OgBlocks – Animated React UI Library Built with Motion and Tailwind CSS

Hacker News

Hey HN, My name is Karan, and I'm a frontend developer from India When I started my development journey, I fell for frontend development and stuck with it ever since But I noticed that many of my friends hated writing CSS because creating UIs is a very tedious and time-consuming process. But at the same time, they also wanted their project to look premium with beautiful animations and a world-class user experience That's when I thought "What if anyone could integrate beautiful animated components into their website regardless of their CSS skills?" And after six months of pain and restless nights, I finally built ogBlocks to solve this problem. ogBlocks let you integrate beautiful and practical animated UIs with simple copy and paste, and its main purpose is to enable everyone to create beautiful UIs regardless of their CSS Skills I hope you'll like it Best Karan

Visit product View on Hacker NewsNov 28, 2025

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2points

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

86%86% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

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

80%80% predicted probability of success on Product Hunt, 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

50%50% 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

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

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

47%47% 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

13%13% 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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