Pu

Publish SEO optimized content to your NextJS project in minutes

Hacker News

Publish SEO optimized content to your NextJS project in minutes

We're all developers here, we like building stuff. But what's even more great is having people use what built. Thats why in my last project I decided to create some blog articles to drive traffic to my site and increase my userbase. It actually went really well and I found some keywords with low competition, so I decided: "Hey, why not build this in a way so I can use it easily accross all my other projects?" And that's exactly what I did! I built a developer focused minimalistic CMS, especially designed for creating and publishing SEO optimized articles to your NextJS project. My goal was to make the integration into your NextJS project as fast and painless as possible, through a shadcn-like cli. Installation time, including creating your first content, from start to finish is between 1-3 minutes. It's only two commands (actually only 1 if you are using npm and not pnpm or yarn). Of course excluding the time it takes you to build and deploy your application. Here are some of the features it comes with, out of the box: - Automatic Sitemap Generation - SSG with ISR, you can see content changes deployed instantly without rebuilding your application - Image Support Some of the features that are on my radar as a roadmap: - i18n support - Automatic image generation for articles - Pages router support - Scheduled publishing - Improved article editing experience with some QOL changes Google highly values how useful content is to the reader these days, so I highly recommend seeing the generated articles as a starting point and then editing them in the online dashboard! I would love your guys feedback! You can try it for free under https://nxtblog.ai Cheers!

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Actual performance

1points
Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Strong signals: including · Missing: supports, reddit linkedin, podcasting
90%90% 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: google, user, using · Missing: mac, agents, macos
82%82% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io, including · Missing: https docs, excited, just released
54%54% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
47%47% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: google, way · Missing: mobile apps, ios, personal
35%35% 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
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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