest was Chief of Staff to the CTO of a 400 ppl company, and it happens that each of the 5 C level has one.
Result is they actually spend time between them to detect and course correct the issue of their leadership team.
With the right C level and chief of staff this is an incredible super power for any scaling team.

→ But the downside of this..
For other CoS, this necessity to manage their leadership team is very hard and can be a curse more than a blessing.
Projects are shared by C levels in cryptic manners and conflicts between C level has been raised by some as one of the toughest challenge they have on their plate.

→ Top challenge for 2026 remains internal communication
We heard this in the 2 previous dinners, and this is still one of the top problems to be solved for this cross operational role: 
→ accelerate onboarding
→ remove the noise of repetitive questions
→ avoid the unnecessary friction between departments.
(not really a surprise as we deploy super.work through a lot of chief of staff and this is one of the reasons to learn more from them)

I loved this format, if you're a founder, throw these dinners with your top buyers, make them have a good time and learn from them!

It was a blast to meet you all Henriette Brune Jan Philipp Kuhnert Trang Thuy (Rachel) Dang Joon Knapen Mitja Thomas Tabea Severin Anna Jopp Eva Sayre Fadeelah Al-horaibi

Hope you enjoyed it! (and if I missed a key insights you got from this, share in comments ;) )

I have 2 AEs closing deals all day. 
I banned the team from interrupting them. 
Gave them this instead 👇

Everyone needs something from Sales.
GTM needs attribution. Product wants early users feedback. CX needs customer expectations. Execs needs results reports.

So I built a workflow that automatically 👇
→ Goes through Attio, sales recordings, notes, Slack
→ Looks for signals for each department
→ Creates a one-pager with 2 main things each department should know from last 2 weeks of sales conversations.

Here are 4 most interesting things it gives

1/ For marketing
The workflow pulls from last week's Attio data, Slack mentions, and call transcripts.
Then generates:
Which channels drove conversations
How prospects actually describe their problem
What messaging made them reach out
No more guessing which campaign worked ✅

2/ For product
Every feature request. Every "I wish it could..." moment.
Surfaced from real conversations. Ranked by frequency.
You'll hear patterns you'd never catch manually. The roadmap starts writing itself.

3/ For customer support and success
What objections keep coming up. What's confusing prospects before they become customers. What expectations are being set that CS will inherit.
Fix it in sales, save hours in support 😅

4/ For dev
Technical blockers and integration requests.
Every "does it work with..." question. Every security concern. Every API ask.
No more secondhand requirements through three Slack threads.
The output is simple. A bi-weekly digest with:
→ Top requests
→ Attribution insights
→ Excitement signals
→ Deal blockers

Each department gets points. Relevant to them. Actionable.
All from one automated workflow.

If you want this for your team, DM me.

Consensus killed one of my products.
Here are 2 stories, 1 fail and 1 win, 2 years apart.
1/ 2022: Failure by compromise
We went to build a major feature of Slite, Discussions. A way to bring the key decision-making discussions back in your documentation.

Half the team wanted to build them as an extension of docs. The other half wanted it as an extension of comments.

We settled somewhere in the middle.

The result: a Frankenstein. Hours of endless debate. ICs unable to move because nothing was clear.

Consensus killed our product for 1+ year.

2/ 2024: Win by committing.
I pitched starting a new product on top of our existing one.

Half the team thought I'd lost my mind.

We were struggling to unlock growth for Slite. My solution? Build a second product that would take 14 months and split our focus.

The hypothesis - which proved right - was that our buyers would need both. But the objections were valid. "We should double down, not diversify." Multiple heated discussions. Smart people on both sides, all caring deeply about the company.

We discussed, heard all opinions, and took the decision. Not half way.

Similarly when we decided to build it a new debate emerged: should it be inside Slite, or as a standalone?

We picked one direction, and avoided the 2022 pitfall.

The result: a highway for developers and designers instead of a maze, and an incredible product, Super, a year later.


Strong decisions are gifts for your team.

