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I feed all my daily entries to an AI (ChatGPT)

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I feed all my daily entries to an AI (ChatGPT)

Hello there! I hope you're doing well today! I wanted to share something with you. Recently I was on the hunt for the best way to journal daily. Well, I had this idea - what if I could feed all my daily entries to an AI (ChatGPT), and create a friendly, supportive character like Socrates or Simon Sinek? This way, I could ask any questions about my life and mental health, and get some amazing advice on how to improve myself! The results have been absolutely mind-blowing ! I even made a short GIF to show you how it works - check it out! - https://gifyu.com/image/SdHLH I've shared this with my friends, and they loved it so much that they've been asking me to create a full-featured journalling app with an AI assistant! What do you think? Would you be interested in using an app like this? I'd love to hear your feedback and thoughts on this. Please feel free to drop a comment and let me know what you think! Right now, I'm just collecting a waitlist of people who are interested in the app, so if you're interested, here is a link for signup to waitlist - https://www.tryscrapbook.com/ .If I can get 100 people on the waitlist in the next few days, I'll launch the app!

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
79%79% 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: chatgpt, using · Missing: mac, agents, macos
77%77% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: way · Missing: mobile apps, ios, personal
43%43% predicted probability of success on TrustMRR, 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
33%33% 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: friendly · Missing: plus, platform, intuitive
31%31% 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
19%19% 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 · Missing: web3, crypto, cryptocurrency
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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