When Fellow.ai first launched its product in 2019, it wasn’t yet the AI-powered “chief of staff” it is today. Over the last two years, the Ottawa-based startup reinvented itself—from product to pricing to go-to-market—and rebuilt its team to operate as an AI-first company.
“We basically reinvented everything,” CEO Aydin says. “The product, the roadmap, the go-to-market motion, the pricing—and also the team.” As a result, tech hiring has become one of the most critical components of the company’s trajectory. “The better the talent that we have, the more the odds of our success.”
From early MVP to the first hires
Fellow’s founding team includes two technical co-founders, Amin Mirzaee (CPO) and Samuel Cormier-Iijima (CTO), who have worked with Aydin across three companies and five products over the last 15 years. They built the first version of the product themselves. But once the company found early product market fit, they needed to expand the engineering team.
The first hires came from their existing network—people the founders had worked with before and trusted. But even with familiar faces, Aydin learned an important truth about startup hiring: not everyone is a “startup person.”
“It’s really important that you look for startup people,” he says. “Some people grow out of it. It’s not good or bad—you just need a special type of person to be a startup person.”
The traits he looks for: comfort with ambiguity, willingness to experiment, a desire to move quickly, and a mindset focused on the “job to be done” rather than a clearly defined set of duties.
Why titles can slow a young company down
One of Fellow’s most unconventional early decisions: eliminating titles entirely.
“For the first 25 to 30 hires, we had no titles,” Aydin says. “Titles are a roadblock at a small company.” They create boundaries around responsibility—something he wanted to avoid.
In a startup of ten people, he explains, work isn’t divided into neat boxes. Everyone must be comfortable jumping into whatever the company needs, regardless of role. Titles introduce unnecessary friction, hierarchy, and noise.
Eventually, as the team grew, titles reappeared out of necessity—not ego. “The team got large enough that we had to solve things like career progression,” he says. “Once we had those problems to solve, then titles and frameworks came in.”
But in the early days, eliminating them helped Fellow move faster.
Hiring tests built to reveal personality—not perfection
Before AI tools advanced, Fellow relied heavily on take-home tests that evaluated two things:
How fast someone could learn a new technology
Whether they went above and beyond the minimum
The instructions were intentionally vague. “Some people do the bare minimum. Others go above and beyond,” Aydin explains. “You can tell a lot by how people approach it.”
As AI evolved—and could complete some of these tests—Fellow adapted its evaluations to focus more on live problem-solving and interaction. But the underlying philosophy stayed the same: look for people who pour “love” into the work.
This applied across the company, not just in engineering.
“Startups are so hard. You’re fighting gravity every day,” he says. “You need every little percentage point of probability to go in your favor.”
The underrated skill: finding “undiscovered talent”
Aydin warns founders not to be overly impressed by flashy résumés, big-name companies, or candidates who were “there when things scaled.”
“Sometimes people were just along for the ride,” he says. More important is identifying people who have done meaningful work at companies others may not recognize. “As a startup, you’re looking for every advantage. You’re almost looking for undiscovered talent.”
And above all: founders should interview early hires themselves.
“Go with your gut instinct,” he says. “Interview every person—certainly the first 100. There aren’t many things that matter as much.”
Finding the right partners along the way
As Fellow transitioned into an AI-centric product organization, they partnered with VanHack, a global platform that connects companies to vetted international tech talent, to expand their engineering team with global talent experienced in machine learning, backend development, and high-growth environments. These hires supported rapid product iteration and helped the company accelerate its AI roadmap.
Their experience reflects what many fast-scaling teams discover: the right global talent can accelerate reinvention at moments of product and org change.