Li

Linklever makes the concept of default browser obsolete

Hacker News

Linklever makes the concept of default browser obsolete

Hi fellow nerds. Linklever is a local and offline browser launcher. If you're often copy-pasting URLs between browsers, then Linklever might be for you. It registers as your system's default browser. In the app, you configure rules and filters. Later, when you click a link outside of a browser, the rules determine which browser Linklever sends the link to. The filters transform the URL before sending it to the browser. For routing links between browsers, there are Firefox and Chrome extensions. Browser launchers are no new concept; AlternativeTo lists 17 others, but so far Linklever is the only one that supports macOS, Windows, and Linux. It's also pretty darn fast, being AOT compiled. Launch latency is typically 10-20ms, which is unbelievable for .NET. Tech stack: C#, Avalonia, SQLite. I'm also the author of the open source app BrowseRouter, whose moderate star count on GitHub was the inspiration to make Linklever. I'm following a business bootstrapping stair-step method. This is my second product. I started working on it in Dec 2024 and launched it officially in July. I've made five sales so far, which has been a lot of fun. I'm open to your feedback. Thanks for reading.

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Product HuntOn track for Day 1 leaderboard · Strong signals: mac, macos, new · Missing: agents, agent, cursor
83%83% 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.
Hacker NewsStrong engagement from HN community · Strong signals: open source, 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.
Indie HackersFits the IH revenue-focused audience · Strong signals: supports, started · Missing: reddit linkedin, podcasting, created
64%64% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
35%35% 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
23%23% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
20%20% 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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