A Laravel and Vue SaaS Boilerplate

Hacker News

I created a boilerplate for Laravel and Vue (Inertia) with the core features setup for starting a SaaS project allowing you to focus on what's important. The boilerplate includes Stripe for payments with Laravel Cashier and Mailgun integrarion. All on top of the Jetstream starter kit with the benefits of 2FA, session managment, account profile, auth, etc. Any and all feedback is appreciated and you can read more on the github repo page :)

Visit product View on Hacker NewsJun 22, 2024

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Actual performance

4points

Did not reach leaderboard

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

66%66% 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: stripe · Missing: mac, agents, macos

51%51% 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

35%35% 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

28%28% 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

22%22% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

20%20% 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

20%20% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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