Ritmoo

Ritmoo helps fast-growing companies turn ambition into execution. Through strategic design, leadership workshops, and simple goal execution software, Ritmoo partners with leadership teams to clarify priorities, align on strategy, and build execution habits that stick.

We combine expert-led services with lightweight goal management software built on the NCT framework, which is ideal for teams that want clarity without the bloat of rigid OKRs.

Ritmoo has delivered fractional leadership across growth, marketing, GTM, and technology for companies like CLEVR, Software Improvement Group (SIG), Frends, vaylens, and Bnewable. 

We've also run high-impact programs for scaleups like Skytree, IECharge, Dott, Lightly.ai, ELP Network, Incision, and enterprise teams at ING and Tele2.

Co-Founder

Frends iPaaS

The European iPaaS built for mission-critical automation and loved for its usability. Frends iPaaS connects your systems, automates every business process, and gives you full visibility into your workflows. 

Frends iPaaS is a platform that offers tools to integrate applications in the compliant cloud, hybrid, and on-premises. With Frends, businesses can build integrations, automated processes, and APIs in BPMN 2.0-based Low-Code, which reduces costs in development, documentation, and management. Frends is made for BizDevOp teams and enables team collaboration.

Currently leading the GTM strategy and Marketing organization.

Fractional CMO

Angel investor in Pal, digital palliative home care solutions for families affected by life-limiting illnesses.

Private Investor

StayingBee

StayingBee is a community-driven accommodation sharing platform that connects you with trusted hosts from communities you already belong to, turning every trip into a meaningful experience, not just a booking.

It's almost like Couchsurfing meets Airbnb, but strictly for communities, like AIESEC, unlocking an untapped layer of the $400B+ alternative accommodation market.

In just a few months, the team has:
- Grown to 4,000+ users across 90+ countries.
- Hosted 100+ nights booked and listed 200+ homes.
- Launched pilots with the AIESEC community and generated revenue.
- Signed partnerships with global communities, including AIESEC International.
- Expanded into the startup ecosystem, with SLUSH as an official partner.

I'm part of their Supervisory & Management Board.

Board Member

Stolp

Break with the habit of always on, always connected. Stolp designs solutions and experiences that encourage daily moments to disconnect and spend time on what really matters.

Shilling

Shilling is a leading €30M early-stage VC in Portugal. Shilling invests in a wide range of verticals and seeks out the biggest opportunities across all B2B and consumer categories. Leveraging the concept of Founder LPs, Shilling brings much more than capital and offers through its Shilling Platform, direct access to successful founders and executives of leading companies. 

This platform supports entrepreneurs in validating and developing their ventures, which then accelerate their growth into global markets. I'm one of the Founder LP and investors into the fund.

Founder LP

vaylens

vaylens is an EV charging management software for businesses to manage and monetise their EV chargers. Making it as easy as possible for companies of any size to integrate electric mobility into their long-term success, vaylens is on a mission to make electric driving accessible to all. vaylens is based in Dortmund and is part of the KOSTAL Group.

Led interim marketing (replacing Head of Marketing during maternity leave), supporting brand launches in the UK and France, re-engineering revenue operations, and setting the 2025 marketing strategy.

Software Improvement Group

Software Improvement Group (SIG) leads in traditional and AI software quality assurance. Empowering organizations to become more resilient and agile by guiding them to enhance their software quality and security through deep source code analysis and tailored, strategic advice.  

As interim marketing & GTM lead, helped transition to a product-led business, revamped demand generation, evolved Revenue Operations, and launched the flagship event Scope. This led to a 40% YoY pipeline increase and a 20% growth YoY in closed ARR revenue.

Fractional GTM & Marketing Lead

CLEVR

CLEVR delivers digital transformation at scale by implementing Siemens and Mendix solutions to serve industries like manufacturing, retail, energy, and more. 

During this fractional service, I've designed the positioning strategy, revised GTM market approach built on partner-led growth and led (interim) the GTM and Marketing teams, resulting in a 100% pipeline increase and supporting the transition from loss-making to profit-making business.

Fractional CMO & GTM

IECharge

IECharge® is a high power electric vehicle charging solution developed by NW Group, first french unicorn in the energy transition. Advisory was focused on setting up the first Marketing & GTM foundation from website, communication, and approach to customers.

Advisory

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 culture of growth.

Today, I’m the co-founder of Ritmoo, where we combine expert-led leadership & strategy design services with simple, lightweight goal software — built for fast-moving teams that want strategic clarity without the bloat of OKRs. Our work spans scaleups, mid-sized companies, and enterprise teams across growth, marketing, GTM, and leadership transformation.

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

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

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🚀 Highlights summary
- Co-founder of Ritmoo | Goal software + leadership programs for strategic clarity and execution
- Fractional Growth Operator | Supporting scaleups like SIG, CLEVR, Frends, Dott, vaylens, and more
- 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 org
- Angel Investor & LP | Backing early-stage founders via Stolp, Pal, and Shilling VC
- Writer | Teams in Hell (June 2025), exploring how to fix modern leadership from the inside out

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

Hugo Pereira

Your best people are falling behind. 
And you're letting it happen.

Here's the truth about AI adoption: the biggest threat isn't the technology. It's your best performers who think they don't need to adapt.

We love to talk about AI in absolutes. 
You're either all-in or you're a dinosaur. 
You're disrupting or being disrupted.

Non-sense.

The real question isn't whether your team uses AI. It's what kind of learning you're enabling, and whether you're creating the conditions for progress.

𝗦𝘁𝗼𝗽 𝘄𝗮𝗶𝘁𝗶𝗻𝗴 𝗳𝗼𝗿 𝗽𝗲𝗿𝗳𝗲𝗰𝘁𝗶𝗼𝗻. 𝗦𝘁𝗮𝗿𝘁 𝗯𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝗺𝗼𝗺𝗲𝗻𝘁𝘂𝗺.

Last week, as part of my fractional work with Frends, we did something simple but powerful. We blocked out half a day, a Friday morning, for what we called a "Data & AI Deep Work Session."

Every team member picked one of three paths:

1. Learn and build an AI workflow
2. Test AI tools in their actual work
3. Extract data insights OR document a key process 

No pressure to master everything. 
No mandate to become an AI expert overnight. 
Just deliberate practice and learning.

