I built a free diary for growth to replace doomscrolling

Hacker News

In the past few years, I read many self-improvement books and listened to podcasts that helped me grow. But after a while, I always forgot most of the lessons and slipped back into old habits. So I started writing short daily notes about what I learned and how I felt. It helped me stay focused, but I didn’t have a simple place to revisit those reflections. That’s why I built Bloomind. It helps me reflect daily, revisit my notes, and stay connected with my goals. It's just a few mindful minutes instead of doomscrolling. I built it with Kotlin Multiplatform, sharing logic between Jetpack Compose and SwiftUI. I would be more than happy to hear any feedback or thoughts. Also if anyone wants to support the app, please leave a review on the App Store or Play Store, that would mean the world to me.

Visit product View on Hacker NewsOct 28, 2025

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

76%76% 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.

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

46%46% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

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

Product HuntUnlikely to reach the leaderboard · Strong signals: notes · Missing: mac, agents, macos

37%37% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

35%35% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released

22%22% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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.

Correct prediction on native model

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