Reimagining My CV as an iOS App

Hacker News

TLDR: The UX of viewing a PDF CV on a mobile device is subpar, so I tried designing a better experience. InVision link: https://invis.io/6AT12ROPEWN Details: I saw someone view my CV on a mobile device, trying to pinch and zoom their way to read the content. As a fun project, a way to differentiate myself in job applications (alongside my traditional CV and an excuse to learn Swift (which I am now starting), I decided to design something better. This is version 1.0, so any feedback or guidance would be very much appreciated :) Viewing notes: The prototype was made using Sketch and InVision. It is optimised for the iPhone X, working best when downloaded to the X’s home screen or when viewed on a laptop/desktop browser.

Visit product View on Hacker NewsSep 3, 2019

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Actual performance

4points

Did not reach leaderboard

Launch Intel predictions

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

85%85% 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.

Product HuntOn track for Day 1 leaderboard · Strong signals: using, notes · Missing: mac, agents, macos

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

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

50%50% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

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

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

44%44% 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

17%17% 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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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