72H Fasting Contest

The description states that 72H Fasting Contest is a native iPhone app for tracking 72-hour fasting challenges. The author describes it as a motivation and tracking tool, not a medical device. It includes features like live timer, milestone notifications, leaderboards, private contests, and anonymous sign-in. The app uses SwiftUI, Firebase, and AI tools (Codex + GPT-5.6) in its development but does not call OpenAI APIs at runtime.

Key commercial signals:

• No evidence of revenue or customers.
• The app is self-contained and built by one person.
• It targets individuals participating in 72-hour fasts, potentially with social accountability elements.
• Pricing and business model are not described.
• Technical implementation involves Firebase and offline fallbacks.
• No traction or user growth data provided.

The description states that 72H Fasting Contest is a native iPhone app designed for tracking 72-hour fasting challenges. It includes:

• A live timer and progress view
• Milestones at 12, 24, 36, 48, 60, and 72 hours
• Local reminders and milestone notifications
• History, statistics, streaks, rankings, and achievement badges
• Global and weekly leaderboards
• Private contests with invite codes
• Anonymous sign-in without email, phone, or password

The app asks users to accept a safety agreement before uploading data. It is described as a motivation and tracking tool, not a medical device.

Inference The app appears to be a personal wellness or challenge-tracking application focused on intermittent fasting.

The description states that the app was inspired by the desire to turn an abstract 72-hour goal into a sequence of milestones, add optional social accountability, and keep safety information visible throughout the experience. The author positions it as a way to track fasts with motivation and community elements.

Inference The positioning evolved from a simple timer to a structured challenge with social features and safety considerations, suggesting an intent to make fasting more approachable and accountable.

The description states that the app is for individuals participating in 72-hour fasts. It includes features like leaderboards and private contests, implying a community or competitive element.

Inference The target customer likely includes people interested in intermittent fasting who want structured tracking, social motivation, and accountability. The anonymous sign-in suggests a low-friction onboarding approach for casual users.

The description does not state anything about pricing, monetization, or business model. It only describes the app's functionality and technical implementation.

Not evidenced.

The description states that:

• The app is built using SwiftUI and a shared AppViewModel.
• Codable models are used for profiles, fasting sessions, contests, badges, and preferences.
• Firebase Authentication and Cloud Firestore are used for backend services.
• A ContestBackend protocol separates UI from domain workflow with offline/local fallbacks.
• Realtime listeners power leaderboards.
• Firestore security rules validate ownership, permitted fields, contest membership changes, elapsed-time limits, and session state transitions.
• Server timestamps prevent early completion by changing local clock.
• Codex and GPT-5.6 were used during development but not in runtime.

Inference The app has a modern iOS architecture with backend integration and offline capabilities. AI was used for development assistance, not for product delivery or runtime functionality.

The description does not provide any evidence of traction, revenue, or user adoption beyond the author’s own development efforts. It mentions:

• A public GitHub repository
• A demo video
• Manual acceptance checklist and build instructions

Not evidenced.

The description does not mention competitors or market positioning relative to other fasting or wellness apps.

Not evidenced.

• The app is built by a single developer, with no evidence of team or institutional support.
• No revenue, customer base, or user metrics are provided.
• The app is described as a hackathon project (submitted to OpenAI 2026 hackathon), suggesting early-stage development.
• It does not collect medical data but still requires safety consent — this may raise regulatory questions if scaled.
• Use of AI tools for development raises concerns about reproducibility or dependency on proprietary tools.

Inference The lack of traction, team size, and business model makes it difficult to assess commercial viability. The app is likely in a very early stage.

1. What is the intended path from prototype to product?
2. Are there any plans for monetization or revenue generation?
3. How does the team plan to scale beyond one developer?
4. Has the app been tested with real users, and what feedback has been received?
5. Is there a roadmap for future features or platform expansion (e.g., Android)?
6. What are the legal or regulatory considerations around safety agreements in this context?