Alex at Brilliant Earth

Changing careers is harder than it should be, especially early in your working life. That's where Alex was when she applied to Brilliant Earth: finishing graduate school, leaving an early-stage AI startup, and trying to land somewhere that would let her take on bigger work in a new industry.

When she saw the Brilliant Earth posting, the application came with a challenge. Her first reaction was familiar. "OK, here's another AI assessment."

She'd done a couple of those before. They'd felt like thin wrappers on ChatGPT, with generic questions and the sense that nothing she wrote would ever be read. She'd spent hours on one and never heard back, and walked away asking herself: "Did I just do free consulting, basically?"

This one surprised her.

What was different from the first screen

The Brilliant Earth challenge read differently. It was built around the real role at the real company, with specifics that couldn't have been copy-pasted from a template. "This is the role, here's the company," Alex said. "It was just spot on." A human had clearly designed this one, which told her a human would read what she turned in. She decided the time was worth spending.

The bigger surprise: an actual assignment

The challenge asked Alex to build something. She produced a video walkthrough and a one-page white paper that laid out her whole approach to the project: scope, execution plan, risks, and how she'd measure success. For someone whose strength is pulling together the systems view of a problem, this was the first time an application format had given her room to show it.

"You can't show that on a resume, as much as you can write bullet points for that, to see how someone does that kind of systems-level thinking."

The first interview started from a place of recognition

On her first call with Brilliant Earth, the SVP opened with "I feel like I know you already."

That kind of opening doesn't happen by accident. It happens when the other side has already spent real time with your thinking before you walk in. They'd watched Alex walk through her approach and read how she'd plan it out on paper. Her interview picked up from there.

Why this matters, especially for AI roles

Alex had a blunt take on the broader moment. Anyone can put AI on their resume right now. The skills behind that word are hugely varied, and resumes don't distinguish between them. A role-specific challenge, reviewed by a human, is one of the few ways a candidate can actually show which kind of AI practitioner they are.

"If I was a hiring manager, this is exactly how I would want to roll out my process to find that good candidate that hits what I actually need."

Three days into her new role, Alex was still thinking about the experience. About the one application where she got to show what she could do, and the team that already knew her when she walked through the door.