1UpBlitz – A SaaS Starter for Blitzjs

Hacker News

Hey HN Today I finally released 1UpBlitz. A SaaS start for the full stack react framewok - Blitzjs. For those who never heard of blitzjs, it's a full stack react framework. Think ruby on rails, but for React. You can learn more about it here https://blitzjs.com/ I chose blitzjs for these reasons: - Great dev community that I contribute to - Consolidates my previous tech stack with the use of magic - Already very stable with less and less breaking changes - Brings the ruby on rails vibe that I love to nextjs (react), which I also love So I created a SaaS starter. I finished a client's MVP in a matter of 2-3 weeks. 1UpBlitz comes with the following: - Create multiple plans - Plan upgrading and downgrading - Roles & Permissions for workspaces - Invite users to a workspace - File upload api routes and an included react-dropzone form component - Smart slug generator - Search & Paginated table component - End-to-end tested with cypress

Visit product View on Hacker NewsAug 30, 2021

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

78%78% 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: user · Missing: mac, agents, macos

59%59% 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

36%36% 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: users · Missing: mobile apps, ios, personal

33%33% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

33%33% 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

17%17% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: smart · Missing: web3, chat, crypto

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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