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Posted on • Originally published at aicoreutility.com

AI Landing Page Generator Backend Design and Documentation

#ai #api

Backend Design and Documentation for AI Landing Page Auto-Generation Service

When I started developing the AI-based landing page auto-generation service, I felt lost about how to plan and technically approach it. I had a gut feeling that if I didn't take care of documentation from the very beginning, I'd definitely regret it later. So, this post is about sharing the process I went through and its outcomes.

Trials and Traps

At first, I just focused on implementing the features. I thought I could somehow manage integrating the AI model and outputting the results via an API. But as I started development, I realized I hadn't put enough thought into how to manage this feature and how to present it to users.

The core functionality was somewhat shaped, but the lack of documentation to explain it caused confusion. With no information about this new feature on the admin page, nobody knew how to use it.

Cause

Ultimately, the biggest problem was overlooking the creation of planning and technical documentation when developing new features. It wasn't just about quickly building a feature; the process of clearly defining its purpose, how it works, and how to use it was missing. Additionally, failing to consider adding related UI components and pages, and integrating them into the admin page, was also an issue.

Solution

To solve this, I rewrote the planning and technical documentation for the AI-based landing page auto-generation service from scratch. I concretely defined the overall service flow, the interface with the AI model, and the API specifications.

# AI-Powered Landing Page Auto-Generation Service Technical Documentation

## 1. Overview
This document describes the backend design and implementation details of a service that automatically generates landing pages based on user input using AI.

## 2. System Architecture
- **API Gateway**: Receives all external requests and routes them to the appropriate service.
- **Landing Page Generation Service**: Receives user requests, calls the AI model, and returns the generated landing page data.
- **AI Model Service**: Hosts the AI model that generates HTML, CSS, and JavaScript code based on text input.
- **Database**: Stores generated landing page data, user information, etc.

## 3. API Specifications

### 3.1. Landing Page Generation Request
- **Endpoint**: `/api/v1/landingpages/generate`
- **Method**: `POST`
- **Request Body**:
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json
{
"prompt": "AI-based service introduction landing page, concise and professional design",
"userId": "user123"
}

- **Response Body**:
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json
{
"landingPageId": "lp_abc123",
"htmlContent": "...",
"cssContent": "body { ... }",
"jsContent": "console.log('Hello');",
"createdAt": "2026-07-16T10:00:00Z"
}


### 3.2. Retrieve Generated Landing Page
- **Endpoint**: `/api/v1/landingpages/{landingPageId}`
- **Method**: `GET`
- **Response Body**: (Same as 3.1. Response Body)

## 4. AI Model Integration
- The AI model used is assumed to be OpenAI GPT-4 or a model with similar performance.
- Prompt engineering will be used to guide the generation of landing pages with the desired style and content.

## 5. Admin Page Integration
- Provides functionality to view a list of generated landing pages and their details.
- Allows checking the generation history and related data for each landing page.
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Along with this, I added the UI components and pages that would integrate with this feature, and created a documentation tab for this feature on the admin page to improve accessibility.

Result

  • The implementation and documentation for the AI-based landing page auto-generation service are complete.
  • Related UI components and pages have been added, improving the user experience.
  • A documentation tab for this feature has been added to the admin page, enhancing information accessibility.
  • Currently, this feature is available exclusively to the owner.

Takeaway — To Avoid the Same Pitfall

  • [ ] When developing new features, include planning and technical documentation creation from the initial stages as a mandatory step.
  • [ ] Alongside feature implementation, concurrently design and develop related UI components and pages.
  • [ ] Pre-emptively consider and design integration plans with internal systems such as the admin page.
  • [ ] When documenting, clearly specify API specifications, architecture, usage, etc.

💬 This is part of *Riel** — a full AI product I'm building solo, in public (failures and all). Read more build logs → · See the product →*

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