Case Study: Preventing Mis-Leveling

How Woven helped a fast-growing AI company reduce their mis-hires by more than 91%

See how Woven helped predict their only mis-hire.

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Today’s engineering leaders are accountable for building large teams that continually raise the bar. However, as an org grows with hiring managers, directors, and more unique roles, maintaining a high bar can be challenging.

Teams often become littered with mis-leveled hires, where the hiring levels are not tied well to career ladders and there’s a lack of consistency in experience and skill.

The Situation

A newly hired VP of Engineering at a series B startup backed by Craft Ventures was tasked with hiring a large number of senior engineers while increasing department benchmarks. The VP had just come from a company that struggled with chronic mis-leveling and knew the impact it could have on their department as well as their own job.

The Solution

The VP of Engineering reached out to Woven to prevent mis-hires and get a consistent signal on seniority. Unlike traditional code quizzes, Woven puts engineering candidates through scenarios that emulate real world work.

We ask candidates to complete Code Review, Systems Design, and Architecture/Debugging scenarios to see who can actually perform in a role. Then we score them using real engineers and a detailed rubric.

The Results

Based on our same-day scores, the VP of Engineering was able to identify the most qualified candidates fast. 

The VP said, “In my prior role, 1 out of 3 hires didn’t perform. With Woven, only 1 out of 11 hasn’t performed. And that person had a noticeably lower Woven score.” 

Today, this fast-growing company relies on Woven to mitigate the risk of mis-leveling and get a consistent signal on senior engineering candidates.

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