💡 My Personal Experience Using AI in Web Development
In recent years, AI has become an essential assistant for developers—especially in the world of web development. In this article, I’ll share my personal experience with AI tools, highlighting where they shine, and where you should be cautious when using them.
✅ Effective Use Cases for AI in Web Development
1. Creating Utility Functions and Pure Functions
AI is incredibly good at generating clean and optimized utility functions. Whether it’s for formatting text, manipulating data, or simple logic, the results are usually excellent.
2. Writing Native JavaScript and Browser API Code
When dealing with raw JavaScript or browser-specific APIs (like IntersectionObserver, Clipboard API, WebSockets, etc.), AI provides reliable and fast solutions, saving you time from reading documentation.
3. Code Documentation and Comments
AI is super helpful when it comes to writing clean inline comments or even full documentation files (like Markdown docs). This is particularly useful when working in a team or contributing to open-source projects.
4. Building Specific UI Components (with Clear Inputs/Outputs)
If you clearly explain what the component needs (props, expected outputs), AI can generate code that is often close to production-ready.
5. Localization & Internationalization
AI can assist in quickly translating content and generating proper localization files (.json, .po, etc.) based on the structure you’re using.
6. Generating Placeholder or Dummy Data
Extremely useful during the early stages of development to simulate API responses or UI behavior with realistic-looking mock data.
7. Generating Backend Entities with ORM (Prisma, TypeORM, etc.)
By giving a detailed explanation of your system resources and their properties, AI can generate entity schemas and models—something that usually takes a lot of time when done manually.
8. Code Refactoring (⭐ Highly Recommended)
One of the areas where AI truly shines. It understands your logic, cleans up messy code, and improves structure—saving hours of work with impressive results.
⚠️ Use Cases Where You Should Be Cautious
1. Project Architecture & Boilerplate Setup
If you don’t provide a very detailed description, AI might fall back to outdated or overly simplified project structures. You’ll need to guide it carefully.
2. Final UI Design (Especially for Arabic/RTL Layouts)
AI isn’t great at full-page designs—especially in Arabic or RTL. You might spend more time fixing its output than building it yourself. The better approach: explain the UI section by section.
3. Creating Animations
AI-generated animations often fall short in terms of quality or smoothness. For complex or modern UI/UX effects, manual work or specialized tools are better.
4. Debugging New Framework Features
If you're using a very recent feature from a library or framework (e.g., the latest version of React, Next.js, etc.), AI may not be up-to-date or trained on enough examples to help effectively.
5. Runtime Error Debugging
Just pasting the console error isn’t enough. AI needs full context: components involved, the flow of execution, and what you're trying to do. Without that, it might give you irrelevant solutions.
🚫 Golden Rule
“Never copy code from AI that you don’t understand.”
If AI generates something unfamiliar or complex, read it, ask it to explain, or search it online. Blindly copying code—especially logic-heavy snippets—can be risky.
🌟 Bonus AI Use Cases
Improving SEO: AI can write meta tags, generate structured data (JSON-LD), and suggest better titles/descriptions.
Writing Tests (Jest, Vitest, Cypress): With proper input, AI can generate test cases that follow your logic and structure.
Summarizing Long Code or Documentation: If you're working with legacy code or a new library, AI can break down what’s going on quickly and clearly.
🧠 Final Thoughts
AI is not a replacement for developers—it’s a powerful tool. The more you understand its strengths and weaknesses, the better you can use it to enhance your workflow and speed up delivery without sacrificing quality.