This told essay is based on a conversation with Shivam Sagar, a 28-year-old senior software engineer at Aragon AI based in northern India. The following has been edited for length and clarity.
I wish I had fully understood the difference in pace and rhythm of a small team before joining.
When I changed jobs last year, I went from an organization with dozens of engineers to one with only six people, including the CTO. In large teams, roles and processes form a natural structure. For teams of less than 10 people, that disappears overnight.
I underestimated how mentally exhausting the personal pressure would be, but owning this much product is also liberating.
Migration is all about mindset, trading expertise with a focus on flexibility, and structure with a focus on speed. Once we stopped trying to recreate something that worked at scale, the creativity and ownership we gained in a small AI-focused team became incredibly rewarding.
I became a generalist and learned to be close to the users in order to succeed in a small team.
Product, engineering, and design teams are small and often blend together. We feel great because we are solving problems as a unit rather than as individual features.
Because I’m involved in so many aspects of the product, I have to step out of my comfort zone and become a bit of a generalist because the scope I’m working with is new to me. Decision-making doesn’t require layers of overhead management or scheduling five meetings to coordinate. When I see something that needs to be done, I usually just do it.
What I’ve learned is to be close to your users for guidance. Especially for small teams, every conversation with your users can rebuild your roadmap faster than any research paper.
my work feels more intentional
When I transitioned to a smaller team, I basically spent the first six months waking up, coding, and sleeping. However, with more context around the product, the workload became more manageable.
When I’m in a large team, I often feel like I’m juggling requests and priorities without fully grasping them, making it difficult to switch off when work is done. My work feels more intentional here, and I can make clearer decisions about where to focus and when to step back.
Work-life balance has changed
At first, there was a backlog, and I was in charge of most of it, so it was hectic. We didn’t really have anyone to teach us the codebase, so we had to learn the structure, build new features, and handle all the quality checks ourselves. This was a big change from working in large teams with multiple developers reviewing and testing each feature before release.
It’s definitely a different kind of work-life balance. It’s a little hectic at times, but overall I’m working in better conditions and with more control.
My biggest advice is to value adaptability over perfection
For small teams committed to using AI, things change quickly. Tools, models, priorities, and even the definition of success can change rapidly.
Gone is the natural peer review and mentorship that comes with large teams, so code reviews, design critiques, and knowledge sharing must be deliberate to prevent silos from forming. We can move incredibly fast, but only if we’re all aligned, in constant communication, and honest about what’s real.
Teams that succeed in this model are not those that plan everything perfectly in advance, but those that experiment quickly, learn from failures, and integrate new features.
Do you have a story to share about transitioning to a smaller team? Contact this reporter, Agnes Applegate, at: aapplegate@businessinsider.com.
