Way to Use AI for Coding
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.