Today I Am A – A Playful SwiftUI App for Daily Affirmations

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I aimed to create an app that efficiently adds a positive outlook to someone's day. Many people appreciate and enjoy a label, and I have personally benefited from daily affirmations. Combining these elements, I developed "Today I Am A: A Daily Persona" entirely in SwiftUI and SwiftData. The app is designed to be opened at the start of each day, assigning users a unique persona. Each persona comes with a coordinated affirmation, merging your new identity with a positive outlook. Recently, I added HealthKit integration, widget support, and Apple Watch compatibility. Any and all feedback is greatly appreciated! App Link: https://apps.apple.com/us/app/today-i-am-a-daily-persona/id6...

Visit product View on Hacker NewsJun 17, 2024

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

84%84% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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TrustMRRFits verified-revenue profile · Strong signals: personal, apps, users · Missing: mobile apps, ios, entrepreneurs

55%55% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

44%44% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: apple, apps, user · Missing: mac, agents, macos

35%35% predicted probability of success on Product Hunt, 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

32%32% 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 · Missing: arr, mrr, revenue

22%22% 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

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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