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Retool Mobile

Hacker News

Retool Mobile

Hi all, founder @ Retool here. We initially launched Retool on HN five years ago: https://news.ycombinator.com/item?id=14515494 . The feedback was extraordinarily helpful then (e.g. we launched source control, on-prem, etc. based on HN comments), and we’re grateful for all of it. Today, we’re excited to get HN’s thoughts on one of our new products: Retool Mobile. It lets you build and deploy mobile apps in minutes, not days. The idea is there is a large class of line-of-business mobile apps, and the process of getting a simple form + button on a mobile device, in a native app, to POST back to an API endpoint, is startlingly difficult. (As a web developer myself, it has for a while been shocking how hard it is to build and ship something useful onto the app store.) For us, it was important that we build a native mobile app. That’s because although the web as a platform has come a long way, we think Apple / Google are — to some extent — anti-web, in the sense that they hamstring web developers in an attempt to get more apps on their app stores. With a native app, we were able to ship a brand new set of mobile-specific components, drive substantially more performance, and frankly — deliver much more delight. The team is currently hard at work on white labeling, offline apps, and push notifications. We expect to ship all that in the next few months. If you have any feedback on the product, please do comment in this thread! HN is a particularly valuable source of product feedback for us, and the team is very eager to please HN readers. (Since if we can do that, we can surely please any developer, hah!)

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Actual performance

226points
78comments
Made the leaderboard

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: apple, google, apps · Missing: mac, agents, macos
93%93% 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.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
86%86% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: excited, lua, ide · Missing: https docs, just released, exist
74%74% 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: mobile apps, apps, month · Missing: ios, personal, entrepreneurs
57%57% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform · Missing: plus, intuitive, reviews
31%31% 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
29%29% 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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