V1 – An open-source starter kit for your next project

Hacker News

Introducing v1: a free, open-source starter kit for your next project, built with insights from Midday. This monorepo is designed for rapid development, using the best tools and services available today. It includes Next.js and Supabase for a robust foundation, along with: * Sentry - Error monitoring * Resend - Email delivery * Triggerdotdev - Background jobs * Dub - Sharable links * Upstash - Cache and rate limiting * OpenPanel - Analytics * Polar - Billing * Vercel - Hosting We have handpicked the best libraries in the ecosystem: * Shadcn - UI components * React Email - Email templates * react-safe-action - Server actions * nuqs - Type-safe Search params * next-themes - Theme manager * Turborepo - Build system * Biome - Linter, formatter We hope you enjoy it as much as we do! We'd love to hear your feedback and see what you build!

Visit product View on Hacker NewsAug 31, 2024

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Actual performance

58points

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Made the leaderboard

Launch Intel predictions

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

79%79% 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: email, using, open · Missing: mac, agents, macos

63%63% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

AppSumoStrong fit for a featured deal · Strong signals: host · Missing: plus, platform, intuitive

53%53% predicted probability of success on AppSumo, 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

46%46% 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: para · Missing: mobile apps, ios, personal

29%29% 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

14%14% 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

3%3% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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