Platform to practice front end problems

Hacker News

Hello everyone TLDR: I created a website(DevDrills): https://www.devdrills.io/ I recently realized whenever I wanted to practice frontend problems I just googled around, read articles or found questions which weren't auto evaluated. This made me think about creating a platform for devs where they can actually solve problems which we devs face in everyday life. My intention with the platform is to help people improve their development skills, help them learn about new concepts through problems and hopefully make a dent in how our industry conducts interviews(shift away from leetcode). The platform is still very young so it only has frontend problems currently and I am working on improving the test cases & adding more questions. Let me know what you guys think this or any feedback you have :). There might be a few bugs here and there but they should be gone soon.

Visit product View on Hacker NewsJun 11, 2022

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1points

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

74%74% 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: google, new, code · Missing: mac, agents, macos

54%54% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: lua, io · Missing: https docs, excited, just released

50%50% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRLess likely to generate early MRR · Strong signals: google, way · Missing: mobile apps, ios, personal

45%45% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

33%33% 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

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

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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