96% Retention in Hypergrowth: How We Beat the Industry Average by 28 Percentage Points
Lloyd Moore
When I told our CEO I wanted our best blockchain engineers to work part-time for Ethereum Foundation and Solana, he didn’t blink. Constantine trusted me. But I understood why it sounded mad.
We were scaling Blockdaemon from 10 to 187 engineers. We’d just closed a funding round. Everyone knows you’re supposed to lock down your best people during hypergrowth, not let them moonlight with the competition.
But here’s what I’d learned: certain engineers need challenging work more than they need loyalty speeches. If Blockdaemon couldn’t provide that challenge every single day, they’d leave anyway. Better to let them scratch that itch with Ethereum Foundation while bringing back knowledge that would benefit us for years.
We ended up with 96% retention. Industry average is 68%.
That’s a 28 percentage point advantage during the exact period when most companies haemorrhage talent.
Why Series A retention matters more than you think
Series A is when the knowledge problem starts to kill you.
You’ve gained momentum. You’ve got paying customers. You’re hiring fast because the next funding round depends on hitting aggressive targets. And then someone leaves.
They take with them all the reasons why the codebase looks like it does. Why you made that architectural decision in March. Why the team culturally rejected that framework everyone else uses. The new person comes in and immediately creates work - explaining context, justifying decisions, re-litigating debates you thought were settled.
Lose three people in quick succession and you’ve lost your institutional memory. The team stops moving forward because they’re constantly explaining the past.
2025 data shows 38% of engineering leaders report less motivated teams than a year ago. Only 21% describe their teams as healthy. If you’re a Series A founder reading this and thinking “my team seems fine,” you might be six months behind the curve.
What actually worked
I’m not going to give you a generic retention framework. You’ve read those. They don’t work because they’re not specific enough.
Here’s what we actually did, and why it mattered.
Let your best people work elsewhere
I mentioned the Ethereum Foundation arrangement. This wasn’t charity. It was strategic.
Top engineers with niche blockchain knowledge were hard to keep challenged. Blockdaemon’s work was demanding but sometimes not cutting-edge enough for people who’d rather be solving novel cryptographic problems.
So we let them work part-time on Ethereum and Solana projects. They stayed engaged. We got early visibility into where the ecosystem was heading. They brought back knowledge that kept us ahead of the market.
The mistake most companies make is thinking they need to own 100% of someone’s time to get 100% of their value. Wrong. Give your best people the freedom to stay intellectually stimulated and they’ll give you their best work.
Build systematic onboarding that scales
When you’re growing fast, the temptation is to throw new people at problems immediately. We built Blockdaemon University instead.
Four-week rotation system. New engineers spent their first month learning from different teams, understanding our architecture, absorbing why we’d made key decisions. Crucially, this meant existing teams didn’t lose productivity every time someone new joined.
Most companies treat onboarding as a checklist. We treated it as a system. The difference: our teams stayed productive even while we were hiring aggressively.
Design teams that don’t need help
Cross-team dependencies kill velocity. Every time Team A needs something from Team B, you’ve introduced delay, coordination overhead, and frustration.
We structured teams so they could complete their work independently. Not perfectly - some dependencies are unavoidable - but we minimised them ruthlessly.
This mattered for retention because engineers hate being blocked. They hate waiting for other teams. They hate feeling like they can’t ship because someone else is the bottleneck. Give people autonomy to complete their work and they stay engaged.
Pay globally competitive rates everywhere
We paid salaries based on the highest paying regions, regardless of where someone lived.
This wasn’t altruism. It was pragmatism. If you want to hire the best people from anywhere, you can’t pay them based on local markets. You pay them what they’re worth globally.
Most companies try to arbitrage talent by paying local rates. They save money in the short term and lose people in the medium term. We chose to compete globally from day one.
Evaluate fairly with SPACE
Performance reviews are where retention dies quietly. People leave when they feel evaluations are subjective, political, or unfair.
We used the SPACE framework - Satisfaction, Performance, Activity, Communication, Efficiency. It’s not perfect but it’s systematic. More importantly, it gave us a common language for evaluating people that felt less arbitrary than “culture fit” or “leadership potential.”
Engineers respect systems. They don’t respect vibes-based management.
Over-communicate the mission
At any stage of onboarding - week one or month six - anyone on the team could tell you what Blockdaemon was trying to achieve and why it mattered.
That’s not an accident. I over-communicated constantly. Mission, strategy, priorities, trade-offs. Again and again until it felt repetitive to me but was finally landing with the team.
People don’t leave companies with clear missions. They leave when they don’t understand why their work matters.
What this actually means for you
If you’re running a Series A company, here’s what you should be thinking about:
Who are your retention risks right now? Not the people who are obviously unhappy - you already know about them. The high performers who seem fine but haven’t been challenged in three months. They’re the ones who’ll get a LinkedIn message next week and actually reply.
What knowledge lives only in people’s heads? If your best engineer left tomorrow, what decisions would the team struggle to understand? That’s your documentation gap. Fix it before you need it.
Are your teams designed for autonomy? Map out the dependencies. Every time Team A waits for Team B, you’ve found a retention risk. Engineers who can’t ship get frustrated fast.
How do people learn your “why”? New joiners need to understand not just what you’ve built, but why you built it that way. If that’s not systematic, you’re creating work every time you hire.
Who’s being challenged enough? Your best people need hard problems. If you can’t provide them, they’ll find them elsewhere. Better to make that arrangement explicit than lose them entirely.
The 96% retention rate wasn’t luck. It was deliberate systems, built over time, that removed the friction that makes people leave.
Most companies lose their best people not because they’re bad places to work, but because they haven’t thought systematically about what makes people stay.
You’re scaling fast. You’re hiring aggressively. You’re under pressure to hit targets that unlock the next round.
But if you lose your best people in the middle of that, you’re not moving forward. You’re explaining the past to newcomers who don’t have the context to understand it.
That’s the retention problem at Series A. And it’s fixable if you’re willing to build systems instead of relying on hope.
Want this framework as a one-page reference? Download it here: https://lloydmoore.com/downloads/retention-framework.pdf