Sixteen years ago, we started as a small group of engineers. Long nights of coding. Endless problem-solving fueled by passion and a belief that we could build something meaningful.
Scaling in those days meant one thing: more people.
Recruiting at speed. Running intensive onboarding sessions. Leaning on outsourcing partners whenever demand spiked. We tried everything – distributed pods, layered hierarchies, global delivery centers.
Each approach came with its own lessons. Some stuck. Others taught us what to avoid.
What we learned through it all is this: scaling has never been about numbers alone. It has always been about rhythm. The rhythm of hiring at speed. Transferring knowledge quickly. Aligning diverse teams across geographies. And most importantly, keeping product quality consistent under pressure.
We felt the growing pains ourselves, and we watched our clients experience them too.
Today, the same call for rapid scaling continues. A client lands a new enterprise deal and suddenly needs to double their engineering capacity. A product hits market traction, and the development roadmap expands overnight.
The urgency feels the same. The environment does not. Because AI is simplifying the rules of how scaling should be approached.
It is from this vantage point (having lived through the old cycles of growth and now actively helping companies navigate the AI era) that we want to share a perspective on what scaling product development teams truly means today.
12 mins
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