IntercoolerJs – A Declarative Ajax Framework

Hacker News

Hey All, It isn't 100% complete yet, but I've decided to cut a 0.0.1 release for IntercoolerJS: http://intercoolerjs.org/ Intercooler is a Partial View Controller framework, where AJAX responses are HTML fragments (partials) that are swapped in for existing content, based roughly on the Basecamp 2 approach. If anyone else is interested in working on or using the project, please let me know: there is still tons of interesting work to do (e.g. back-button/pushState() support) I think that, for many apps, this might be a good way to get 90% of the UX advantages of a thick Javascript MVC framework, at a fraction of the complexity.

Visit product View on Hacker NewsApr 7, 2014

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Product HuntOn track for Day 1 leaderboard · Strong signals: apps, using · Missing: mac, agents, macos

79%79% 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: exist, existing, ide · Missing: https docs, excited, just released

73%73% 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

56%56% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

37%37% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: apps, 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

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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