Hacker News web app with 2 UI's and some additional features

Hacker News

Hello HN! Author here :) I've finished upgrading the Hacker News reading app that I made sometime earlier. Among previous features, I added some new ones - which include: - the ability to bookmark any story or comment, which you can read later, and the newly added comments are highlighted (the ones you did not see or read earlier); - the ability to search through comments, and find the one that you are interested in; - the ability to reply to comments (but you must be logged in at original news.ycombinator.com website to do so). The app is using offical HN API to get the data, and it's client side rendered. The technologies used for making this web app are: React (Router, Redux) and vanilla CSS. Let me know what you think about the app in the comments. Thanks!

Visit product View on Hacker NewsMay 31, 2022

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Actual performance

2points

Did not reach leaderboard

Launch Intel predictions

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Hacker NewsStrong engagement from HN community · Strong signals: hacker news, ide, io · Missing: https docs, excited, just released

67%67% 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 HuntOn track for Day 1 leaderboard · Strong signals: new, using · Missing: mac, agents, macos

65%65% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

61%61% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

42%42% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

31%31% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

13%13% 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

6%6% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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