I built a React Native boilerplate to ship mobile apps faster

Hacker News

Hey HN. I'm a developer and solopreneur. Few months ago I realized I was doing the same thing over and over again: set up onboarding flow, user authentication, payments, connect a DB... So I built ExpoShip for 3 reasons: 1. Save Time and focus on what matters: building a business. 2. Avoid headaches like setting up authentication or handling in-app payments. 3. Get profitable fast. I hope this boilerplate will be as helpful to you as it is for me. Would love your feedback. Rudolfs

Visit product View on Hacker NewsAug 12, 2024

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

80%80% 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

78%78% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

65%65% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRFits verified-revenue profile · Strong signals: mobile apps, apps, month · Missing: ios, personal, entrepreneurs

53%53% 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

38%38% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: profit, profitable · Missing: arr, mrr, revenue

30%30% 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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