DailyBrew | Making coffee habits visible, one cup at a time

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.

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

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

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.

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

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

DailyBrew reflects my approach to product design:

Strong MVP thinking and product judgment

Clear decision-making over feature volume

AI used as a practical enabler of insight

End-to-end execution from idea to live product