Smol Web Hosting

Hacker News

Smol Web Hosting

let me introduce you a simple CMS without frameworks, and hosting that is based on this CMS. https://github.com/turboblack/HamsterCMS The great thing about CMS is that it has multi-templates, you can assign each page its own design (template) enjoy web 1.0 hosting - http://web1.0hosting.net/ hosting is a home for geeks, like geocities 30 years ago, but with one interesting change - you can run a blog, you can install a chat, use ready-made templates (there are already more than 80 of them), and administer your site even from under DOS (and many templates work in Internet Explorer 5 from `99) Since March, we have seriously expanded the functionality, and now it is a rather interesting platform with a social component, in addition, if you bring friends, you always receive an additional 500 MB for files, and so on every time, if there is a recommendation from you. For activity (initiative and assistance to the project) you can also earn additional space for files.

Visit product View on Hacker NewsJul 26, 2024

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Actual performance

2points

Did not reach leaderboard

Launch Intel predictions

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

83%83% 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.

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

58%58% 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 · Strong signals: platform, host · Missing: plus, intuitive, reviews

49%49% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: way · Missing: mobile apps, ios, personal

43%43% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: activity · Missing: mac, agents, macos

42%42% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

23%23% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

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

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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