How to Stay Under 150 Employees and Still Grow
“At 150 people, weird stuff starts to happen.” — Chris Cox, Facebook
There’s this moment in a startup — usually around 50 people — when something fundamental shifts. If you’ve been through it, you know what I mean.
Suddenly, you need org design. You need management layers. You need budget planning, delegation, handoffs. Work starts to diversify. You move slower. Veterans miss the old days. Newcomers struggle to catch the vibe. The product gets more complex. Everything gets... heavier.
And that’s just the warm-up.
Because if you’re lucky — or well-funded — growth continues. And before you know it, you blow right past 150 people.
That’s where the weirdness really begins.
The 150-Person Problem No One Prepares You For
I used to think it was just a meme — like “the 3-year relationship curse.” But the number 150 keeps showing up. Not because founders like it, but because the human brain does.
Anthropologist Robin Dunbar noticed that humans seem wired to comfortably maintain about 150 relationships. Beyond that, social cohesion breaks. Communication frays. Context disappears. Trust turns into bureaucracy. It’s not magic. It’s cognitive load.
“At 150 people, weird stuff starts to happen.” — Chris Cox, Facebook
source“We found again and again that things get clumsy at a hundred and fifty.” — Bill Gore, Gore-Tex
source
Some companies try to acknowledge this limit structurally — like Spotify, with its famous “tribes” model, each capped at ~150 people. But even they’ve admitted that it’s hard when the product is still one monolith. You risk fragmenting ownership of the whole.
Others, like Basecamp or FatSecret, just… never cross 150 in the first place.
Basecamp: ~70 employees, profitable, millions of users.
FatSecret: ~38 people, 100M+ users.
Cursor: ~20 people. ElevenLabs: ~50.
sources / crunchbase / techcrunch
These are not tiny lifestyle businesses. They’re deliberate machines, built under constraint.
What We’re Trying to Do — and Why
We made a decision recently: we want to grow without crossing 150 people.
We wrote it down. It’s a goal at the top management level. Not because we’re trying to be clever — honestly, it’s kind of terrifying. But because we think there’s something real at stake.
We want:
To preserve clarity and speed
To avoid future layoffs from overhiring
To protect culture before we have to define it in Notion
To keep building things that are actually good — not just good enough
And we think the constraint might help us do that.
It’s not some final answer. It’s more like a hypothesis. But a serious one.
Why It's So Tempting to Ignore This
Because when you raise money or start hitting product-market fit, hiring feels like the obvious lever.
Can’t ship fast enough? Hire more devs. Need growth? Hire a team. Can’t keep up with users? Expand support.
But it adds up — and by the time you look up, you’re 180 people deep and wondering why no one feels responsible for anything anymore.
There’s research behind this. At 150 people, the number of potential relationships is ~11,175. That’s a lot of lost context.
And honestly, it’s hard to feel urgency when the team’s too big to feel the tension. The fire’s still burning, but the pot is so wide, no one sees the boil.
So How Are We Trying to Pull This Off?
We’re still learning. But here’s what we’ve been thinking.
We realized that hiring “great people” is not enough. Even the best people hit bottlenecks — in communication, coordination, and feedback.
And that’s where AI comes in — not just as a way to do more, but as a way to work differently.
Most people talk about AI like it’s a tool for automating repetitive tasks. And yes, it is — especially the kind of well-documented, low-context, rule-based things that humans tend to get bored of or mess up.
But there’s a second, much less discussed strength of AI: it doesn’t fear volume.
Humans hit a wall when there’s too much context. We get overwhelmed. We skim. We drop the thread. AI doesn’t flinch. It can hold more information in active memory than any one of us. And that matters a lot when you’re trying to scale without losing context.
The third thing — and this surprised me — is feedback.
Giving and receiving feedback in teams is deeply emotional. It costs people energy. They hesitate. They sugarcoat. They delay.
But AI doesn’t need to manage anyone’s feelings. It can offer gentle reflection, performance stats, behavior patterns — early, consistent, and emotionally neutral.
It reminds me of sports.
Athletes live in a world where feedback is constant, quantified, and non-optional. Every pass, every run, every missed shot — it’s all there, after every game. And somehow, they survive. They even thrive.
In most companies, that kind of feedback loop doesn’t exist. But with AI? It could. And that might be the key to scaling quality and culture without drowning managers in emotional labor.
One more thing: for AI to work well, your org needs to become legible.
You have to write things down — culture, strategy, decisions, processes. You have to be clear, structured, and searchable. That alone forces a level of organizational hygiene that, frankly, most companies never get to.
And maybe, just maybe, that hygiene is what keeps the soul of the company intact when everything else scales.
So yeah, we will grow.
But we’re also trying to stay small.
Not small in ambition. Small in entropy.
And AI, weirdly enough, is giving us hope that both might be possible.
If you’re a founder trying to hold onto the magic while building something big — I’d love to hear what’s working for you.