Write,push code via your smartphone

Hacker News

Hi Gilbert, and maker of CodeTroll CI https://codetroll-app.firebaseapp.com, an app that helps you write, push code using your smartphone app. We are always bumping into constant changes as developers where your clients ask for changes constantly and if you're a long commuter like me who spends almost in total 4hrs each day, a tool that can help make small changes to any codebase comes handy. CodeTroll provides an easy interface to write code like a chat app, push functionality that connects to your favorite git clients. I am not sure if the problem is severe, but if you have any questions or feedback please reachout.

Visit product View on Hacker NewsAug 22, 2019

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Launch Intel predictions

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

80%80% 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.

TrustMRRFits verified-revenue profile · Strong signals: way · Missing: mobile apps, ios, personal

69%69% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

68%68% predicted probability of success on Indie Hackers, 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

47%47% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

39%39% 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

17%17% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: chat, smart · Missing: web3, crypto, cryptocurrency

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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