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Full-Stack DeveloperPortfolio · 2026

000
Case study · AI App

Habit Tracker AI

MERN habit tracker with Llama 3 powered improvement tips.

private build

Today · 4 habits

Keep the streak going

Morning run

86% this week

Read 20 pages

64% this week

Deep work

92% this week

Meditate

48% this week

AI

Suggestions · Llama 3

Tip 1

Stack your reading habit right after your morning run.

Tip 2

Meditation dips on weekends. Try a 5-minute version.

Tip 3

Block deep work before 11am, when you finish it most.

Client

Personal product

Role

Solo Developer

Category

AI App

Deliverables

Web app · REST API · AI service

Overview

A personal productivity app where users build daily habits, track completion with progress rings and receive three AI-generated suggestions to improve, served by Llama 3 through the Groq API.

Llama 3

AI model

3

Tips per request

MERN

Stack

Key features

What it does

JWT sign-up and login with protected routes
Create habits and mark them complete each day
Circular progress indicators on the dashboard
AI suggestion endpoint returning three personalised tips
Profile and settings management
Tech stack

How it is built

React 19
Vite 7
React Router 7
Node.js
Express 5
MongoDB
JWT
Groq
Llama 3
Engineering decisions

The thinking behind the build.

01

AI where it helps

The model sees the user’s habits and returns short, actionable tips instead of a generic chat box.

02

Fast inference

Groq’s low-latency Llama 3 endpoint keeps suggestions near-instant.

03

Lean full stack

A compact Express 5 API and React 19 client keep the product simple to run and extend.

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