You deserve better

A candid reflection on leaving academia. From silence and sacrifice to freedom, trust, and a life beyond the lab.
You deserve better

This post was originally written in July 2016 but was never published. Nearly a decade later it still rings true. I revisit it now for anyone still in grad school, thinking about life outside.

“You don’t climb mountains without a team… you don’t climb mountains without being prepared… you never climb a mountain on accident.”

– Mark Udall, US Senator

Stop me if you’ve heard this before.

Every day you go to work. You don’t just give your time, your attention… you give a piece of yourself. Sometimes you work late and lose track of time because you’re too invested. The people who love you say you work too much. They don’t get it.

The pay isn’t great. And when you start doing the math on your hourly rate, you quickly stop because you must have forgotten how division works. Besides, you didn’t get into it for the money.

You went into it because it matters. It might not be glamorous. It might not be revolutionary. But in its own way, your work will change the world.

In those rare moments when you stop to look around, you see people who are equally talented, equally committed, equally driven. Peers.


Through the looking glass

If you’re reading this, I’d bet you’re thinking about your lab. Read it again. Couldn’t I just as easily be describing a startup?

Right now I’m in an office of forty people: biologists, engineers, statisticians, computer scientists - at last count, twenty different passports between us.

Here’s what stands out: when someone doesn’t understand something, they say so. No shame, no fear - just a question. In a room full of experts, everyone accepts that nobody knows everything. Over time you become the go-to for some things, and you lean on others for the rest. You learn to trust each other.

In seminars, you could feel the silence when something didn’t add up. A slide went by with the obvious gap, the unanswered “why?”, as the whole room shifted awkwardly in their seats. Everyone knew, but no one spoke. That silence wasn’t neutral - it protected the hierarchy, let flaws slide, and trained young researchers to swallow their doubts.

Here, it’s different. When someone doesn’t understand, they ask. Out loud. No shame, no fear - just a question that could have been easily buried or ignored. Sometimes the response is immediate. Other times the whole room stops, rethinks its assumptions, and changes course.

Deceptively simple questions are often the ones that matter most:
“Why are we doing it this way?”
“Have we thought about just…?”

And who wants to admit the answer is only “because that’s how we’ve always done it”? When no one questions the foundations, the work ossifies.

Yes, simple questions can bruise your ego. But they make the work stronger. A culture that invites them doesn’t just save time - it can save years of effort, even lives.


Shouldn’t science be a team sport?

I’m not saying companies are flawless. Big or small, every workplace has its grievances. Startups might be agile but rarely have the multi-year budgets of big pharma.

Both options are better than sitting at your bench alone.

You already know something’s off. It isn’t always about working harder or being more talented. We all know the postdoc who ran one perfect experiment on a magic sample and walked away with a Nature paper before they’d even worked out the coffee machine.

It stings - and everyone knows it’s all about luck, timing, and the supervisor you happen to have. And that’s the point: talent alone isn’t enough in a system that runs on chance. No one should build a career on lottery tickets.


We regret the decisions we don’t make

I was there too. I remember walking into my PI’s office, breaking down - tears on my cheeks, shoulders shuddering - forcing myself to resign in person because I’d promised myself I would. After more than a decade in university, grad school, and research institutes, I felt hollow. I didn’t have a why. All I had was “just not this.”

I couldn’t change my whole life alone. From age twelve, I’d aimed everything toward becoming a professor. Walking away felt like abandoning a dream, a piece of who I was. But with help, I found a plan - not a betrayal, but a path. Slowly “not this” turned into “what next?”


Hindsight is perfect

It’s been nearly two years since I walked away from academia. I’ve never regretted it. I miss some people, sure - colleagues, mentors, friends - but nothing about the life itself. I don’t ache for the bench. I don’t dream of swapping my keyboard for a pipette.

Now I go home at five. Now I know what a weekend feels like. The constant guilt, the “shouldn’t you be working?” voice that followed me everywhere - gone.

Sometimes I sit with my partner late at night, watching her wrestle with cells that refuse to grow. I look around the lab and remember how it felt to be trapped there, living on other people’s deadlines, measuring my worth in papers and p-values. And I feel nothing but gratitude that I’m no longer a hostage to that system.

They always say that once you leave, you can never go back: you’ll be out of date, you weren’t committed, you failed. But what if that’s backward? What if, once you’ve tasted freedom, you can never fit back into the cage?

Because in the end, you don’t climb mountains by accident - and you don’t have to climb them alone.

So, you wanna be a team lead
The Absence of Outrage

How do you define successful engineering leadership?

The Philosophy

Many view technical leadership as being the “smartest architect in the room.” I see it as the opposite. My job is to build a room where I don’t have to be the smartest person because the systems, culture, and communication are so robust that the team can out-innovate me.

The Strategy

  • Alignment: Does every engineer understand how their sprint task impacts the company’s bottom line?
  • Velocity vs. Stability: We aren’t just “shipping fast”; we are building a predictable, repeatable engine that doesn’t collapse under its own weight at the next order of magnitude.
  • The Human Growth Curve: Success is when the engineering team’s capability evolves faster than the product’s complexity. If the team feels stagnant, the tech stack will soon follow.

What is your approach to scaling technical organizations?

The Philosophy

Scaling isn’t just “hiring more people” - that’s often how you slow down. Scaling is about moving from Individual Heroics to Organizational Systems.

The Strategy

  • The 3-Continent Perspective: Having managed global teams, I focus on “High-Signal Communication.” As you grow, the cost of a meeting triples. I implement “Asynchronous-First” cultures that protect deep-work time while ensuring no one is blocked by a timezone.

  • Modular Autonomy: I advocate for breaking down monolithic teams into autonomous units with clear ownership. This reduces the “communication tax” and allows us to scale the headcount without scaling the bureaucracy.

  • Automation as Infrastructure: At petabyte scale, manual intervention is a failure. I treat the developer experience (CI/CD, observability, self-service infra) as a first-class product to keep the “path to production” frictionless.

How do you balance high-growth velocity with technical stability?

The Philosophy

Technical debt isn’t a “bad thing” to be avoided; it’s a set of historical decisions that no longer serve you. Like any loan, leverage can accelerate growth when investments payoff. But if velocity and returns are slowing you need a payment plan before the interest kills you.

The Strategy

  • The ROI Filter: I don’t refactor for the sake of “clean code.” I don’t refactor a micro-service with no users. I refactor when the pain on that debt - measured in bugs, downtime, or developer frustration - starts to exceed the cost of the fix.

  • Zero-Downtime Culture: Especially at scale, stability is a feature. I implement “Guardrail Engineering” where the system is designed to fail gracefully, ensuring that a Series B growth spike becomes a success story rather than a post-mortem.

  • The 70/20/10 Rule: I typically aim to dedicate 70% of resources to new features, 20% to infrastructure/debt, and 10% to R&D. This ensures we never stop innovating, but we never stop fortifying either.