I Used AI to Build My Project… But Then I Had to Actually Understand It
When I built my social media automation platform, I used AI tools to generate a lot of the code. Everything seemed to work — login, dashboard, APIs. But when I looked deeper, I realized something i...

Source: DEV Community
When I built my social media automation platform, I used AI tools to generate a lot of the code. Everything seemed to work — login, dashboard, APIs. But when I looked deeper, I realized something important: I didn’t fully understand what was happening inside my own project. So I decided to slow down and learn the core concepts properly: JWT authentication, AES encryption, database design, and debugging. Here’s what I learned. Understanding JWT (Authentication) At first, I thought JWT was just a login token. But it’s more than that. A typical flow looks like this: User logs in → password verified → JWT created → frontend stores token → sends it in each request → backend verifies token → access granted JWT is essentially structured data that is signed using a secret key. Example: from jose import jwt from datetime import datetime, timedelta def create_token(email): return jwt.encode({ "sub": email, "exp": datetime.utcnow() + timedelta(minutes=60) }, SECRET_KEY, algorithm="HS256") Once I