Product

Behind the scenes: shipping the AI screening engine

The nine-month journey from prototype to GA, the design partner programme that shaped the six default scoring parameters, and the bug that almost cost us the launch.

How the six defaults emerged

We started with twelve scoring parameters and a hypothesis that more is better. Design partners hated it. By month three we cut to nine, by month five to seven, and by GA we settled on the six defaults: experience, technical depth, education, domain fit, career stability, resume quality.

The customers who most wanted custom parameters were the ones who needed them; the rest defaulted to the six. The ATS still supports adding custom parameters, but the six handle most of what hiring teams need.

The bug that almost killed launch

Three weeks before GA, a customer reported that the score for a senior candidate was lower than for a junior with the same skills. The bug: our experience score was applying a recency penalty meant for entry-level candidates to senior candidates as well. The fix was a one-line change; the diagnosis took two days.

We added a regression test the same day. Our bias harness was already running, but the harness did not catch this case because the swap was on experience years, not on a protected attribute.

What ninety design partners taught us

We ran a structured nine-month design-partner programme: ninety customers, monthly check-ins, weekly issue triage. The discipline of writing back to design partners by name made the team think about feedback as a relationship, not a queue.

The five biggest product changes in the last sprint of GA all came from design partners. A separate post covers the programme structure.

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