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A mobile gesture-based browser I have been working on. [iOS]

Hacker News

A mobile gesture-based browser I have been working on. [iOS]

A while back I had an idea of making a browser that "translated" mobile websites into a better experience for mobile. I didn't really know where to start but then I thought that the entire "container" experience of browsing websites on mobile could be better. I had some ideas and this is a mixture of many of them: * clear app launch with keyboard up to quickly search * "intelligent" search suggestions so you don't have to manage bookmarks/tabs that learns your browsing history and what sites you visit (lots of ideas here) * ad blocking * banners and "download the app" banner blocker (on some sites) * dark mode-ify websites * Easily re-run your query on other sites (reddit, youtube, etc) (similar to SWURL that was posted here) * Search helpers to quickly run your query where you want * Quickly create new tabs and swipe between them * Zoom gesture to enter full screen browsing mode that makes it feel like any website is an app! * A Video player bar that shows on pages with videos to easily control things like play/pause, airplay/chromecast, PiP, change playback speed, and more) * Customize the colors * Purely local, no data is sent to a server (i'm too lazy to do that) I think that's about all the ideas i've built in so far, but I have many others. And if you have cool ideas, feedback, bugs, complaints please join the Discord and lets chat!: https://discord.gg/Njd8uzCF8P I first wrote this app in React native and didn't touch it for months, I recently came across SwiftUI and decided to re-write it and ended up getting a bit carried away with how easy it was to build things in SwiftUI in such a short amount of time

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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: new, plain · Missing: mac, agents, macos
94%94% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Indie HackersFits the IH revenue-focused audience · Strong signals: ios · Missing: supports, reddit linkedin, podcasting
90%90% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Strong signals: ios, video, month · Missing: mobile apps, personal, entrepreneurs
53%53% predicted probability of success on TrustMRR, 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.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
43%43% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: arr · Missing: mrr, revenue, profit
23%23% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency
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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