ResumaidPro – Tailoring Resumes Simplified

Hacker News

Hey HN! I built an app to tailor resumes to job descriptions. It has a Chrome extension and web app, with the extension being the main focus. Users can open it on supported job listings and hit "generate" to tailor their resume. The process: Upload base resume, open extension on listing or paste job description, review content, select template, and then download. You can edit and change the resume after you've generated it as well. You can also add cover letters and recruiter emails tailored to the job. The review step is important as I acknowledge AI isn't perfect and mistakes can be made (like lying), so with that review step, users can filter out things they don't want and also add information that may have been missed. I made this to help me tailor my resumes and have built a similar tool in the past, which inspired this one. I would love any and all feedback or ideas on what would make the tool more useful for you. Thanks! Younus Link --> https://www.resumaidpro.io/

Visit product View on Hacker NewsOct 15, 2024

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

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

46%46% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

45%45% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: users · Missing: plus, platform, intuitive

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TrustMRRLess likely to generate early MRR · Strong signals: users · Missing: mobile apps, ios, personal

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

14%14% 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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