𝗛𝗲𝗿𝗲'𝗿𝗲 𝘀𝗼𝗺𝗲 𝗼𝗳 𝘁𝗵𝗲 𝗮𝗰𝘁𝘂𝗮𝗹 𝗿𝗲𝘀𝘂𝗹𝘁𝘀:

- The social media intern built a workflow to analyze monthly results and spot patterns. Half a day. Done.
- The lead content person created a system that processes industry news and drafts weekly articles. We published the first one. It was good.
- The B2B demand gen marketer dug into website traffic data and found 2 things we'd completely missed. We reprioritized the roadmap quickly afterwards.

𝗔𝗻𝗱 𝗵𝗲𝗿𝗲'𝘀 𝘁𝗵𝗲 𝗯𝗲𝘀𝘁 𝗽𝗮𝗿𝘁: this is a company that sells an enterprise-grade integration and workflow automation platform.

The easy route would have been for marketers to go with n8n or Zapier. Instead, the mandate was to work with our own product, even if technically tougher.

Now they understand better what they're selling. They speak closer to the language of their customers. 

That's not just AI adoption. That's commercial advantage.

𝗠𝗮𝗸𝗲 𝘁𝗵𝗶𝘀 𝗮 𝗿𝗵𝘆𝘁𝗵𝗺, 𝗻𝗼𝘁 𝗮𝗻 𝗲𝘃𝗲𝗻𝘁.

Once a month. 
Bimonthly. 
Quarterly. 

Pick your pace based on your reality, not some guru's playbook.

The teams that win aren't the ones going all-in on day one.  They're the ones building adaptability into their operating system.

Your best performers got there by learning faster than everyone else. Don't let comfort kill that edge.

---

I’m Hugo Pereira, co-founder of Ritmoo and fractional growth operator. I’ve led companies from €1M to €100M+ while building purpose-driven, resilient teams.

Follow me for unfiltered takes on growth, leadership, and scaling what matters. My book 𝘛𝘦𝘢𝘮𝘴 𝘪𝘯 𝘏𝘦𝘭𝘭 – 𝘏𝘰𝘸 𝘵𝘰 𝘌𝘯𝘥 𝘉𝘢𝘥 𝘔𝘢𝘯𝘢𝘨𝘦𝘮𝘦𝘯𝘵 is out now on Amazon.

Fractional Growth (CMO/CGO) | Co-founder @Ritmoo | Author “Teams in Hell – How to End Bad Management”

If Series A feels hard, then Series B will break you.

I've recently had small advisory sessions with 3 scaleups in B2B SaaS, who are struggling at this exact stage.

Here's my view on why this is a tougher Series than the previous one:

At Series A, you're proving the idea works. 
At Series B, you're proving the company works.

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𝗪𝗵𝗮𝘁 𝗯𝗿𝗲𝗮𝗸𝘀 𝗯𝗲𝘁𝘄𝗲𝗲𝗻 𝗦𝗲𝗿𝗶𝗲𝘀 𝗔 𝗮𝗻𝗱 𝗦𝗲𝗿𝗶𝗲𝘀 𝗕:

→ 𝗬𝗼𝘂𝗿 𝗳𝗼𝘂𝗻𝗱𝗶𝗻𝗴 𝘁𝗲𝗮𝗺
Scrappy generalists can't scale you forward.

→ 𝗬𝗼𝘂𝗿 𝗽𝗿𝗼𝗰𝗲𝘀𝘀𝗲𝘀 
What worked for 20 people creates chaos at 100.

→ 𝗬𝗼𝘂𝗿 𝗰𝘂𝗹𝘁𝘂𝗿𝗲
"We're a family" dies when you're hiring 10 ppl / month. 

→ 𝗬𝗼𝘂𝗿 𝘂𝗻𝗶𝘁 𝗲𝗰𝗼𝗻𝗼𝗺𝗶𝗰𝘀 
Investors want sustainable growth, not just growth.

→ 𝗬𝗼𝘂𝗿 𝗺𝗮𝗿𝗸𝗲𝘁 𝗽𝗼𝘀𝗶𝘁𝗶𝗼𝗻𝗶𝗻𝗴
Competitors now take you seriously.

---

To add to the above, these are other implications to consider:

𝟭. 𝗖𝗮𝗽𝗶𝘁𝗮𝗹 𝗶𝘀 𝗲𝘅𝗽𝗲𝗻𝘀𝗶𝘃𝗲 𝗮𝗴𝗮𝗶𝗻 
Series A investors threw money at potential. Series B investors want proof of capital efficiency, so your previous high burn-rate won't do good any longer.

𝟮. 𝗔𝗜 𝗶𝘀 𝗰𝗼𝗺𝗽𝗿𝗲𝘀𝘀𝗶𝗻𝗴 𝗰𝗼𝗺𝗽𝗲𝘁𝗶𝘁𝗶𝘃𝗲 𝗮𝗱𝘃𝗮𝗻𝘁𝗮𝗴𝗲𝘀 
That product moat you built? Your competitor just replicated it with AI in 3 months. Defensibility is harder to prove.

𝟯. 𝗧𝗮𝗹𝗲𝗻𝘁 𝗶𝘀 𝗽𝗶𝗰𝗸𝗶𝗲𝗿 
The "join a rocket ship" pitch doesn't work when layoffs are everywhere. Series B hiring is a war, not a hunt.

𝟰. 𝗢𝗽𝗲𝗿𝗮𝘁𝗶𝗼𝗻𝗮𝗹 𝗱𝗲𝗯𝘁 𝗰𝗼𝗺𝗽𝗼𝘂𝗻𝗱𝘀 𝗳𝗮𝘀𝘁𝗲𝗿 
Every shortcut you took at Series A (messy data, duct-tape workflows, financial agility to prove some 'made-up ARR') now costs 10x to resolve.

---

From seeing the best companies succeeding at Series B, I find that they might have the below in common:

→ 𝗧𝗵𝗲𝘆 𝗼𝗯𝘀𝗲𝘀𝘀 𝗼𝘃𝗲𝗿 𝘂𝗻𝗶𝘁 𝗲𝗰𝗼𝗻𝗼𝗺𝗶𝗰𝘀 
Revenue growth without efficiency is a death sentence now.

