I Made an App Called PrepPro – AI Interview Prep Tool

Hacker News

Hey HN, I’m excited to share PrepPro, an AI-powered app designed to help you ace your job interviews with confidence. As someone who has gone through the nerve-wracking process of job hunting, I wanted to create a tool that makes interview preparation easier and more effective. Features: AI-Powered Tools: Leverage GPT-3.5 Turbo (GPT-4 Coming Soon) to generate tailored interview questions and practice your answers. Self-Interview Practice: Use our simple webcam interface for mock interviews. No recordings, just practice. Unlimited Generations: Practice as much as you need without any limitations. Comprehensive Support: Get tips, strategies, and support to improve your performance. Pricing: PrepPro Plus: $9.99/week with a free trial option. Unlimited access to AI tools Self-interview practice sessions Dedicated customer support Why PrepPro? Tailored Preparation: Personalized interview questions based on your job role and industry. Convenient Practice: Practice anytime, anywhere with our user-friendly interface. Boost Confidence: Repeated practice helps reduce anxiety and build confidence for the real interview. We’d love to hear your thoughts and suggestions to make PrepPro even better. https://x.com/JayPateln7/

Visit product View on Hacker NewsJun 23, 2024

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Indie HackersFits the IH revenue-focused audience · Strong signals: para · Missing: supports, reddit linkedin, podcasting

81%81% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

AppSumoStrong fit for a featured deal · Strong signals: plus, friendly, interface · Missing: platform, intuitive, reviews

59%59% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Strong signals: personal, answers, para · Missing: mobile apps, ios, entrepreneurs

51%51% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: user, recordings · Missing: mac, agents, macos

35%35% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: excited, ide, io · Missing: https docs, just released, exist

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

nativeThis product was originally launched on this platform.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

11%11% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

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

Correct prediction on native model

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