GLinksWWW – A lightweight browser with 9 independent clipboards

Hacker News

Hi HN, I built a browser for power users who are tired of the "copy, switch tab, paste" loop. Key Features: 9-Segment Clipboard: Copy 9 different items (Ctrl+Shift+1-9) and paste them anywhere. Granular Cookie Control: Delete cookies for a specific site with one click (Great for privacy). Built-in AI Search: Direct access to Perplexity, Google, Brave, etc., from the home screen. Linux First: Native .AppImage and .deb support. It's a solo project, and I'd love to get some feedback on the performance. Download: https://drive.google.com/drive/folders/1_l4mEDoyERPMj_AXsvDC...

Visit product View on Hacker NewsJan 29, 2026

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Actual performance

4points

2comments

Did not reach leaderboard

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: google, user, perplexity · Missing: mac, agents, macos

65%65% 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 · Missing: supports, reddit linkedin, podcasting

62%62% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

AppSumoStrong fit for a featured deal · Strong signals: users · Missing: plus, platform, intuitive

59%59% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

39%39% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRLess likely to generate early MRR · Strong signals: google, users · Missing: mobile apps, ios, personal

32%32% 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

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

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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