Meet Claire: Head of Talent Ops at Terac

From referrer to operator

Claire did not set out to work at Terac. She joined as a contributor and quickly noticed that the hardest part of running a verified-expert network was not the technology; it was the sourcing. The audiences researchers actually needed were the kind of people no recruiter could find through a LinkedIn search.

So she started referring people she knew personally: friends, friends of friends, niche operators inside industries she had spent years adjacent to. Quietly, methodically. A few of those referrals turned into the kind of long-running contributors every panel wants.

The pattern was hard to ignore. The experts she trusted enough to vouch for tended to stick around: they submitted thoughtful work, completed the studies they signed up for, and brought their own networks along when a research team needed a deeper slice of an industry.

Why referrals beat ads, every time

"I started by referring people I trusted into the panel, friends, friends of friends, the niche operators no recruiter could find," Claire says. The pattern repeated: every time the panel needed a hard-to-source slice (a particular type of clinician, a sector specialist, an operator from a specific region), the best path was a warm intro from someone already in the network.

Paid sourcing solves the easy half of the supply problem: the volume half. It is excellent at producing applicants and unreliable at producing the specific applicant a study actually needs. The narrower the niche, the worse the economics get, and the more an ad-sourced funnel fills up with people gaming the screener instead of people who belong in it.

After a few months of referring her way around that bottleneck, Terac called and offered her a full-time role running Talent Ops. The pitch was simple: do what you have been doing, but for the whole network.

What Talent Ops looks like inside Terac

Today Claire leads the team responsible for the supply side of the platform. That means building the systems that let referrals scale: how people get invited, how their credentials get verified through attestations like government ID and LinkedIn, and how studies get matched to the experts most likely to do them well.

A lot of the work is unglamorous in the best way. Tightening invitation flows. Reviewing which referral paths actually produce active experts versus the ones that just look good on a dashboard. Pruning channels that drift toward incentive farming. The compounding wins come from removing reasons the network might lose its signal, not from chasing raw growth.

She still spends a meaningful chunk of her time on the same activity that got her hired: making warm intros. The difference now is that the whole team is structured around that motion, and the systems behind it carry referrals that would have been informal a year ago.

Where the panel is heading

Terac started in market research, panels for UXR and product teams. The shape of the problem has not changed as the platform has expanded into human data for AI training and, eventually, labor infrastructure for agent-driven work: at every step, the question is whether you can put a verified, specific human in front of a specific job, fast.

Claire's view is that the referrer motion gets more valuable, not less, as the jobs get stranger. A training run looking for senior tax attorneys to evaluate a model's reasoning, or for clinicians who can adjudicate edge-case diagnoses, is exactly the kind of audience that does not exist on a recruitment ad surface. It exists in the personal networks of people who already do that work.

Growing the people who grow the company

"The community grew the company, and the company grew me right back," Claire says. Over 240 hires have been sourced through the referral system she helped formalize, and a good portion of Terac's most active experts joined through a personal vouch.

Her advice for anyone thinking about referring someone they know: do it carefully. A network is only as good as the trust running through it, and a vouch is a small claim about your own judgment as much as it is about the person you are referring.

The referrers who land the most experts tend to be the ones who are slightly stingy with their intros. They make fewer of them, and the ones they make tend to belong.