More and more companies are reducing their staff and leaning into AI. Coinbase CEO Brian Armstrong is the latest tech exec to head in that direction.
Armstrong said the fintech company plans to lay off around 14% of its workforce. He shared his message publicly on X on Tuesday morning, saying, “The pace of what’s possible with a small, focused team has changed dramatically, and it’s accelerating every day.”
The appeal is simple: smaller teams mean faster decisions, lower costs, and more control. But as AI changes the number of people companies actually need, new challenges have emerged.
Business Insider has spoken with over a dozen executives at lean AI startups with fewer than 10 full-time employees over the past few months as part of our Tiny Teams series. They’ve all agreed that speed is the biggest advantage that AI has given them. However, with that speed, they’ve cited having to work harder to guide creativity, hire the right job candidates, and minimize potential mistakes.
Below are three founders who shared the biggest upsides and challenges that AI has presented them and their tiny teams. Their words have been edited for length and clarity.
The hardest part of a small team is balancing quick executions and meaningful creativity
Nathaneo Johnson is a 22-year-old CEO of Series, an AI social network, based in Chelsea, New York.
A lot of CEOs who are running older companies are in a relatively tough position to have to lay off a significant number of employees during the awakening of AI automation.
The AI era is all about speed, which makes lean specialized teams thrive, but the hardest part, day to day, is trying to restrict meetings without losing creative brainstorming time. I started Series with my cofounder during this exact era, so there wasn’t a need to hire at scale when there are AI agents for practically anything. However, creativity and vision will always be where humans win.
On a tiny team, it’s always a game of whether we encourage creativity and collaboration or push more heads-down execution. We could be the company that never talks and just works in Slack all day, and that seems to optimize productivity. The flip side is that there could be a brainstorming meeting that turns into a 10x idea, and we don’t want to lose that.
In the next five years, you won’t need someone to be a heads-down specialist; you’ll need someone who’s creative or visionary.
We can stay profitable when we’re lean, but finding the right hires is becoming more challenging
Sidhant Bendre is a 26-year-old cofounder of Oleve, an AI-driven consumer software portfolio company, based in New York.
Keeping our team small stemmed from a desire to be profitable. The fastest path to growth for us was to figure out tricks and hacks to do more with AI and fewer people. But on tiny teams, there’s no middle management layer to catch sloppiness, and there’s no room for people who aren’t thinking about how their work affects what comes next.
When everyone is a specialist, moving fast with a real sense of agency, one bad result doesn’t just mean one bad result; it compounds into an entirely bad system. That’s why the bar has been raised for each individual contributor, making hiring challenging.
We’ve had to create more involved engineering recruitment processes because we need to vet potential employees more closely. We’ve seen take-home tasks from job applicants where someone clearly just fed a prompt into ChatGPT and submitted whatever came back without critical thought.
It’s a skill to use AI to fully drive results, but that can be temporary when someone lacks the deeper knowledge needed to fix issues that arise.
Read more from our Tiny Teams series
The faster we move, the riskier it is for junior employees to make mistakes
Charles Swann is a 44-year-old founder of an AI startup based in Boulder, CO.
I founded my startup around two years ago, and I have one full-time employee. My business is in the marketing technology space, and I needed someone with a deep connection to modern culture and social media. So, I hired a 24-year-old from my neighborhood to be my growth and brand specialist.
I don’t need a huge team of founding engineers, each with a six-figure salary, to launch a product. I can use AI to have my junior employee produce senior-level work.
AI, specifically Gemini, serves as a middle management layer, helping her level up the work she produces. But, there’s always a risk in relying on AI to teach my employee how to gain years of experience in seconds. Hallucinations and feedback loops can occur when someone lacks the experience to know when to redirect.
What I’ve done to help safeguard us is create a collection of prompt starters that I can copy and paste into the chat to save time and help keep the AI focused on relevant context.
We might encounter potential mistakes or hallucinations, but I’d rather have those mistakes come up and have to course-correct than not be able to move at the pace we are.
Do you have a Tiny Teams story to share? Contact this reporter, Agnes Applegate, at aapplegate@businessinsider.com.
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