Yes, you can be wrong. But it's much easier to go 100% in one direction, realize your mistake, and turn around than to walk multiple paths simultaneously with low conviction.

Strong decisions let us reach a lovable product, validate demand, and generate revenue at the same time.

That's my ideal is for our team: generate strong decisions, loosely held. Don't be blind, be opinionated.

I made 2 mistakes setting my company goals: setting them on vibes, and basing them on hope.
Now we work differently.

This is my full journey of setting goals - the 2 times when we did it wrong 😅 and how we do it now.

1/ Before traction, we set goals on vibes
Right before our YC batch, we had nothing - no funnel, no distribution, just a launched product. I asked our partner what our demo day goal should be.

Their answer:
"You want to be the Slack for notes, so aim for the sky. Go from 1,5k to 100k users in 3 months."
(not representative of my overall YC experience btw, this is the only bad advice I can recall, and it was probably more due to me as a young founder interpreting this from our convo)

I tuned it down to 30k, but it still put enormous pressure on the team. We just had started, the 1,5k users where volatile signups from our initial PH...
We shipped like crazy and hit 13% week-over-week growth. By any measure, it was the best stretch the company had ever had. But it felt like failure because we missed the number.

I remember feeling frustration instead of celebration, and I know the team felt the same.

That's when I knew something was broken about how we set goals.

2/ After traction, we set goals on hope
At $1-2M ARR, we were powering through and I needed something to energise myself, the board, and the team.

So we said "let's double the business" without a clear set of actions to achieve it.

The issue there is it made us lose focus on foundations, on the quality we needed to keep pouring in our customers and core feature to build our compounding effects.

As a result we added years of legacy to pay back by trying to aim for only very large bets who could radically raise our trajectory.

3/ After traction: goals from math
Now, we start with baseline
→ What stays the same if we do nothing different
→ Existing revenue trends, current retention, predictable growth.
Then we look at specific levers that could change things:
→ Repositioning Slite as a bundle
→ Outbound, SEO, and LinkedIn efforts
→ Having developers work directly on sales deals

Each lever has an estimated impact. The goal becomes baseline plus realistic lever outcomes, not a number we hope sounds impressive.

The past two years, we've hit our goal, last year we did +50% in revenue with great metrics on all sides.

Not because we sandbagged, but because we were realistic about what was achievable. And it cascaded down in improving all our business fundamentals, our key customers, our NRR, our brand positioning, our product stability, our developer velocity etc...

The way I think about it now:
Goals should be just out of reach enough that hitting them feels great
But missing by 5-10% still feels like a win.

If hitting your goal brings relief instead of joy, the goal was wrong.

OpenAI had the first mover's advantage in AI but their last big thing was... announcing ads. Anthopric? Claude Code.
Why is Anthropic - the second mover - winning? When did OpenAI begin losing?

Here's what I'm seeing:

1/ First movers set the map, second movers choose the road
OpenAI defined the category. But they also made every mistake first.
Anthropic watched. Learned. Then picked their lane.
Model quality for coding. Enterprise reliability. Developer tools.
They didn't try to win everywhere. They just won where it mattered.

2/ Consumer success can become a distraction
OpenAI built ChatGPT into a cultural phenomenon. 100M users. Household name.
But that success pulled them into a war with Google and Meta. Massive companies with infinite resources and consumer DNA.
Meanwhile, Anthropic stepped away from the crowd.
They bet on developers and enterprise work.

3/ They shipped protocols, not just products
MCP. Defining papers on RAG. Skills.
They shipped foundations other companies build on.
When you set the standard, you don't chase the market. The market comes to you.

4/ The cult following became a movement
It started with developers who loved Claude for coding.
Then Claude Code dropped. The first true agentic AI for technical work.
Then Claude Cowork. The same power, for everyone else.
Enterprise usage? Already led by Anthropic.

Not because they were first. Because they were focused.
Anthropic kept watching what's missing while OpenAI tries to win a losing battle on 10 fronts.

