Interbeing: AI-Powered Habit Tracking Meets Planetary Impact
Solo Founder, Product Designer & Developer
The Concept
An AI-powered habit tracker that connects personal behavior change to verified planetary impact—see exactly where your trees are planted, plastic is removed, or bees are protected on a map.
The Challenge
Traditional habit apps focus only on personal achievement. Users seeking environmental impact can't verify where their contributions go or see tangible results.
Technology Stack
Design & Development Process
Phase 1: Brand Development & Product Design (1 day)
Used ChatGPT for concept generation and Midjourney for visual inspiration. Built brand identity and product specs in Figma, including complete visual identity, mobile-first user flows, core screens, and personalized achievement system design.
Phase 2: AI Coach Development (1 day)
Built custom GPT clone trained on BJ Fogg's Tiny Habits principles using a simple RAG implementation. The system queries a behavior design knowledge base before generating personalized recommendations.
Phase 3: Core Feature Development (2-3 days)
Developed habit tracking with streak visualization, GreenSpark API integration for verified impact, interactive map showing contribution locations, timeline of all impact actions, daily emotion tracking, and personalized achievement system.
Phase 4: Testing & Iteration (1-2 days)
Personal testing, bug fixes, mobile optimization, and UI refinement based on usability issues.
Key Features
AI Behavioral Coaching
Personalized recommendations grounded in evidence-based Tiny Habits methodology
Verified Planetary Impact
Tree planting, plastic rescue, clean water, bee protection. See exact locations on map.
Personalized Achievements
Custom interface elements that adapt to user goals and celebrate milestones uniquely
Emotional Wellbeing
Mood tracking correlated with behavior patterns over time
Results & Learnings
What Worked
- • Rapid prototyping: Concept to functional prototype in 2 weeks
- • Validated core hypothesis: Users want verified impact alongside habits
- • Skill development: Learned modern dev workflows, AI integration
- • AI-assisted development: Built features beyond previous technical ability
What Didn't Work
- • Never reached production readiness (no payment integration)
- • Hit technical complexity ceiling without engineering support
- • Replit hosting costs ($25/month) unsustainable for demo
- • No monetization validation
Key Insights
Vibe coding is powerful for MVPs — Tools like Replit enable rapid hypothesis validation, but production applications require professional engineering, proper infrastructure, and scalable hosting.
This project demonstrated that the barrier to building has dramatically lowered—a non-engineer can build a multi-faceted application integrating AI, APIs, and complex user flows in two weeks with $80.
If I Built This Again
Technology:
Swift native iOS with Cursor/Claude Code
Process:
- • Comprehensive product spec upfront
- • Strict MVP boundaries
- • Plan production architecture from beginning
- • Bring in senior engineer as coach
Project Status: Demo/Portfolio Project
Demo available upon request in Replit environment