Ra

Random Positive Reward App for iPhone

Hacker News

Random Positive Reward App for iPhone

I built an iPhone app that is now available in the App Store. Its purpose is to make it easy and effective to use intermittent positive reinforcement as a motivation tool - the psychological phenomenon behind doom-scrolling, gambling, and animal training, now finally purposed for your benefit. It provides the tools to manage the little treats your brain needs to move in the right direction, combined with gamification designed to support your journey and encourage healthy usage. This is the outgrowth of a “scratch your own itch” project when I learned about how variable reward schedules and wanted to be able to use it to break through times of lower motivation. While simpler alternatives like rolling a (virtual) d20 worked to prove the concept, there was a lot of room for improvement. There’s a system for dynamically weighting outcomes inspired by how RNG-heavy video games avoid big streaks of wins/losses. The other big idea was building anticipation into the app itself in the form of gamification so even if your rewards themselves aren’t really getting you into the right headspace at some time, there’s something to work towards in-app to add an extra boost. SwiftUI for presentation, Rust for business logic in case it ever pencils out business-wise to port to another platform. If I was doing it again starting today, I would probably do React Native for the UI, but the integration story with Rust was pretty weak when I was evaluating options (they work together well enough now, and I have another project combining them, but not able to justify a UI rewrite yet). CTA: this is a niche product in a (currently) non-existent market category. I’m starving for feedback, so if you have opinions about the app or even just the problem space, please let me know (comments here, App Support link from App Store, or messages to TantalusPath on social media), and I’ll eat it up! TantalusPath https://apps.apple.com/us/app/tantaluspath/id6504832898

Share card

Actual performance

3points
Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
87%87% 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, apps · Missing: mac, agents, macos
53%53% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: apps, video · Missing: mobile apps, ios, personal
49%49% 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
42%42% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: exist, lua, ide · Missing: https docs, excited, just released
34%34% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Acquire.comPre-revenue stage for this audience · Strong signals: growth, training · Missing: arr, mrr, revenue
17%17% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: reward · 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

Similar products

Ne
Nezumi 2, iPhone app for Heroku35%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Nezumi 2, iPhone app for Heroku

Hacker News7
Re
Released My IPhone App (Finderous)50%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Released My IPhone App (Finderous)

Hacker News4
My
My first iPhone app, TrackMate39%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

My first iPhone app, TrackMate

Hacker News1
My
My first iphone app was accepted39%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

My first iphone app was accepted

Hacker News3
Pa
Parked for iPhone, my first app39%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Parked for iPhone, my first app

Hacker News2
Pr
Prayer Intentions - My First iPhone App39%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Prayer Intentions - My First iPhone App

Hacker News2
Dr
Drinkups (my first iPhone app)39%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Drinkups (my first iPhone app)

Hacker News1
Si
Sightstream - my 2nd iPhone app39%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Sightstream - my 2nd iPhone app

Hacker News3
iP
iPhone App Detects your Movements through Ultrasound40%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

iPhone App Detects your Movements through Ultrasound

Hacker News3
iP
iPhone Karate App33%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

iPhone Karate App

Hacker News1