They ask the AI to build the entire project.

Something like:

“Build me a full SaaS app that does this”

The result?

A messy codebase.

AI tries to generate everything at once, and the architecture usually falls apart.

After experimenting with AI coding tools, I’ve found a workflow that works much better.

Think Like an Architect, Not a Prompt Engineer

The key idea is simple:

You design the system. AI helps implement pieces of it.

Instead of asking AI to generate the whole project, break it down.

You decide:

architecture

folder structure

data models

API design

Then AI helps implement one piece at a time.

A Better Workflow

Here’s the process that works well for me.

Design the architecture first Before asking AI for code, define:

project structure

database schema

API routes

major components

Example:

/api auth.ts users.ts

/services userService.ts

/components Dashboard.tsx

This prevents AI from inventing random structures.

Ask AI to build one file at a time Instead of:

“Build the backend”

Ask:

“Create an Express API route for user registration with email and password validation.”

Or:

“Create a React component for a dashboard that displays a list of projects.”

Small tasks = much better results.

Review and refine Never paste AI code blindly.

Check for:

unnecessary complexity

security issues

inconsistent patterns

AI is great at generating code, but developers are still better at judging it.

Use AI for boring work Where AI really shines:

boilerplate

tests

simple CRUD endpoints

documentation

refactoring suggestions

Let AI do the repetitive work.

Focus your time on system design and product decisions.

The Real Shift

AI doesn’t replace developers.

It changes the role of developers.

Instead of spending most of our time writing code, we spend more time:

designing systems

reviewing generated code

thinking about architecture

Which, honestly, is where the interesting problems are anyway.