AI coding tools have made it much easier to build application interfaces. You can generate a landing page, create dashboards, and build a working prototype in a fraction of the time it used to take.
But there is another part of the application that still needs careful attention: the backend.
A real application needs somewhere to store data, manage users, enforce permissions, and expose functionality through APIs.
The problem behind the interface
Imagine building a project management application with an AI coding tool.
The interface looks great. You can create tasks, open dashboards, and navigate between pages.
But what happens when you refresh the page? Where is the data stored? How do you manage user access? How does the frontend communicate securely with the database?
These are backend problems, and they matter just as much as the interface.
Why I'm building ZendBX
I'm building ZendBX, a backend platform designed to help developers build and manage the backend infrastructure their applications need.
The goal is to make the journey from an idea to a working application simpler, especially for developers building with modern AI coding tools.
Instead of treating the backend as an afterthought, I want developers to have a clear path to connecting their applications to the services they need.
A practical example
Suppose you're building a simple notes application.
The workflow looks like this:
Build the frontend using Next.js or an AI coding tool.
Create a project in your backend platform.
Configure the application's connection to the backend.
Create a database table for notes.
Send a request to save a note.
Retrieve the saved note and display it in the interface.
Configure authentication and permissions before using real customer data.
The important part is that the application needs to save and retrieve real data—not just display a convincing interface.
What I'm focused on
With ZendBX, I'm focused on making backend development more approachable for developers building modern applications.
I'm particularly interested in how backend platforms can fit into workflows that use AI to generate code, prototypes, and complete applications.
There is still plenty to learn about what developers need most, and I want to keep improving the product around real-world use cases.
I'd like to hear from other developers
If you're building applications with Next.js, Lovable, Bolt, Cursor, or other AI coding tools, I'd love to hear about your backend workflow.
What do you currently use for your database and backend?
Which part of backend integration takes the most time?
What would make connecting an AI-generated application to a backend easier?
You can explore ZendBX here:
I'm interested in hearing how other developers approach this problem and what they think a better developer experience should look like.
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