Vibe coding has changed how developers build software.
You can describe a feature to an AI coding assistant and get working code in minutes. That is incredibly powerful.
But there is a problem:
Generating code is easy. Building a scalable application is not.
For serious projects, I don't think the best approach is:
“Give AI a prompt and let it build everything.”
A better approach is to give AI structure, rules, and context before asking it to generate code.
1. Start With Requirements
Before writing code, define what the application actually needs.
Think about:
- Who will use it?
- What features are required?
- What data needs to be stored?
- What are the business rules?
- Who can access what?
- What integrations are needed?
- How large could the application become?
This gives the AI a clear target.
2. Design the Architecture
Next, define the basic architecture:
Frontend → API → Backend → Database → External Services
Decide important things such as:
- React or Next.js
- REST or GraphQL
- PostgreSQL or another database
- Authentication
- Caching
- Background jobs
- File storage
Don't start generating hundreds of files yet.
3. Design the Database First
For most applications, the database is one of the most important foundations.
Define your:
- Tables
- Relationships
- Primary keys
- Foreign keys
- Constraints
- Enums
- Indexes
I also like generating an ERD using Mermaid before creating the actual database.
This makes the relationships easy to review before implementation.
4. Create and Optimize the Database
Once the schema is approved, create the database and migrations.
For PostgreSQL, don't blindly add indexes everywhere.
Think about the queries your application will actually run.
For example:
- Which columns are frequently searched?
- Which columns are used for sorting?
- Which columns are used together in filters?
- Are there slow joins?
- Are queries returning unnecessary data?
Use tools such as EXPLAIN ANALYZE to understand real query performance.
The best index depends on the query.
5. Build the Backend From the Design
Now AI can generate the backend based on the approved architecture and schema.
A simple structure might be:
Controller → Service → Repository → Database
Then add:
- Validation
- Authentication
- Authorization
- Error handling
- Transactions
- Logging
- Rate limiting
The important part is that AI should follow the architecture rather than inventing a new structure for every feature.
6. Define the API Contract
Before connecting the frontend, define the API clearly.
For each endpoint, specify:
Method + URL + Request + Response + Errors + Authentication
This prevents the frontend and backend from slowly becoming inconsistent.
7. Build the Frontend
Now connect the frontend to the API.
A clean flow is:
UI → State → API Client → Backend
Keep API calls organized instead of scattering raw requests throughout components.
Also handle:
- Loading states
- Error states
- Empty states
- Authentication
- Validation
- Optimistic updates when appropriate
8. Test Before Shipping
AI can generate tests too, but generated tests aren't enough.
Actually run them.
Test:
- Database constraints
- Services
- API endpoints
- Authentication
- Permissions
- Important user flows
- Edge cases
A test that nobody runs doesn't protect your application.
9. Security and Performance
Before production, review:
- Authentication
- Authorization
- Input validation
- SQL injection
- XSS
- Rate limiting
- Secrets
- File uploads
- Sensitive data exposure
For performance, measure first and optimize second.
Find the actual bottleneck instead of optimizing everything because AI suggested it.
The Real Meaning of Vibe Coding
I don't think the future is about developers disappearing.
I think it's about developers becoming better at directing AI.
Instead of:
“Build my entire application.”
Try:
“Here is my architecture, database schema, API contract, coding standards, and constraints. Implement this feature, explain the changes, and verify it with tests.”
That's the difference between AI-generated code and AI-assisted engineering.
AI can write a lot of code.
But you still need to design the system.
