Anthropic has repeatedly overhauled its technical interview assessments as rapid improvements in its Claude models have made traditional take-home tests less effective at distinguishing human talent. Since 2024, candidates applying to Anthropic’s performance optimization team have been asked to complete a coding challenge, with the explicit allowance to use AI tools. According to team lead Tristan Hume, successive releases of Claude steadily narrowed the gap between top applicants and model output, eventually eliminating meaningful differentiation under fixed time constraints.
As Claude Opus 4 and later 4.5 matched or exceeded the performance of Anthropic’s strongest candidates, the company redesigned the test to focus on novel problem structures that current AI systems struggle to solve. The episode highlights how advances in AI-assisted coding are reshaping not only education and assessment, but also hiring practices inside leading AI labs themselves.
