Learn to Code with Interactive Lessons

Hacker News

Back in 2018 when I was learning React on Codecademy, I realized their coding tutorials were frustrating because you needed to write the code exactly as they wanted, even if there were multiple ways to do it. Also the tutorial steps were not granular enough. If they ask you to write a for loop, you need to write the whole thing on your own, instead of being guided at step-by-step. Another thing that CodeCademy wasn't good at: teaching you the thinking process behind coding. It took me around 7 months to develop the interactive tutorial engine that improved on what CodeCademy offered.

Visit product View on Hacker NewsJun 21, 2023

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5points

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Did not reach leaderboard

Launch Intel predictions

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

65%65% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

64%64% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

63%63% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

39%39% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

30%30% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

20%20% 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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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