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CodeMentorGPT – Tool to help busy programmers to learn new languages

Hacker News

CodeMentorGPT – Tool to help busy programmers to learn new languages

Hello, here I scratched my own itch: as a busy full-time dev with family, I had NO time to learn new programming languages. So I launched CodeMentorGPT.com , an AI-powered solution to help people like me to stay up-to-date with the dev world. I went from idea to the project in 6 weeks for a NoCode challenge, and had my pitch to sell it on NoCodeSale on May 31th You can watch my Pitch here: https://youtu.be/87Gcwz0kRC4 Here to get any feedback to improve that. Thank you!

Visit product View on Hacker NewsJun 9, 2023

Actual performance

4points

Did not reach leaderboard

Launch Intel predictions

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

72%72% 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.

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

59%59% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

56%56% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

55%55% 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 · Missing: plus, platform, intuitive

21%21% 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

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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