→ 𝗧𝗵𝗲𝘆 𝗯𝘂𝗶𝗹𝗱 𝗿𝗲𝗮𝗹 𝘀𝘆𝘀𝘁𝗲𝗺𝘀
Not more tools. Systems for decisions, accountability, and execution.

→ 𝗧𝗵𝗲𝘆 𝗽𝗿𝗶𝗼𝗿𝗶𝘁𝗶𝘇𝗲 𝗿𝘂𝘁𝗵𝗹𝗲𝘀𝘀𝗹𝘆 
With so much going on, the ability to communicate clearly what matters and don't is critical for speed of execution.

→ 𝗧𝗵𝗲𝘆 𝗳𝗶𝗿𝗲/𝗿𝗲𝗽𝗹𝗮𝗰𝗲 𝗳𝗮𝘀𝘁 
This isn't popular, but many early team members can't scale any longer (hardest decision, most important).

---

Series A forgives mistakes. 
Series B punishes them.

Most founders aren't ready for that shift. 
But again, many learn from it and grow to do even better later on.
---

I'm Hugo Pereira, co-founder of Ritmoo and fractional growth operator. I've led companies from €1M to €100M+ while building purpose-driven, resilient teams.

Follow me for unfiltered takes on growth, leadership, and scaling what matters. My book 𝘛𝘦𝘢𝘮𝘴 𝘪𝘯 𝘏𝘦𝘭𝘭 – 𝘏𝘰𝘸 𝘵𝘰 𝘌𝘯𝘥 𝘉𝘢𝘥 𝘔𝘢𝘯𝘢𝘨𝘦𝘮𝘦𝘯𝘵 is out now on Amazon.

At one of the early stage startups I worked for, we hired a VP of Sales too early that nearly destroyed our whole sales motion.

Not because the person was bad, but because the company wasn't ready.

I've watched startups make the same hiring mistakes over and over: burning cash, killing momentum, and creating org debt that takes years to fix.

These are the most common hires that kill startups:

𝟭. 𝗧𝗵𝗲 "𝗲𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲𝗱 𝗲𝘅𝗲𝗰" 𝘁𝗼𝗼 𝗲𝗮𝗿𝗹𝘆
You just raised Series A. 
Revenue is €2m ARR. 
You're at 15 people.

Your investors tell you: "Hire a VP of Sales from a unicorn.", so you do.

You pay €180k + equity. 
They have an impressive resume. 
They've managed teams of 50+.

What happens: 
→ They try to build the org they had previously 
→ They want a team, budget, and tools you can't afford 
→ They're used to running plays, not inventing them 
→ They leave in 9 months. You've burned €200k+.

The reality: Senior execs from big companies often can't operate in early-stage chaos.

𝟮. 𝗧𝗵𝗲 "𝗰𝘂𝗹𝘁𝘂𝗿𝗲 𝗳𝗶𝘁" 𝘄𝗵𝗼 𝗰𝗮𝗻'𝘁 𝗲𝘅𝗲𝗰𝘂𝘁𝗲
You're scaling. 
You interview a candidate who loves your mission, says all the right things.
You hire them because "culture is everything."

What happens: 
→ They're great in meetings but can't ship 
→ They talk strategy but avoid execution 
→ They're well-liked but not effective

The reality: Culture fit without execution is just an expensive friend.

𝟯. 𝗧𝗵𝗲 "𝘄𝗲'𝗹𝗹 𝗴𝗿𝗼𝘄 𝗶𝗻𝘁𝗼 𝘁𝗵𝗲𝗺" 𝗵𝗶𝗿𝗲
You need a senior engineer. 
You interview someone amazing, they're at a FAANG company making €250k. 
You can offer €120k + equity.
They say yes. You think: "We got lucky!"

What happens: 
→ They expect resources and processes you don't have 
→ They're frustrated by the lack of infrastructure 
→ They miss their old job's stability 
→ They leave in 6 months

The reality: Overqualified hires often regret the trade-off.

𝗪𝗵𝗮𝘁 𝗴𝗿𝗲𝗮𝘁 𝘀𝘁𝗮𝗿𝘁𝘂𝗽 𝗵𝗶𝗿𝗶𝗻𝗴 𝗹𝗼𝗼𝗸𝘀 𝗹𝗶𝗸𝗲:
1. Hire for the now, not the future. Get someone who can execute in your current chaos with potential to grow 
2. Prioritize learning velocity over experience. Adaptable beats polished in early stage
3. Avoid the "brand name" trap. A VP from Salesforce isn't automatically your answer

The best hires I've seen were sometimes underqualified on paper, but overperformed because they matched the company's reality, not its aspirations.

Before your next senior hire, ask: 
→ Can this person operate with our current constraints? 
→ Are they energized by ambiguity or paralyzed by it? 
→ Are we hiring for the company we are or the company we wish we were?

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I'm Hugo Pereira, co-founder of Ritmoo and fractional growth operator. I've led companies from €1M to €100M+ while building purpose-driven, resilient teams.

Follow me for unfiltered takes on growth, leadership, and scaling what matters. My book 𝘛𝘦𝘢𝘮𝘴 𝘪𝘯 𝘏𝘦𝘭𝘭 – 𝘏𝘰𝘸 𝘵𝘰 𝘌𝘯𝘥 𝘉𝘢𝘥 𝘔𝘢𝘯𝘢𝘨𝘦𝘮𝘦𝘯𝘵 is out now on Amazon.

Don't outsource your critical thinking. 
You'll need it, with or without AI.
AI won't save you from lazy judgment.

Busy work is the real workplace enemy.
It's high intensity but low impact. 

It creates the illusion of productivity while delivering zero real results. 

People feel good about it because it makes them think they're doing something real. But they're not.

Teams running at full speed, meetings back-to-back, Slack constantly buzzing, everyone claiming they're swamped. 

But when you look at the results, chances are that nothing meaningful is getting done.

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A mindset shift is required, for deep work to happen:

𝗦𝗵𝗶𝗳𝘁 𝟭: 𝗙𝗿𝗼𝗺 "𝗔𝗰𝘁𝗶𝘃𝗶𝘁𝘆 = 𝗣𝗿𝗼𝗴𝗿𝗲𝘀𝘀" → 𝗢𝘂𝘁𝗰𝗼𝗺𝗲𝘀 𝗼𝘃𝗲𝗿 𝗼𝘂𝘁𝗽𝘂𝘁𝘀 
Stop measuring how much people are doing. Start measuring what actually moves the needle. Deep work isn't about volume. It's about impact combined with intensity.

