Mindmapping wasn't working for me, so I fixed it

Hacker News

I decided to build an unorthodox but extremely useful (at least to me) approach to mindmapping: Dealing with things one at a time. Instead of being bombarded with hundreds of nodes, graphics and text when a mindmap gets large enough. Brainstorms aims to show the nearest connections to a node, allows you traverse through them as your curiosity guides you and most importantly, retrace your steps. It also has a cool fuzzy finder so you can go straight to the state of a particular node in mind and iterate from there. This app is also just more fun and intuitive to use than existing mindmapping software out there which can feel bloated or extremely outdated.

Visit product View on Hacker NewsMar 29, 2025

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

62%62% 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 HackersIH features products with proven revenue · Strong signals: ios · Missing: supports, reddit linkedin, podcasting

48%48% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

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

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

43%43% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

30%30% 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

16%16% 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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