What if you could use Nano Banana right inside your docs?
Hear me out, you can generate any visualization you need - blog headers, product specs, social media assets, whatever.

I'm probably more excited about this than I should be but it has been a lot of fun 😅

Slite is becoming absurdly powerful for doc writing workflows.

You can already fill your docs with information from all your tools using Super.
You can drop rough notes and auto-format them at once,
You can proofread these docs against the rest of your data,

And now we play with generating images based on whatever you're writing, without switching a single tab.

Here's what this unlocks:
→ Marketing can generate infographics on the fly for their posts
→ Yesterday I read a complex RFC translated in a human readable diagram
→ Devs can quickly visualize a new spec's architecture without drawing rectangles in Excalidraw.
→ Anyone can create a doc cover in seconds.

No context switching.
No opening Gemini in another tab.
Just describe what you need and keep writing.

Shipping soon.
DM me if you want early access 😉

Trying out Nano Banana in Slite

Documentation won't be read by humans anymore
Check this chart. Our team asks exponentially more and writes exponentially less.

In a world of AI, Context is king and you need verified company context.
But manual documentation is dying.

It always was a painful process. You hire smart people to do high-leverage work, and then ask them to spend hours writing docs that no one can find the next day. Nobody wins.

So what if we had best of both worlds, what if the knowledge base maintained itself?
Imagine your Knowledge Base
- automatically detecting that the onboarding guide needs to be updated because of a Slack convo and just updates the doc itself.
- understanding your Granola transcripts and automatically updating key client info in the pipeline tracking docs.

All this to deliver spot-on answers to your team. This idea really excites me.

It's the truest form of what I set out to do with Slite since the day it began.

Have a Knowledge Base that's not outdated or hated - while still being a single source of truth for your entire company.

And now, since the tech's caught up, 
All Knowledge Bases will just... do the writing, editing, updating, of your everyday work.

Here's our 11 step-roadmap to build the first knowledge base on autopilot
0. Make a Knowledge Base so simple everyone documents and reads ✅
1. Build a nested doc system for all types of docs ✅
2. Let teams verify docs - via API/app - recurrently so it stays up-to-date ✅
3. Let teams talk to their docs like they'd talk to a coworker ✅
4. Flag gaps from question asked ✅
5. Go beyond the Knowledge Base, let teams ask about ANYTHING from ANY tool (Super.work) ✅
6. Cross-check docs against real-time data sources - Slack chats, PRs, CRM records ✅
7. Generate suggestion of changes ready to be applied 🔨
8. Detect outdated articles and generate suggestions on autopilot. 🔨
9. Generate suggestions to fill gaps, on autopilot. 🔨
10. Build the first API endpoint so agents can update/edit your docs 🔨

We're at step 7. That's the thesis. 

Do you buy it?

We've all heard that 95% of AI pilots fail.
No one talks about how to be in the 5%.
We've done 100+ AI handholding pilots for Super with great companies this year and of the ones that fail, always boil down to 1 of these 4 points.

1/ The technology sold simply can't solve your use case → impossible for it to work
The AI fundamentally can't do what you need.
Typical case: You try a custom GPT to "find the answer in your docs". If your service doesn't offer semantic search like Super does, it simply can't work.
It's not a training issue or a prompt issue. The architecture can't support the job.

2/ Missing integrations/tools → impossible to deploy
It can't connect to your CRM, can't pull from your knowledge base, can't push to Slack. Your team would need to copy-paste between six different tools to make it useful. Nobody's doing that. The AI stays in the sandbox while everyone goes back to their old process.

3/ Threshold of reliability is not met → impossible to build trust
The AI works in a demo. It falls apart in your actual workflow.
If the AI is right <90% of the times, it means your team has to verify every single output. Which means they're doing their original job plus babysitting the AI. The cognitive overhead is higher than just doing it themselves. After two weeks of spot-checking, they stop using it entirely. Trust never forms.