𝗦𝗵𝗶𝗳𝘁 𝟮: 𝗙𝗿𝗼𝗺 "𝗠𝘂𝗹𝘁𝗶𝘁𝗮𝘀𝗸𝗶𝗻𝗴 𝗶𝘀 𝗲𝗳𝗳𝗶𝗰𝗶𝗲𝗻𝘁" → 𝗖𝗼𝗻𝘁𝗲𝘅𝘁 𝘀𝘄𝗶𝘁𝗰𝗵𝗶𝗻𝗴 𝗸𝗶𝗹𝗹𝘀 𝗽𝗿𝗼𝗴𝗿𝗲𝘀𝘀 
Every time you jump between tasks, you lose focus. Deep work requires sustained attention on high-impact tasks. Multitasking doesn't make you faster. It makes you slower and less effective.

𝗦𝗵𝗶𝗳𝘁 𝟯: 𝗙𝗿𝗼𝗺 "𝗖𝗼𝗹𝗹𝗮𝗯𝗼𝗿𝗮𝘁𝗶𝗼𝗻 𝗺𝗲𝗮𝗻𝘀 𝗰𝗼𝗻𝘀𝘁𝗮𝗻𝘁 𝗰𝗼𝗺𝗺𝘂𝗻𝗶𝗰𝗮𝘁𝗶𝗼𝗻" → 𝗦𝗶𝗹𝗲𝗻𝗰𝗲 𝗰𝗮𝗻 𝗯𝗲 𝘀𝗮𝗰𝗿𝗲𝗱 
Early in my career, while at AIESEC International, we had three hours of complete silence every morning. No meetings. No interruptions. Just deep work. It wasn't mandated, people protected it because they understood its value. That's when transformative work happened.

𝗦𝗵𝗶𝗳𝘁 𝟰: 𝗙𝗿𝗼𝗺 "𝗨𝗿𝗴𝗲𝗻𝘁 𝗮𝗹𝘄𝗮𝘆𝘀 𝘄𝗶𝗻𝘀" → 𝗛𝗶𝗴𝗵-𝗶𝗺𝗽𝗮𝗰𝘁 𝗯𝗲𝗮𝘁𝘀 𝗵𝗶𝗴𝗵-𝗶𝗻𝘁𝗲𝗻𝘀𝗶𝘁𝘆 
Urgent feels important. But urgent rarely moves the company forward. Deep work focuses on high-impact tasks that actually matter, even when they're not screaming for attention.

𝗦𝗵𝗶𝗳𝘁 𝟱: 𝗙𝗿𝗼𝗺 "𝗥𝗲𝗺𝗼𝘁𝗲 = 𝗺𝗼𝗿𝗲 𝗺𝗲𝗲𝘁𝗶𝗻𝗴𝘀" → 𝗔𝘀𝘆𝗻𝗰 𝘂𝗽𝗱𝗮𝘁𝗲𝘀, 𝘀𝘆𝗻𝗰 𝗳𝗼𝗿 𝗱𝗲𝗰𝗶𝘀𝗶𝗼𝗻𝘀 
When Covid hit, we eliminated countless meetings and shifted to async updates. We created time-blocked deep work sessions, where everyone worked silently together. It probably saved the team mental health.

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The path from busy work to deep work starts with one decision: 𝗽𝗿𝗼𝘁𝗲𝗰𝘁 𝘆𝗼𝘂𝗿 𝘁𝗲𝗮𝗺'𝘀 𝗳𝗼𝗰𝘂𝘀 𝘁𝗶𝗺𝗲.

Create meeting-free zones. 
Define clear deliverables. 
Celebrate focused achievements.

Your team doesn't need more hours. 
They need fewer distractions and clearer priorities.

The diamond is there. 
Stop digging for pebbles.

---

I’m Hugo Pereira, co-founder of Ritmoo and fractional growth operator. I’ve led companies from €1M to €100M+ while building purpose-driven, resilient teams.

Follow me for unfiltered takes on growth, leadership, and scaling what matters. My book 𝘛𝘦𝘢𝘮𝘴 𝘪𝘯 𝘏𝘦𝘭𝘭 – 𝘏𝘰𝘸 𝘵𝘰 𝘌𝘯𝘥 𝘉𝘢𝘥 𝘔𝘢𝘯𝘢𝘨𝘦𝘮𝘦𝘯𝘵 is out now on Amazon.

Many leaders still see vulnerability as weakness.
I've seen it happen over and over. 

Leaders resist vulnerability because they think it means encouraging weakness. So, they build cultures where people are scared to speak up when they need help.

The result is teams that hide problems instead of solving them. Here are 5 myths about trust that keep teams stuck:

𝗠𝘆𝘁𝗵 𝟭: 𝗩𝘂𝗹𝗻𝗲𝗿𝗮𝗯𝗶𝗹𝗶𝘁𝘆 = 𝗪𝗲𝗮𝗸𝗻𝗲𝘀𝘀 
Wrong. When someone admits they're struggling with a deadline or need support, that's not weakness. That's courage. Teams that support vulnerability get stronger. Teams that punish it fall apart.

𝗠𝘆𝘁𝗵 𝟮: 𝗛𝗶𝗴𝗵 𝘁𝘂𝗿𝗻𝗼𝘃𝗲𝗿 𝗶𝘀 𝗮 𝗰𝗼𝗺𝗽𝗲𝗻𝘀𝗮𝘁𝗶𝗼𝗻 𝗶𝘀𝘀𝘂𝗲 
Most times, It's not. People don't leave because of money. They leave because of low trust. When trust is missing, everything else falls apart, including retention. Fix the trust problem, not just the salary.

𝗠𝘆𝘁𝗵 𝟯: 𝗧𝗿𝗮𝗻𝘀𝗽𝗮𝗿𝗲𝗻𝗰𝘆 𝗺𝗲𝗮𝗻𝘀 𝘁𝗲𝗹𝗹𝗶𝗻𝗴 𝗲𝘃𝗲𝗿𝘆𝗼𝗻𝗲 𝗲𝘃𝗲𝗿𝘆𝘁𝗵𝗶𝗻𝗴 
It doesn't. When EVBox's IPO was delayed, we couldn't share why for legal reasons. I acknowledged with the team what we couldn't say and why. Transparency isn't always about full disclosure. It's about honest communication within boundaries.

