Create a Darkmode with Minimal JavaScript

Hacker News

Hello everyone, I’m excited to share a new project I’ve been working on: I’m building a blog all about frontend development, with a big focus on CSS. The goal? Write articles that are not just informative but also fun, with interactive examples to help bring concepts to life. It could be anything from building a component to diving into more abstract topics. Since it’s my first time writing a blog, I’d really love to hear what you think! Feedback on the writing style, learning value, or anything else would be super helpful. Feel free to ask questions, drop suggestions, or just share your thoughts. Thanks a lot!

Visit product View on Hacker NewsNov 27, 2024

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

84%84% 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

80%80% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

57%57% 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 · Missing: mobile apps, ios, personal

45%45% 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 · Strong signals: active · Missing: arr, mrr, revenue

11%11% 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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