Ne
Newspaper-style HN reader (PWA) with articles and comments side by side
Hacker NewsNewspaper-style HN reader (PWA) with articles and comments side by side
I built a newspaper-style Hacker News reader where you can read articles and comments in one view. Sites that block iframes (Substack, Medium, BBC) get a clean reader mode automatically. It's a PWA, has dark mode, and there's a weekly newsletter. Open source: https://github.com/terryds/hackernewstimes
Share cardActual performance
1points
Did not reach leaderboard
Launch Intel predictions
Analyze your own launch →Hacker NewsStrong engagement from HN community · Strong signals: open source, hacker news, ide · Missing: https docs, excited, just released68%68% 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: new, open · Missing: mac, agents, macos48%48% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive40%40% 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, personal33%33% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting32%32% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue16%16% 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, crypto5%5% predicted probability of success on BetaList, based on ML models trained on real launch data.
Incorrect prediction on native model
Similar products
An
Android HN reader with collapsible comments58%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Android HN reader with collapsible comments
Hacker News1Katalog68%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Audio-first articles reader
Indie Hackerscommitment-side-projectRe
Reader – Curated Articles for You52%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Reader – Curated Articles for You
Hacker News5So
Soundcloud-style time-tied comments for YouTube50%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Soundcloud-style time-tied comments for YouTube
Hacker News3So
Soundcloud-style time-tied comments for YouTube50%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Soundcloud-style time-tied comments for YouTube
Hacker News2Si
Simple reader of the top voted articles of news and worldnews subreddit51%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Simple reader of the top voted articles of news and worldnews subreddit
Hacker News1Em
Embeddable hackernews comments69%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Embeddable hackernews comments
Hacker News3Le
Lectio, contextualized comments for lectures75%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Lectio, contextualized comments for lectures
Hacker News21Co
Collapse HN Comments54%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Collapse HN Comments
Hacker News141Fl
Flocking comments63%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Flocking comments
Hacker News3