𝗠𝘆𝘁𝗵 𝟰: 𝗣𝗿𝗼𝗯𝗹𝗲𝗺𝘀 𝗱𝗶𝘀𝗮𝗽𝗽𝗲𝗮𝗿 𝗶𝗳 𝘆𝗼𝘂 𝗱𝗼𝗻'𝘁 𝘁𝗮𝗹𝗸 𝗮𝗯𝗼𝘂𝘁 𝘁𝗵𝗲𝗺 
They multiply. When people hide overwhelm or burnout, you end up with high turnover and absenteeism. I've watched businesses fail because employees weren't comfortable speaking up.

𝗠𝘆𝘁𝗵 𝟱: 𝗦𝘁𝗿𝗼𝗻𝗴 𝗹𝗲𝗮𝗱𝗲𝗿𝘀 𝗻𝗲𝘃𝗲𝗿 𝗻𝗲𝗲𝗱 𝗵𝗲𝗹𝗽 
The opposite is true. Leaders who can't express vulnerability can't get help when they need it most. Their teams learn to hide problems too.

-

Low-trust cultures don't protect teams. 
They break them.

The role of a leader isn't just to execute strategy. It's to create an environment where people trust each other enough to do their best work.

When trust is high, teams take risks, make decisions, and admit mistakes without fear. 

When trust is low, hesitation and politicking take over.

𝘕𝘰𝘸, 𝘺𝘰𝘶 𝘮𝘪𝘨𝘩𝘵 𝘣𝘦 𝘸𝘰𝘯𝘥𝘦𝘳𝘪𝘯𝘨, 𝘩𝘰𝘸 𝘤𝘢𝘯 𝘐 𝘢𝘤𝘵 𝘰𝘯 𝘵𝘩𝘪𝘴?

Start small. Pick one component that could improve trust on your team. 𝗔𝗻𝗱 𝘁𝗮𝗸𝗲 𝗮𝗰𝘁𝗶𝗼𝗻 𝘁𝗼𝗱𝗮𝘆.

---

I’m Hugo Pereira, co-founder of Ritmoo and fractional growth operator. I’ve led companies from €1M to €100M+ while building purpose-driven, resilient teams.

Follow me for unfiltered takes on growth, leadership, and scaling what matters. My book 𝘛𝘦𝘢𝘮𝘴 𝘪𝘯 𝘏𝘦𝘭𝘭 – 𝘏𝘰𝘸 𝘵𝘰 𝘌𝘯𝘥 𝘉𝘢𝘥 𝘔𝘢𝘯𝘢𝘨𝘦𝘮𝘦𝘯𝘵 is out now on Amazon.

Language translation when expanding to new markets, especially in Europe, simply isn't enough.

I just sat down with Nicola Calabrese on the Multilingual Content Podcast to talk about something most companies get wrong when expanding internationally. 𝘗𝘚: 𝘓𝘪𝘯𝘬 𝘵𝘰 𝘵𝘩𝘦 𝘱𝘰𝘥𝘤𝘢𝘴𝘵 𝘪𝘯 𝘵𝘩𝘦 𝘤𝘰𝘮𝘮𝘦𝘯𝘵 𝘴𝘦𝘤𝘵𝘪𝘰𝘯.

They think cultural differences = translation.
They're not.

Culture shapes how people make decisions, perceive value, and what trust even means.

Here's what actually matters when you go global: 
𝗧𝗵𝗲 𝗺𝗮𝗿𝗸𝗲𝘁 𝘁𝗲𝘀𝘁𝘀 𝘆𝗼𝘂𝗿 𝗽𝗿𝗼𝗱𝘂𝗰𝘁. 𝗘𝘅𝗽𝗮𝗻𝘀𝗶𝗼𝗻 𝘁𝗲𝘀𝘁𝘀 𝘆𝗼𝘂𝗿 𝗽𝗲𝗼𝗽𝗹𝗲.

At EVBox, we learned this the hard way across Europe:
• Netherlands: sustainability drove buying decisions
• Germany: engineering specs came first
• UK: convenience and future-proofing mattered most

Same product. 
Completely different customer journeys.

--

𝗙𝗶𝘃𝗲 𝗚𝗧𝗠 𝗽𝗿𝗶𝗻𝗰𝗶𝗽𝗹𝗲𝘀 𝗳𝗼𝗿 𝗲𝗻𝘁𝗲𝗿𝗶𝗻𝗴 𝗮 𝗻𝗲𝘄 𝗺𝗮𝗿𝗸𝗲𝘁:
1. Nail product-market fit in your home market first 
2. Look for demand signals (inbound requests, competitor activity) 
3. Build infrastructure to support properly (local partners, someone on the ground) 
4. Have resources and attention to give it a real chance 
5. Understand the regulatory landscape upfront

𝗢𝗻 𝗔𝗜 𝗮𝗻𝗱 𝗺𝘂𝗹𝘁𝗶𝗹𝗶𝗻𝗴𝘂𝗮𝗹 𝗲𝗻𝗴𝗮𝗴𝗲𝗺𝗲𝗻𝘁:
For Frends, we recently added a conversational AI experience right at the start of the homepage instead of standard CTA buttons (not a rigid chatbot with rules, but an AI that was trained on over 7000 questions). 

In less than three months = 500+ unique conversations. People aren't just navigating websites anymore. They're want to have conversations.

We trained the model to answer in Swedish if you write in Swedish, German if you write in German. The content? All in English. The AI adapts.

But here's one issue: AI understands patterns, not culture. Humor that works in the US can fall flat in Germany. Directness that's normal in the Netherlands can feel rude elsewhere.

And the other issue: AI still hallucinates. Even with a lot of trained data, it still gives wrong answers from time to time and doesn't adapt quickly enough to new information that replaces old one.

The solution for now is to keep humans in the loop. 
Audit weekly. 
Stay hybrid.

--

I'm 𝗛𝘂𝗴𝗼 𝗣𝗲𝗿𝗲𝗶𝗿𝗮, co-founder of Ritmoo and fractional growth operator. I've led companies from €1M to €100M+ while building purpose-driven, resilient teams.

