Lagan AI Habit Tracker

Lagan is an AI habit tracker that turns your day into a simple timeline of habits — with a coach that notices your patterns and makes the next step clear.

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Inspiration

Staying consistent with habits is difficult—even when we know exactly what we should do. Many habit trackers eventually become another checklist, and missing a few days can make people feel like they have failed.

I wanted to create something more motivating: an app that makes progress visible, turns consistency into a rewarding experience, and uses AI to provide meaningful guidance. That idea became Lagan AI Habit Tracker.

I started building Lagan from scratch as a solo developer. Over five months, I learned while building, worked through countless late nights, invested my own money, and handled every part of bringing the product to life.

What it does

Lagan is an AI-powered habit tracker that helps people build habits that stick.

Users can create and complete habits, build streaks, earn XP, level up, unlock badges, and track their consistency over time. Lagan also generates an AI-powered weekly report that highlights progress, identifies the strongest habits, and suggests what to focus on next.

The app includes progress heatmaps, weekly momentum tracking, reminders, leaderboards for friendly competition, and automatic step and sleep tracking through Apple HealthKit and Android Health Connect.[1]

How we built it

Although this is a solo project, I built Lagan as a production-ready cross-platform application using React Native, Expo, and TypeScript.

The backend runs on Supabase, which handles authentication, the PostgreSQL database, and real-time leaderboard updates. Habit completions are updated immediately on the device and synchronized with the backend, where XP, streaks, levels, and progress are calculated.

Google Gemini generates personalized weekly reports through a secure Supabase Edge Function. RevenueCat manages subscriptions, while PostHog and Sentry provide product analytics and error monitoring. The app also integrates with HealthKit and Health Connect for step and sleep data.[1]

Challenges we ran into

The biggest challenge was building everything alone. I had to switch constantly between being a developer, designer, product manager, tester, marketer, and customer-support person.

From a technical perspective, some of the hardest problems included:

  • Keeping local and cloud data synchronized reliably
  • Making XP, streaks, and progress calculations consistent
  • Supporting different health platforms on iOS and Android
  • Protecting AI credentials by keeping them off the client
  • Implementing subscriptions across the App Store and Google Play
  • Managing authentication, notifications, analytics, testing, and releases
  • Delivering a smooth experience even when the network is unreliable

Another major challenge was realizing that completing the app was not the finish line. Building the product was only half of the journey; getting people to discover, trust, and continue using it became the next challenge.

Accomplishments that we're proud of

My proudest accomplishment is turning Lagan from an idea into a real product with active users and paying customers.

Lagan is not simply a prototype or hackathon demo. It is a working application with AI reports, gamification, health integrations, real-time leaderboards, subscriptions, analytics, and production monitoring.

Seeing someone use—and pay for—something I created from zero has been one of the most rewarding moments of this journey. I am also proud that I shipped the complete product independently while learning many of the required technologies along the way.

What we learned

The most important lesson I learned is that writing the code is only one part of building a successful product.

A great product still needs clear positioning, distribution, marketing, user feedback, and continuous improvement. Shipping early and learning from real users is more valuable than waiting endlessly for perfection.

I also learned that AI should not be added simply as a feature. It must provide useful, personalized guidance that helps users take their next step. Most importantly, I learned that persistence matters—especially during the long periods when progress is happening but results are not yet visible.

What's next for Lagan AI Habit Tracker

The next phase is focused on improving retention, personalization, and growth.

Planned improvements include:

  • Partial-progress tracking so smaller wins still count
  • Streak freezes and repairs to create a less guilt-driven experience
  • Home-screen widgets and faster habit logging
  • A proactive daily AI coach and conversational AI support
  • Smarter, adaptive reminders
  • More personalized and actionable weekly reports
  • Shared challenges, referrals, and stronger social accountability
  • Deeper insights connecting habits with step and sleep data

Alongside product development, I will focus heavily on marketing, distribution, and learning directly from users. My goal is to turn Lagan into a successful product and use everything I learn from this journey to build even bigger projects in the future.[1]

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