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Design as you build with ViewsDX

Hacker News

Design as you build with ViewsDX

Hey HN! Over the last months (or years, who's counting?!) we've been running many experiments with this simple goal in mind: We want to simplify writing code. Simplify it to the point where every designer, developer and product manager can be hands-on making, tweaking and improving the apps they create. We aim at removing the need for a hand-off. Would you like design interfaces as you build them? It's a long shot, but since we understood that design is engineering, we feel relentlessly excited about it. Today we are launching Preview of ViewsDX together with this super detailed tutorial https://learn.viewsdx.com/put-interfaces-together-like-lego-blocks-df5d30abcecb#.1kx24mvoy Stay creative and make stuff!

Visit productView on Hacker NewsFeb 7, 2017
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Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
89%89% 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: apps, code · Missing: mac, agents, macos
81%81% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: excited · Missing: https docs, just released, exist
72%72% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRFits verified-revenue profile · Strong signals: apps, month · Missing: mobile apps, ios, personal
60%60% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: interface · Missing: plus, platform, intuitive
34%34% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
18%18% 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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