Follow me for unfiltered takes on growth, leadership, and scaling what matters. My book 𝘛𝘦𝘢𝘮𝘴 𝘪𝘯 𝘏𝘦𝘭𝘭 – 𝘏𝘰𝘸 𝘵𝘰 𝘌𝘯𝘥 𝘉𝘢𝘥 𝘔𝘢𝘯𝘢𝘨𝘦𝘮𝘦𝘯𝘵 is out now on Amazon.

I've seen dozens of companies fail at OKRs.
Same pattern every time.

The CEO stops logging into the tool by week 3.
Not because they're lazy. 
Not because they're too busy.

Because deep down, they know the truth:
𝗠𝗼𝘀𝘁 𝗢𝗞𝗥 𝗶𝗺𝗽𝗹𝗲𝗺𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻𝘀 𝗮𝗿𝗲 𝘁𝗵𝗲𝗮𝘁𝗲𝗿.

Here's what I see in every company that fails at goal-setting:

→ Goals are set in a 2-day offsite with post-its and tons of coffee 
→ Everyone nods excited about "ambitious but achievable" targets 
→ The goals get entered into whatever tool the VP bought last quarter 
→ Week 1: People update their progress religiously
→ Week 3: Updates become sloppy (probably even written by AI by now) 
→ Week 6: The CEO hasn't logged in since the kickoff 
→ Quarter-end: Everyone rushing to update everything before the board meeting

The tool isn't the problem.
𝗧𝗵𝗲 𝗽𝗿𝗼𝗯𝗹𝗲𝗺 𝗶𝘀 𝗹𝗮𝗰𝗸 𝗼𝗳 𝗮𝗹𝗶𝗴𝗻𝗺𝗲𝗻𝘁 𝗮𝗻𝗱 𝗰𝗹𝗮𝗿𝗶𝘁𝘆 𝗼𝗻 𝘄𝗵𝘆 𝘁𝗵𝗶𝘀 𝗺𝗮𝘁𝘁𝗲𝗿𝘀.

When goals are disconnected from daily work, when they're written to impress investors instead of guide decisions, when they're too many or too vague, people smell it immediately.

And the CEO stops logging in because facing that disconnect is painful.

But here's what most companies miss entirely:
𝗢𝗞𝗥𝘀 𝗮𝗹𝗺𝗼𝘀𝘁 𝗻𝗲𝘃𝗲𝗿 𝗱𝗶𝘀𝗰𝘂𝘀𝘀 𝘁𝗵𝗲 "𝗵𝗼𝘄" 𝗼𝗿 𝗮𝗹𝗶𝗴𝗻 𝗼𝗻 𝘀𝘁𝗿𝗮𝘁𝗲𝗴𝗶𝗰 𝗯𝗲𝘁𝘀.

Everyone agrees on the "what" (grow revenue 3x, reduce churn, expand to X region). But then nobody aligns on: 

→ Which bets we're making to get there 
→ What we're saying no to 
→ How we're sequencing the work 
→ What trade-offs we're willing to accept

So teams pick their own interpretation of "how" and wonder why nothing connects.

Leaders massively underestimate how much alignment is required. 

They think setting goals = creating alignment. Well it doesn't.

Goals without shared understanding of the path forward are just wishful thinking with a deadline.

I've worked with companies from all growth stages. The ones that actually achieve their goals have three things in common:

→ 𝗙𝗲𝘄𝗲𝗿 𝗴𝗼𝗮𝗹𝘀 (3-5 company-level max, not 47 cascaded nightmares) 
→ 𝗥𝗲𝗮𝗹 𝗮𝗹𝗶𝗴𝗻𝗺𝗲𝗻𝘁 𝗼𝗻 𝘀𝘁𝗿𝗮𝘁𝗲𝗴𝗶𝗰 𝗯𝗲𝘁𝘀 (not just the goal, but how we'll get there) 
→ 𝗗𝗮𝗶𝗹𝘆 𝗿𝗲𝗹𝗲𝘃𝗮𝗻𝗰𝗲 (teams reference goals in real decisions, not quarterly reviews)

Your OKR tool is probably fine.
Your alignment on the "how"? That's what's missing.

If your CEO isn't in the tool, it's not a software problem.

It's a belief and alignment problem, disguised as a goal-setting problem.

---

I'm Hugo Pereira, co-founder of Ritmoo and fractional growth operator. I've led companies from €1M to €100M+ while building purpose-driven, resilient teams.

Follow me for unfiltered takes on growth, leadership, and scaling what matters. My book 𝘛𝘦𝘢𝘮𝘴 𝘪𝘯 𝘏𝘦𝘭𝘭 – 𝘏𝘰𝘸 𝘵𝘰 𝘌𝘯𝘥 𝘉𝘢𝘥 𝘔𝘢𝘯𝘢𝘨𝘦𝘮𝘦𝘯𝘵 is out now on Amazon.

super.work

Super is your team ultimate AI search engine and assistant, based on all company data.

Founder

Slite

Founder and CEO 🛰

Staffit

Launched in college, Staffit let recruiters without technical skills assessing their candidates.
We were offering proper tests based on projects, rated with peer assessments (candidates reviewing each others in a controlled manner).

Co-founder

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

Currently hard at work building Super 🔥

Super is our ultimate AI search and assistant. It plugs to your company data and comes with the recipes and tools for your team to get instant benefit from AI at work
 👉 super.work


And of course we keep growing Slite! 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

OpenAI's top 30 customers list got leaked?
And by the way things look like
SaaS competition is going to be BRUTAL 

Look at who's consuming the most tokens: Notion, Salesforce, HubSpot, Zendesk, Shopify, JetBrains. These aren't simple products. Far from it. They're the most complex, feature-rich platforms in their categories. They've spent years adding features, building depth, creating power. And in doing so, they created a massive problem: 

Their products became too complex for most users to navigate.
AI is their answer to that problem.

Eg: Salesforce has thousands of features across dozens of modules. Most users touch maybe 5% of what they're paying for. But with AI, you can just ask "show me all deals likely to close this quarter" instead of building a custom report.
Same with Notion. Same with HubSpot. AI becomes the interface that makes complexity accessible.

At Slite and super.work, we've got our hats in the ring too. Knowledge management tools have historically struggled because finding the right information means navigating structured and unstructured data from ALL your apps. We made Slite into the best Knowledge Base but Super will actually solve the information asymmetry problem.

