StackHive – Live Web Coding and Visual Styling from the Browser

Hacker News

StackHive is a browser based website development tool that helps developers and designers in saving a majority of their development time. Packed with a live code editor, importing existing websites and a visual editor; StackHive brings the best of both worlds (Visual Editing and Full Code Control) to responsive website development and converts the browser into a fully functional and extremely capable IDE for static web development. We just released it a few days back and would love to get some feedback from the developers out there who struggle with front-end development! You can check it out http://stackhive.com

Visit product View on Hacker NewsDec 15, 2014

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Product HuntOn track for Day 1 leaderboard · Strong signals: visual, coding, code · Missing: mac, agents, macos

89%89% predicted probability of success on Product Hunt, 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: just released, exist, existing · Missing: https docs, excited, lua

84%84% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

70%70% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive

51%51% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

49%49% 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

13%13% 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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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