I made a tool that makes React faster automatically

Hacker News

In brief: I'm Aiden, 18, and have spent the past 2 years of high school working on Million.js, an open source React alternative with 11K stars on GitHub and hundreds of thousands of npm downloads. Recently, I released automatic mode, which detects slow React components and automatically optimizes the reconciliation phase. It's still in beta but chugging along. It's around 70% faster than React on the JS Framework Benchmark and you can see how I did it here: https://million.dev/blog/virtual-dom Interested? Check it out here: https://million.dev

Visit product View on Hacker NewsAug 11, 2023

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

77%77% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

77%77% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

66%66% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

39%39% 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

21%21% 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

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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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