If you're building software today, you're automatically in the AI business now. It doesn't matter if you're in productivity, dev tools, legal, healthcare, e-commerce. AI isn't a feature category anymore. It's infrastructure.

The companies on this list figured that out.

CEO at slite (W18) & super.work | Deep AI search & agents connected to all your work apps

Every knowledge base sells you on centralizing everything.
Then you realize your docs can't answer half your team's actual questions.
We spent 8 years building Slite before accepting this.

Let's say your documentation is perfect with every tag, folder, and doc.
But then someone asks "why did this customer churn?" and you're suddenly opening Intercom, Slack, and HubSpot because the answer lives across all three.
Good questions will always need good context. That's why we built Super.

Slite gives you verified, official documentation. Super finds everything else.
For a year, we sold them separately. Watched teams buy both because they needed both.

So here's the Knowledge Suite.
Slite at $10/user/month. Super at $15/user/month.
Together: $20/user/month.

You're getting both for less than competitors charge for one mediocre product.

Companies are choosing the suite it because fighting reality is exhausting. Your knowledge will always live in multiple places. The suite lets you stop pretending otherwise.

Document what should be official in Slite. Search everything that exists with Super.

If you're tired of choosing between perfect docs and complete context, book a demo. 👉 https://lnkd.in/eSwiyTjp

The lost prospect that pissed me off the most?
A French fintech company we'd been courting for months.
Perfect fit on paper, great logo to have, their team was excited about everything we built. Then at the last minute they chose our biggest competitor.

All because our competitor was selling Kanban boards + databases + project management + wikis.

I realized that the leads we were getting wanted an all-in-one solution and couldn't tell the difference between a standard all-in-one and Slite. But Slite had always been opinionated about just being a great knowledge base, but somehow our leads had hesitations because they wanted more.

The answer wasn't to ship more features and catch up to our competitors. That would lose our opinionated feature set of being decluttered and beautiful. We needed to communicate more clearly about who we were.

We chose our lane and repositioned fast. Instead of competing on breadth, we doubled down on being the best knowledge management tool that actually works. We focused on speed, search quality, and AI-powered assistance.

The pivot accelerated our growth. Once we clearly stated that we were for teams who cared about having the best documentation app, the magic happened.

Prospects started choosing us because we solved their specific problem better than anyone else. We still kept getting prospects that wanted an all-in-one, but the new positioning and messaging let them self-disqualify and saved the pressure on our sales team of trying to sell to customers that never wanted something like Slite in the first place.

That lost deal helped us do that. Sometimes you'll lose a deal so right that it'll shake you to re-think everything you thought you knew. And that's when magic in positioning and product thinking happens.

But damn, that rejection stung at the time.

Leaving this ✨ crew after 1 week of outstanding work and now ➡︎ on my way to San Francisco!

Last week we were preparing the future of Slite and super.work, this week I plan to show it to as many potential buyers and founders to see if our next iteration resonates!

If you are in town and 
- need Super for your team
- want to boost your team speed with instant business answers
- need a more accurate and cheaper alternative to your Guru, Glean Notion AI, etc
- work on RAG and AI productivity

Hit me up! 

And for all the rest stay tuned, we have the 2nd version of Super almost ready for show time, it truly will be the best company search in the world (we measure it).

The SF 996 work culture gets criticized a lot, but honestly? It's the default for most founders I know.

It also applied to most startup employees before ~2018, before the massive COVID funding wave.

In 2012, most of my friends out of college joining startups had way lower salaries than others, they were genuinely excited about innovation and building things that hadn't existed before, they wanted to be here for the ride.

My cofounder Pierre still tells me stories of running migrations at nights, working and sleeping in his first company office. And I don't think he'd have traded this for anything in the world.

If you ask anyone who went through this in their 20s in the last decade, I believe the story would have been the same. The long hours weren't glorified or bashed, they just were, but I believe for the right reasons.

It felt sustainable because everyone was doing it for the right reasons (and most people were too young to have families 😅).

996 is a taboo issue now because the "tech world " norm went from startup to scale-up, from bootstrapping to being funded day 1, from joining and be part of a mission to optimising your career by joining the right rocketship. Something shifted, and we began to criticise 996 because we were suddenly judging startups as mature companies.

But, making a startup work is a game against all odds. It requires a crazy amount of attention and care. It's not for everyone, and not everyone should join a startup.

But if you're a startup founder, looking to create generational products, at least for a given point in time, 996 is necessary. And if people join and enjoy this rhythm for a few years, and get rewarded for it, so be it.

It should not be the norm of work, but startups are not the norm, they're the outliers.

People don't understand Claude skills but I couldn't be more pumped
10y ago, I wouldn't have thought I'd be hyped about folders with MD files 😅
But hear me out, Claude Skills are great.

We've been trying to figure out how to package AI expertise for the last few years.

Custom GPTs were too rigid and quite limited.
MCPs are just tools, and need to be wrapped to deliver value.
Claude Projects were quite basic, just a preset of files and simple RAG to prompt on.

Skills might crack it because they're stupidly simple.

So what's a Skill: folder with context + optional code ready to be run. Claude reads a 2-line description. When you need it, Claude loads the full thing to get the extra context + get your custom code tools ready.
That's it.

Here's why that matters.

Your designer spent weeks getting your brand guidelines perfect. Fonts, colors, spacing, logo placement. Now every deck needs to follow them.

Old way: Copy-paste the guidelines into every prompt. Hope people remember. Get inconsistent results.

Skills way: Package it once. Everyone on your team asks for a deck, Claude applies it. No copy-paste. No drift.

You need a chart in there? add some python code to do it. Or generate end embed images, just running a script to the midjourney api.
Need custom team data to feed this deck? use Super MCP in the loop.

Same for code review standards. Support ticket responses. Meeting notes that become action items. Contract redlining rules.
Build it once. Share it. It works the same for everyone.

Skills validate something: simple modules that load when needed, executable when required, shareable across teams.

Anthropic is testing abstractions. This might not be the final form. But it definitely feels like a natural way for how LLMs work. And we'll definitely take inspiration from them if not use them as a basic format standard in our products.

Only 10-15 books on startups have achieved cult status. Every founder has either read it or has it on their shelves. 
But 2 of them set off my internal red flags every time I see them.

