I built an AI mock interviewer for system design interviews

Hacker News

Hey HN! I'm Nathan and I built a free AI mock interviewer for system design interviews. How many of you have gone through the entire software engineering interview loop only to mess up on the single system design interview? We've all been there—acing the coding rounds only to stumble on that one crucial hour of system design. While there are plenty of resources to improve on system design—blogs, books, videos, and courses—none of these quite capture the real experience of an interview. The nearest would be paying any of the existing mock interview services $200+ for just one mock interview! Enter Interview Shepherd (www.interviewshepherd.com/), an AI mock interviewer designed to help you prepare for system design interviews as realistically as possible! What are Interview Shepherd's core features? Real-Time Speech to Speech: Engage in natural, conversational practice sessions with our AI, simulating a real interview environment. Currently 20+ different system topics Post-Interview Feedback: Get detailed feedback to understand your strengths and areas for growth. Interactive Whiteboard: Sketch and refine your system designs in real-time, just like during an actual interview. Live Transcription: Receive instant transcriptions of your interviews for easy review and improvement. Check it out today with the beta version for FREE and let me know what you all think! Still not convinced yet? Check out a demo: https://www.loom.com/share/0cd01ccc107e4d1386970a2d5196fd3d?...

Visit product View on Hacker NewsJun 25, 2024

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66%66% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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58%58% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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36%36% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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29%29% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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17%17% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

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0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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