Br

Browse the first web site as if from the first web browser

Hacker News

Browse the first web site as if from the first web browser

I adapted the stylesheet from TimBL's WorldWideWeb/Nexus browser to CSS[1] and then applied the style to a mirror of the first web site at info.cern.ch. The result is that you can browse the first web site as it would have appeared in the first* web browser! [1]: https://git.sr.ht/~tweedy/WorldWideWeb-style * Ahem, technically...the stylesheet is adapted from the final version of Nexus (2.02, June 1994). However, the stylesheet was largely consistent throughout the lifespan of the browser.

Visit product View on Hacker NewsNov 18, 2022

Actual performance

1points

Did not reach leaderboard

Launch Intel predictions

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Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released

64%64% 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 HuntOn track for Day 1 leaderboard · Missing: mac, agents, macos

61%61% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

52%52% 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, personal

43%43% 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, podcasting

30%30% 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, revenue

18%18% 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

16%16% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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