They are

1. OKRs - John Doerr's Measure what matters
All companies will implement OKRs at least once in their life.

Maybe it's the new VP at the big org who does it to give the illusion of impact.
But soon the idea spreads and suddenly, you see anxious first-time founders will opt for it as a solution. And it makes perfect sense to them on paper - OKRs signal you're a serious company with clear structures.

But no one tells how to do it, your startup evolves every 3 months, your team is dynamic, and half your tracking for Key Results is a farce.

On the other hand, a large company doesn't have that kind of internal volatility. They're probably an established market player, with a 4+ level hierarchy system where the groundwork becomes opaque to the ones at the top floor. Moreover, they don't have a sense of culture to propel them forward. So OKRs come in, ensure every department knows their lane and HOW they'll impact the bottomline.

You, as a startup, need a strong culture, flat hierarchies, and constant iteration on what you're shipping and how you're selling it.

2. Marty Cagan's Product books
Every PM has read Inspired. It's gospel in product circles.

The ideas make sense when you're at a company with real scale. You've got product-market fit, dedicated teams, engineering resources that aren't stretched thin.

Discovery becomes valuable because building the wrong thing is expensive.
You can afford to say no to features. 
But early-stage founders read the same books and think they need to "professionalize" their product process.

The founder-PM creates a discovery backlog while also doing customer support and trying to close deals. You start separating discovery from delivery when the whole point of being small is that you can do both simultaneously, faster than anyone else.

Cagan's frameworks prerequisite a stability you don't have. They're tools for optimization, not for finding your way in the dark.

And I get it. As a new company, you're always wondering what you're doing wrong. Reading books help you quiet that nagging fear. But as a startup, there's really only 3 things to take care of:
1. Culture
2. Shipping speed
3. Finding PMF

So read wisely, selectively, and don't worry so much - you'll do just fine.

This customer is beating us at our own playbook 🔥🔥

Uscreen is a 100 person team, spanned across 73 countries, fully profitable.

And they've already nailed an issue most companies suck at: Context. 

Their knowledge is perfectly retrievable. Be it an employee or an agent, they can just ask a question about anything related to the company, and get the context to unblock their work.

Sure, it saves the Slack pings of hunting for files, but more importantly, that's the foundation that makes AI tools actually work when you deploy them.

In 9 days, Jaimie (their Chief of Staff) is joining me live to walk through how they built this.
How a distributed team across 73 countries keeps their knowledge accessible.

You'll see how they
- structured their documentation so it's actually findable.
- built the culture where writing things down is just how the team works
- built a team that never blocks each other with information assymetry

This is peer-to-peer learning. No pitch deck. Just a 45-minute conversation with someone who solved this problem.

When: October 29, 2025
Time: 5 PM CET / 10 AM EST

Register here: https://lnkd.in/emBXRsf8

So pumped to have you on this one Jaimie!

Your sourcing agent is hunting for a product marketer. It finds two candidates:

Profile A: 5 years at Google, launched 3 major campaigns, MBA from Wharton, expertise in growth marketing and analytics.
Profile B: 3 years across 2 startups, built marketing from scratch at a 10-person company, no formal degree, specializes in scrappy growth tactics.

The AI agent sees both profiles and thinks: "Perfect matches!"

A human recruiter immediately picks Profile B. Not because of the resume, but because of context. The human recruiter has been in your Slack chats, seen the long threads about moving fast and avoiding corporate processes. They've watched candidates from big tech companies struggle with your lack of structure. They know that your last Google hire quit after three months because they couldn't handle the chaos.

This accumulated wisdom can't be captured in a prompt. You can't distill years of hiring mistakes, cultural observations, and team dynamics into four sentences and expect AI to make the same nuanced decisions.

Yet that's exactly what we keep trying to do. We feed AI generic job descriptions and wonder why it returns generic candidates. We give it surface-level requirements and expect deep insights about cultural fit.

The problem isn't the AI. The problem is context.

AI that truly understands your company needs access to everything your human recruiter knows. The Slack conversations about what went wrong with the last hire. The performance reviews that revealed why certain personalities clash with your team. The CEO's offhand comments about the kind of person who thrives in your environment.

That's what super.work does. It doesn't just read your job description. It understands your company's hiring DNA from every rejection email, every successful onboarding, every cultural misstep. It crafts prompts you wouldn't think of because it knows context you've forgotten.

You need better context delivered fast, otherwise you'll never capitalize on AI's potential.

Without it, you'll just create more noise.

4 months into selling our first AI product and first learning: you need someone in Slack DMs with your biggest prospects.

Palantir Technologies deployed Forward Deployed Engineers 10 years ago to be close to the customer and iterate to a perfect deployment with the customer.

Right now, all AI companies need the same motion to close their biggest customers.

We've closed half a million in revenue since launching Super, and still, the main thing that helped us win all the pilots (beyond core quality ofc) was...
🥁🥁🥁🥁
... our white gloved, 3-month pilot phases.

Any time a Super prospect comes in
→ We offer them a trial
→ They get a Slack channel with us
→ They run into a wall? They text us and we jump immediately
→ They spot a bug? We resolve within 24 hours
→ They get a crazy idea request? We try to ship a proof of concept the same week if it was part of our plans.

The same trend is happening in enterprise deals too. FDE roles are skyrocketing, with GTM over-promising and product under-delivering, you need to do some plumbing to truly embed AI in their team.

Onboarding needs to stay close-knit until the AI category matures to the point where customers know exactly what to expect and product can deliver that with 100% reliability.

Until then, it only makes sense for B2B sales to adapt, even for mid-market
- A real Solution eng + AE to close
- A Product specialist come work hand in hand post sales for internal deployment

In this weird early phase of AI product, this supplements an enormous amount trust to your customers that they're heard, that their concerns are valid, and that you'll help them implement the tool and scale with their team.

Once you prove that you're trustworthy, you automatically get a leg up from your competitors in the trust race. Even if they offer 1 more integration or a better UX for now, your customers will KNOW that you're there, hearing them, working with them to make your product into something they can safely roll out to their team.

All enterprise search tools look the same 🫠
We all promise enterprise search, custom assistants, and transforming how work gets done.

While we're the best in class in terms of answer accuracy, we too sound the same. 

Any advice would be VERY appreciated 😫

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Christophe Pasquier

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taplio

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Hugo Pereira

Christophe Pasquier

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