Pair-programming interviews fail when they turn into a silent performance with an audience. Here is how to run one that feels like real collaboration and tells you something useful.
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Coding challenge sites and interview prep platforms measure something real, just not the thing you are hiring for. Here is what they catch, what they miss, and when to use them.
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Can ChatGPT report you for cheating in a coding interview? No. Here is what cheat detectors really do, why most of them fail, and the honest way to run an online code assessment in the AI era.
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Most AI-open interviews accidentally test how fast someone can prompt. Four design patterns that surface judgment instead of output.
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Whiteboard interviews measure memory and nerves more than engineering. Here is a hiring-without-whiteboards process that uses live coding in a real environment and still scales.
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A practical path to becoming a technical recruiter who engineers respect, from learning the stack to running tech screening that actually predicts who can do the job.
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If a model can pass your coding round, the round was not testing the right thing. The question is not whether AI will replace engineers. It is whether AI already broke your interview.
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You told the candidate they can use Claude. Now you are watching the recording. Here is what to actually look for.
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A candidate's public GitHub holds real signal if you know what to look for. And what to ignore.
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AI fluency is a real skill, but typing speed in a chat box is not it. Here is how to test if an engineer can actually work with AI tools.
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Live coding calls across time zones lose good candidates to fatigue and scheduling. Async technical interviews give you more signal in less calendar pain.
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A take-home should respect a candidate's time and still tell you who can ship. Here is how to design one that does both.
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