Yasmin Stewart

From the Restaurant Floor to Organizational Psychology

Before COVID, Stewart was managing high end chef restaurants. It is a training ground that rewards a particular set of instincts: reading a room quickly, holding standards under pressure, keeping a team of specialists moving in the same direction on a bad night. When the pandemic closed that world down, she made what she calls "kind of like a 180" and went to study psychology, with the specific aim of moving into organizational psychology.

The pivot was not aimless. She knew where she was headed before she got there. "I knew I wanted to go into affecting organizations from within and helping them grow with people," she says. Recruiting was the entry point she chose deliberately. An internship taken during her bachelor's degree turned into a conversation with Larissa, one of Unframe's founders and its COO, and that conversation turned into the job she holds today.

The Two Women Who Changed Her Trajectory

Ask Stewart who shaped her and she names two people without hesitation. The first is Eden, her guide during that internship. Stewart is candid that she arrived without much confidence in her own abilities. Eden believed in her anyway, trusted her, and, most importantly, gave her ownership. "She taught me a lot," Stewart says, and the internship that began with self doubt ended with her landing the role at Unframe. The lesson stuck: real confidence is built by being handed something that matters and being allowed to carry it.

The second is Larissa, the founder and COO who bet on her early. What Stewart takes from Larissa is a model rather than a maxim. She describes a leader who is down to earth and highly professional at the same time, a builder who gets things done. Seeing a woman operating at that level in business, in tech, and specifically in the AI space is, in Stewart's words, a direct motivator to grow with the company and beyond it. She watches closely and learns by observation, which is its own kind of discipline.

AI as a Feature Versus AI as a Product

Stewart's read on the AI shift comes in two parts, and she is careful to separate them. The first is practical and personal. AI has become, in her framing, her assistant. It helps her write outreach messages and job descriptions, and it helps her get up to speed on unfamiliar roles quickly, which matters more than people admit. "A lot of the times you have to recruit and hire for roles that you've never done," she notes. The tool closes that gap.

The second part is what she sees happening on the candidate side, and it is sharper. Talent is actively seeking out AI first and AI native companies, and the best candidates have grown sophisticated about what that actually means. They now distinguish between companies developing AI as a feature and companies developing AI as a product. That distinction, Stewart argues, is what serious talent is screening for. Employer brand in this market is not a careers page. It is whether the engineering problem at the center of the company is real.

Against the Eight Step Process

If Stewart has one conviction she wants other talent leaders to hear, it is that hiring processes have become far longer than the decision requires. She believes culture fit, technical ability, and how a candidate sees the product can all be assessed without dragging someone through eight rounds. "You don't need for people to meet the whole company," she says. Recruiting today, in her view, can and should move considerably faster.

That is not a case for cutting corners. It is a case for knowing what you are actually measuring, and for respecting a candidate's time enough to measure it efficiently. In a market where the strongest engineers and product people have options, a bloated funnel is not rigor. It is attrition.

Hiring for the Role That Does Not Exist Yet

The most demanding part of Stewart's philosophy is temporal. Generative AI tools have changed the day to day work of product managers drastically over the past two to three years, and she expects the same for developers and beyond. Which means a candidate's track record, on its own, is an incomplete instrument. "The way that they did their work two years ago and the way that they're going to do their work in two years is going to be drastically different," she says.

Her answer is to evaluate the whole package: what someone has done, what their skills are, and, frequently, what their potential is. She looks hard for people who are well rounded, and she insists that a recruiter has to form a view of where the role itself is heading. Only then can you hire talent who will thrive in that environment rather than talent who was perfectly calibrated to the environment that just ended.

It is a demanding standard, and it happens to describe her own path. A restaurant manager who retrained in psychology, walked into an internship without confidence, and now hires globally for an AI company is, in a sense, exactly the kind of well rounded bet she now advocates that others make.