Once UI – open-source design system and UI library for Next.js

Hacker News

When I started my career and built my first design system, I was beyond excited. It took a lot of iterations, learning and 6 months of work to launch it internally. In the next job, I did it again, then at the following job, again… And no matter which company I worked for, 80% of the design system was the same. I’ve decided to work full-time on the design system I’ve always wanted, and today I’m launching and open-sourcing it. You can use it to build Next.js apps faster, and I’ve designed it in a way that it’s hard to go wrong with it: you can choose any settings, and you’ll end up with a beautiful UI that’s also functional and accessible. Check it out and share your feedback, I would greatly appreciate it!

Visit product View on Hacker NewsJul 18, 2024

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Actual performance

3points

Did not reach leaderboard

Launch Intel predictions

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

89%89% 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 · Strong signals: apps, open · Missing: mac, agents, macos

85%85% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Indie HackersFits the IH revenue-focused audience · Strong signals: started · Missing: supports, reddit linkedin, podcasting

78%78% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Strong signals: apps, month, way · Missing: mobile apps, ios, personal

53%53% 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

37%37% 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

15%15% 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.

Incorrect prediction on native model

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