I Made the Duolingo for Coding

Hacker News

I have been a duolingo user for quite some time and have been wondering why there isn't an app like that to teach people programming. Well, now there is. Our newly created platform is designed to teach coding in a fun, free, and easy way, accessible from any device. edCode offers bite-sized, interactive lessons designed to keep you engaged while learning at your own pace. Whether you're just starting out or brushing up on skills, we've made coding education simple, enjoyable, and effective. Some exciting features include: - Real-time leaderboard to add a friendly competitive edge - Certificates upon course completion to showcase your progress We’re still in the early stages of development, so your feedback is incredibly valuable as we shape the future of edCode. Head to our feedback page on the dashboard to share your thoughts—we’re quick to respond (within 24 hours)! Thank you for your support and we can’t wait to hear what you think!

Visit product View on Hacker NewsSep 28, 2024

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Actual performance

4points

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Did not reach leaderboard

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

82%82% 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: user, new, coding · Missing: mac, agents, macos

72%72% 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

59%59% 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: platform, friendly · Missing: plus, intuitive, reviews

49%49% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

32%32% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: active · Missing: arr, mrr, revenue

12%12% 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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