🏗️Build a Web App with AI

From Idea to Architecture

Start with a problem, not a technology — let AI propose your project architecture and tech stack.

Setting Up the Project

Let AI scaffold your frontend and backend, set up git, and get a running dev environment in under an hour.

Building the Frontend

Describe pages in natural language and get production-ready React components with Tailwind CSS.

Building the Backend

Django models, REST API endpoints, social auth, and payment integration — all built by AI.

Teaching AI to Validate Its Own Work

The most important lesson: build, test, lint, type-check — never trust AI code that has not been executed.

Visual QA: The Missing Piece

Tests pass but the page looks broken — why visual testing matters more than unit tests for web apps.

Security: What AI Gets Wrong

AI-generated code has 2.74x more vulnerabilities — learn to catch and fix the security mistakes AI makes.

Deploying to Production

Frontend on Vercel, backend on a EUR 3.49 VPS with Kubernetes — the complete deployment pipeline.

Iterating and Maintaining

The app is never done — how to keep improving with AI agents, parallel workflows, and continuous deployment.

Backend Deep Dive: Models, Admin, and API

A deep dive into the Django backend — from data models through the admin panel to clean API endpoints. All with Claude Code.

Authentication and Payments

Social login via Google and LinkedIn, paywall for paid content, and payment gateway — complete purchase flow with AI.

AI Agents as a Team

How PraktickAI was actually built — architect, developer, reviewer, and QA agents working in parallel. The future of development.