The Secret to Scaling Teams from 37 to 1000 Engineers with Ameya Kanitkar
What separates good engineers from exceptional leaders? According to Ameya Kanitkar, Co-founder and CTO of Larridin, it’s not just about building great systems; it’s about building teams that can build systems at scale.
It’s a lesson he learned firsthand during Groupon’s meteoric rise from just 37 engineers to more than 1000, a journey that made the company the fastest to reach $1 billion in revenue at the time.On the latest episode of the Signal to Noise Podcast, Ameya sat down with Eóin O’Toole, Managing Partner at Riviera Partners, to unpack the realities of scaling engineering teams, the role of ownership in differentiating talent, and the messy, but necessary work of balancing process and productivity.
From Building Systems to Building Teams
Early in his career, Ameya received a piece of feedback that changed the way he thought about leadership.
“You’re good at building systems, but you’re yet to get to a point where you can build teams that make systems.”
That shift, from being a builder to building a factory of builders, is what allowed Groupon to scale at breakneck speed. Instead of focusing solely on his own contributions, Ameya had to ask: How do I create an environment where teams can thrive independently and continuously generate impact?
This mindset is what separates leaders who can stay with a company through hypergrowth from those who top out when things get complex.
Matching Teams to Business Needs
The true secret to scaling? Putting the right people in the right places. Ameya uses a simple but powerful framework:
- Do you have the right set of people?
- What’s missing?
- What can you achieve with the team you already have?
Sometimes the missing piece is a senior engineer who can provide stability and architectural foresight. Other times, it’s junior engineers who bring speed and adaptability.
At Coinbase, for example, Ameya ran both a notifications team (where reliability was mission-critical) and SEO/growth teams (where speed was everything). The two required very different team compositions:
- The notifications team needed cautious, detail-oriented engineers who could ensure trust and consistency.
- The growth teams thrived with hungry, risk-tolerant engineers who were comfortable working across multiple codebases and moving fast, even if things occasionally broke.
The key takeaway? Team design must match business priorities. Put the wrong profile in the wrong place, and you’ll get great output that doesn’t matter or fast output that undermines trust.
The ownership factors
“For me, the difference between good and great is actually very simple, which is ownership.”
Ownership shows up in different ways. Some engineers demonstrate it by founding companies. Others take initiative within their teams, spotting problems, proposing solutions, or expanding their responsibilities beyond what’s on paper.
What matters is that they own outcomes. They don’t just wait to be told what to do; they take the business forward.
Moreover, ownership plus critical thinking is a game-changer. In startups, especially, where chaos is a feature, not a bug, you need people who can adapt, take responsibility, and drive progress even when the goalposts move.
Scaling without drowning in the process
One of the big myths of scaling is that startups are dynamic and fast while big companies are slow and bureaucratic. Ameya pushes back on this:
“In good companies, people want to move fast and build value, whether they’re at a startup or a big company. What changes is the scaffolding, primarily processes.”
When processes exist to align everyone in the same direction, they’re valuable. When processes exist because of a lack of trust, they’re just noise.
The trick for leaders is to minimize unnecessary overhead. Too little process and teams fall out of sync. Too much, and you’re burning 30-50% of your CPU cycles on busywork.
The best engineering leaders figure out how to keep that tax as low as possible, sometimes as low as 15%, so that teams can still operate with the agility of a startup, even inside a giant organization.
AI: Noise, Signal, and Adoption
Of course, no conversation about scaling teams today is complete without talking about AI. Ameya’s take?
- AI is both the signal and the noise. It’s the biggest opportunity but also the biggest distraction, depending on how it’s applied.
- Agentic AI isn’t here yet. Much like LLMS in 2021, it’s more of a future promise than a present reality.
Enterprise adoption requires balance. The technology is ready, but people and processes take time to adapt. Safe, human-centered change management is just as critical as model accuracy.
Leadership as the Battery
At the heart of Ameya’s philosophy is a metaphor he once heard from a mentor:
“As a leader, your role is the battery. The rest of the team is doing the actual work, but your job is to provide the energy.”
Your job isn’t to write the code, close the deals, or ship the product. Your job is to be the energy source that powers the system. When you bring energy, output multiplies. When you don’t even the best team underperforms.
It’s why Ameya believes that scaling teams isn’t about replicating processes. It’s about creating an environment where ownership, alignment, and energy multiply across hundreds or thousands of people.
Final Thoughts
Scaling from 37 to 1000 engineers isn’t about brute force hiring or an endless process. It’s about mindset shifts, thoughtful team design, ownership, and leadership that energizes rather than constraints. Whether you’re a founder building your first engineering team or an executive guiding a global organization, Ameya’s journey is a reminder: the secret to scaling lies in the people you empower to build them.
Ameya’s Background
Ameya Kanitkar is the Co-founder and CTO of Larridin, a Bay Area-based startup building an organizational fitness platform powered by AI. With vast experience scaling engineering teams at major tech companies, he previously led consumer trading engineering at Coinbase and built unified data analytics systems at LinkedIn. During his tenure at Groupon, he played a key role in the company’s hyper-growth phase, helping scale from 37 to 1000 engineers.
Listen now: Signal to Noise Episode 5: The Secret to Scaling Teams from 37 to 1000 Engineers with Ameya Kanitkar
