FasterChrome – Navigate the Web Faster

Hacker News

https://chrome.google.com/webstore/detail/fasterchrome/nmgpnfccjfjhdenioncabecepjcmdnjg Before you click on a link, you hover over that link. When you have hovered for 65 ms there is one chance out of two that you will click. FasterChrome preloads the HTML of that link at that time, leaving on average over 300 ms for the page to preload. This noticeably improve page load times. For simple sites it even makes them instant. To prevent preloading links that trigger an action (such as logging out or deleting something) it doesn’t preload links with a query string. (Except links to HN comments!) It’s based on https://instant.page/, a library to make your website faster with the same technique.

Visit product View on Hacker NewsJul 20, 2019

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Actual performance

2points

Did not reach leaderboard

Launch Intel predictions

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

67%67% 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

58%58% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

48%48% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

47%47% 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

46%46% 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

16%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, crypto

4%4% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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