The new Defringe, an online gallery

Hacker News

Hello there! The newest version of http://defringe.com has just launched. I consider this 4th version my biggest learning experience on the web. Hackernews - for me - is an important knowledge hub of programming and development. So I would like to explain some small things and ask for your opinions. > You can read the full article on our lessons learned & applied on Medium: https://medium.com/@defringe/lessons-learned-in-four-years-of-blogging-155eeb8e63d6 I have split the back- and frontend in order to update or move elements when I need to. Not when another party decides to. A new API sitting in between gives me the possibility to create an app on any platform in the future. Separating the backend means that we are no longer depending on a specific content management system. One system that caught my eye was Ghost. Defringe is going to work with Ghost when they release their full version this summer. Some other features that are worth mentioning are a video script that postpones loading and a seamless Tumbr integration. You can read all about it in the Medium article. Have a look. I would really appreciate your opinions and some constructive feedback. http://defringe.com Giel.

Visit product View on Hacker NewsJan 21, 2015

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

81%81% 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.

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

44%44% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

44%44% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

44%44% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released

41%41% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

16%16% 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.

Correct prediction on native model

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