Functional UI Kit – twin Figma and React component libraries

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Hey Hackers! My name is Alex and I’ve been working on this project for the past 8 months with the support of Figma Creator Fund. I’d love to hear your thoughts from your experience working with designers & component libraries. I started out in design and later got into coding, so I understand both sides really well. I did UX Design for 12 years at startups, at my own studio and at Wix, and then worked as a front-end dev at Wix for 2 more years. I've noticed a common problem: most component libraries work great for devs but not so well for designers. In my experience working with big teams, I've felt this frustration firsthand. Instead of focusing on making products, we end up arguing over small details and terms. In Functional UI Kit, each comp has dedicated story in Storybook. Copy pasting from Dev Mode in Figma just works, Figma variables and CSS variables match, auto Layout is mirroring the same box model structure & the CSS architecture shields you from style collisions. It leverages all the latest Figma features to the MAX. Including the latest: Annotations, and of course: Dark Mode. I hope you try it and let me know what you think.

Visit product View on Hacker NewsFeb 25, 2024

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

92%92% 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 · Strong signals: started, including · Missing: supports, reddit linkedin, podcasting

92%92% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: ide, io, including · 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.

TrustMRRLess likely to generate early MRR · Strong signals: month · 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

29%29% 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

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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