The systemic decay of tech hiring
Tech hiring has degraded into a system prioritizing process efficiency over human judgment. Reliance on algorithmic resume filtering, automated assessments, and behavioral interviews creates a fragmented experience that fails to evaluate candidates holistically, ultimately harming both companies and applicants.
Background
- The article argues that tech hiring has degraded from a genuine attempt to assess skills into a ritualized, multi-stage gauntlet that favors candidates who are good at the hiring process itself rather than good at the job.
- Key practices critiqued: take-home assignments that demand days of unpaid labor, blind algorithm screens that reject qualified candidates, "culture fit" interviews used to reject people who don't socialize like the existing team, and leetcode-style whiteboard problems that test memorization rather than engineering ability.
- The author points to a systemic incentive problem: recruiters and hiring managers are not penalized for false rejections (rejecting a good candidate) but are heavily penalized for false acceptances (hiring someone who fails), so the process is designed to be maximally conservative and burdensome.
- This connects to a broader trend in tech industry criticism: companies have shifted from "we need to hire fast" (2010s growth era) to "we need to avoid any hiring mistake" (post-2022 efficiency era), and the process has become worse as a result.