4/ No rails set by the tool → impossible to adopt
If you say your tool can do everything, teammates won't know what to use it for.
If you say your tool does X better than anyone in the market, they'll know exactly when to log in.
The blank input box is where adoption goes to die. This is why we obsess over step 4.

Super.work's an AI search on company data with a - you guessed it - blank box at boot up. So to boost adoption, we think of core use cases we want to solve and integrate as deeply as we can there.

If you use our web extension, your support will get Super directly injected in their Intercom and Zendesk for instance. Within a few months, this becam eone of the most used triggers by Super customers.

They could've done it before the button too, the button just makes it obvious.
One click, one job, zero ambiguity.

And we replicate this over and over.

I'm still documenting learnings as the space evolves.
If you're in the same boat - I'd love to know your learnings/takes!

Anthropic is the 🐐.
They will turn my mother into a developer.

First they redefined development with Claude code, and now they want all of us to act as this new breed of developers.

If you code you've seen the pattern they cracked: instead of pouring things in context, just a series of simple atomic tools, called sequentially, in a very fast manner. Grep (search), create, read, write. That's it.

Last month, they put this pattern in our Chrome browser. Claude for Chrome can read, browse, load a URL, screenshot a page.

Now they release Claude Cowork with the same core pattern: it can do all the actions you do with your finder, and simple file editing, on top of advanced scripting.

For the everyday user, they get a true feeling of what 'agentic' means for the first time in their life. Ask it to organise your folders, prepare a spreadsheet based on scattered data, generate a summary from your notes, find things locally.

They managed to match the experience that made them kings in the dev space, except for 1 exception.

Claude Cowork needs knowledge.

Claude Code had this knowledge in the form of your entire codebase.
Your code base is clean, cohesive, structured. When you write `functionName`, you can't make a typo, or refer to it by `maFonction`. 

What made the series of search and read pattern work for Claude code is simply not present for Claude Cowork. 
You have no graph of knowledge, your data - and your team's - is a messy pile of docs, databases, and Slack threads.

And that's exactly why we've been focusing all our efforts in the past 3 years to build the most accurate source of knowledge for teams with Slite, and the ultimate knowledge retriever with Super.work.
This takes a lot of effort, you need
→ connections to all your toolstack
→ embedding of your core, unstructured knowledge
→ sql queries for your structured knowledge
→ smart orchestrated search to blend both (if you say what have I been doing you want the agent to know you're an ops leader and find the info int he right channels and tools)
→ verified knowledge (ideally continuously maintained with signals from your toolstack)

This being said I could not be more excited by this release. 
This will be banger - especially with a true enterprise search MCP.

 Thanks for pushing the world of work forward Felix Rieseberg Boris Cherny, and for pushing this whole project so fast!

PRs merged per contributor went from ~30/quarter to ~70/quarter.
Same team. Same headcount. More than 2x the output.
That's when my thinking flipped. How is this so cheap?

$100/month per person to double engineering velocity. That's less than what we spend on coffee.

1/ The math isn't "AI cost vs no AI cost"
It's AI cost vs the alternative: hiring more people, longer timelines, slower iterations.
One senior engineer costs $150k+/year. We're getting equivalent output gains for $24k across the whole team.

2/ The gains compound
Faster shipping mean faster feedback loops. Faster feedback means better product decisions. Better decisions mean less rework.
The 2x you see in the chart understates the real impact.

3/ The tools that actually moved the needle
We tried everything, but in the end we have 2 winners. Claude Code, and Super.
Our dev team is a huge fan and use it in tandem with Super MCP to get company context about bugs and more context right in their coding workflow. No opening Slack.

It saves time, it makes everyone more happy that they get to do more of the work they deem important for them to cognitively engage with.

$24k would feel like a lot for any other tool.
But for the impact, it's the best money we spent all year.

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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);}Hugo Pereira's LinkedIn Performance

Performance ScoreChristophe Pasquier's LinkedIn Performance

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Performance ScoreHugo Pereira's LinkedIn Performance