DailyBrew is a lightweight habit tracking platform designed to help people understand their daily coffee consumption through clear, AI-generated insights.
The product was built as a real MVP to validate how fast an insight-driven product can be designed, executed, and shipped using modern AI-assisted tools.
The Challenge
Most habit tracking products fail due to friction and generic insights.
The challenge was to design an MVP that:
Encourages daily consistency with minimal input
Generates meaningful insights instead of dashboards
Uses AI to reduce complexity rather than add it
My Role
End-to-end ownership of the product:
Product concept and MVP definition
UX and UI design
Data structure and insight logic
Full implementation using Lovable
AI-powered insights via Gemini API
Product Approach
Key product decisions:
Minimal input to prioritize habit consistency
No gamification or complex dashboards in the MVP
Automatic AI-generated insights over manual analysis
Visual hierarchy focused on behavior patterns
This approach allowed fast validation and clear direction for future product iterations.
Product & Execution
Users log coffee consumption and receive insights such as:
Daily intake
Frequent coffee hours
Preferred coffee types
Weekly consumption trends
Execution highlights:
Built and deployed using Lovable
Insight generation powered by Gemini API
Visual assets created using AI-assisted tools
Outcome
A fully functional, live MVP that:
Transforms small daily inputs into meaningful insights
Demonstrates AI-assisted product execution
Clarifies what a phase two of the product would require