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See Breakthrough – AI-Powered Action Plans to Overcome Fears

Hacker News

See Breakthrough – AI-Powered Action Plans to Overcome Fears

I built See Breakthrough (iOS & Android) to help people conquer fears and achieve personal goals using AI-generated action plans. Whether it’s public speaking, fitness, or any lingering phobia, the app creates step-by-step tasks, tracks progress via short video clips, and keeps you motivated with points, streaks, and leaderboards. AI for personalized activities via native Swift/Kotlin apps. A close friend’s severe travel phobia inspired me to build something that offers tangible, AI-guided steps—plus social accountability and gamification. How it Works: 1. Enter your goal/fear. 2. Get a personalized action plan with progressively challenging tasks. 3. Complete tasks, optionally record short videos, and earn points to climb leaderboards. I’d love your feedback on everything from the AI approach to the user experience. If you’ve ever tried (and failed) to tackle a fear or build a new habit, I’m especially interested in what you think could be improved. Any tips, critiques, or wild ideas are welcome! Thanks for checking it out. Links: https://seebreakthrough.com/ https://apps.apple.com/us/app/see-breakthrough/id6740042394 https://play.google.com/store/apps/details?id=com.socialkeyb...

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Actual performance

2points
Did not reach leaderboard

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Indie HackersFits the IH revenue-focused audience · Strong signals: ios · Missing: supports, reddit linkedin, podcasting
91%91% 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: apple, google, apps · Missing: mac, agents, macos
88%88% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Strong signals: ios, personal, apps · Missing: mobile apps, entrepreneurs, month
61%61% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: plus · Missing: platform, intuitive, reviews
44%44% 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
21%21% 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: ide, io · Missing: https docs, excited, just released
20%20% 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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