Harnessing the Power of ChatGPT in Software Development
Tags: chatgpt, ai, softwaredevelopment
Published: 2023-11-23 06:42:22

ChatGPT is becoming a valuable asset for developers, aiding in tasks like coding and documentation. But, how do you plan to use this tool? Will you use it strategically for big projects like building prototypes, or just for quick help with your coding skills?

I'd say, think strategically. AI can do more than providing quick fixes for your coding problems — it can do more for your project. However, you have to do so carefully and thoughtfully, without crossing any security and ethics boundaries. This way you push your projects forward efficiently and safely. 

Let’s look at how you can utilize ChatGPT in software development, but firstly…..🔄

## What is ChatGPT?

Developed by OpenAI, ChatGPT is a chatbot designed for conversational interactions. You can ask it a question or give it a prompt, and it will reply, allowing for a back-and-forth conversation similar to messaging a real person.

ChatGPT is a modified version of InstructGPT, which was originally trained to provide detailed responses. To enhance its capabilities, human AI trainers worked on the model, engaging in conversations from both the user and AI assistant perspectives. Their insights, combined with the InstructGPT dataset, evolved the model into one that excels in more natural, conversational exchanges.

## How to Use ChatGPT While Maintaining AI Ethics

When coding with ChatGPT, it's important not to rely too much on it for tasks that need a lot of context. ChatGPT isn't as effective in complex scenarios where you can't share your full codebase. Also, be cautious when learning to code; don’t rely solely on its answers. While ChatGPT can suggest functional code, it might sometimes be too verbose or complex.

## ChatGPT, Best for Quick Prototyping

Rapid prototyping is vital in product development, enabling the creation of functional prototypes swiftly and economically. With ChatGPT, this process is poised for a significant advancement. ChatGPT can quickly generate code snippets for prototypes or Minimum Viable Products (MVPs). This accelerates development and testing, reducing the time and resources needed to launch new products. Let's dive into practical examples.

**Example 1: Creating a Basic React Component using ChatGPT. 
**
Our goal here is to build and style a login form component in React. To effectively use ChatGPT for the coding, you'll need to provide a clear prompt with specific details:

- Type of Code 
- Functionality 
- Technology Stack and Details

Below is the prompt you could use and the result.


**_Generate a basic React component for a login form with username and password inputs. Style it with plain CSS. Use TypeScript. Use React Hook Form version 7. Fields are required._
**
`import React, { useState } from "react";
import { useForm } from "react-hook-form";

interface FormData {
  username: string;
  password: string;
}

const LoginForm: React.FC = () => {
const {
  handleSubmit,
  formState: { errors },
  register,
  reset
} = useForm<FormData>({
    defaultValues: {
    username: "",
    password: ""
  }
});

const [formSubmitted, setFormSubmitted] = useState(false);

const onSubmit = (data: FormData) => {
  setFormSubmitted(true);
  console.log(data);
  reset();
};

return (
<form onSubmit={handleSubmit(onSubmit)}>
  <div>
    <label htmlFor="username">Username</label>
    <input
      id="username"
      type="username"
      placeholder="Email"
      {...register("username", { required: true })}
    />
    {errors.username?.type === "required" && (
    <p className="error-message">Username is required</p>
    )}
  </div>

  <div>
    <label htmlFor="password">Password</label>
    <input
      id="password"
      type="password"
      placeholder="Password"
      {...register("password", { required: true })}
    />
    {errors.password?.type === "required" && (
    <p className="error-message">Password is required</p>
    )}
  </div>
  <button type="submit">Submit</button>
  {formSubmitted && <p className="success-message">Form Submitted!</p>}
</form>
);
};

export default LoginForm;`

 
The code generated successfully includes a form with all necessary features like controls, error handling, and submission functionality. It's also customizable as needed.

Next, let’s address styling with ChatGPT! Yes, ChatGPT can assist with this. For styling, provide a clear prompt including the component’s code and specify your desired design style.

_**Style this component with CSS. Print only CSS. Design style – material.
[your code here]**_

`/* Form styles */
form {
  display: flex;
  flex-direction: column;
  align-items: center;
  padding: 1rem;
}

/* Input styles */
input {
  width: 100%;
  padding: 0.5rem;
  margin-bottom: 1rem;
  font-size: 1rem;
  border: none;
  border-bottom: 1px solid gray;
}

/* Label styles */
label {
  font-size: 1.2rem;
  margin-bottom: 0.5rem;
}

/* Submit button styles */
button[type="submit"] {
  background-color: #3f51b5;
  color: white;
  padding: 0.5rem 1rem;
  border: none;
  border-radius: 4px;
  cursor: pointer;
  font-size: 1.2rem;
  margin-top: 1rem;
}

/* Error message styles */
.error-message {
  color: red;
  font-size: 0.8rem;
  margin-top: 0.5rem;
}

/* Success message styles */
.success-message {
  color: green;
  font-size: 1rem;
  margin-top: 1rem;
}
`
Great job, The code turned out well. The AI model successfully captured the desired style, particularly achieving a material design look. Below is the ChatGPT-crafted login form, showcasing this style.


![The login form crafted by ChatGPT](https://dev-to-uploads.s3.amazonaws.com/uploads/articles/jmgr0pyn45cionprq06h.png)

**Example 2 - Using AI to Create a Docker File for Angular
**

**_Generate a Dockerfile for an Angular application.
_**
`Here's a possible Dockerfile for an Angular application:

- Use an official Node.js runtime as a parent image
FROM node:14
- Set the working directory to /app
WORKDIR /app
- Copy the package.json and package-lock.json files to the container
COPY package*.json ./
- Install the dependencies
RUN npm install
- Copy the rest of the application files to the container
COPY . .
- Build the Angular app
RUN npm run build --prod
- Expose port 80 for the container
EXPOSE 80
- Start the Angular app using http-server
CMD [ "npx", "http-server", "-p", "80", "./dist" ]
`
This Dockerfile starts with an official Node.js runtime as the parent image. It sets the working directory to ‘/app’, copies the ‘package.json’ and ‘package-lock.json’ files to the container, installs the dependencies, and copies the rest of the application files to the container.

Then it builds the Angular app using the ‘npm run build –prod’ command, which creates a production build of the app. After that, it exposes port 80 for the container and starts the Angular app using ‘http-server’ on port 80.

You can build and run the Docker image using the following commands:

docker build -t my-angular-app .
docker run -p 80:80 my-angular-app

Note that the ‘my-angular-app’ tag can be any name you choose for the image. Also, the ‘-p 80:80’ option maps port 80 of the host machine to port 80 of the container.

## TL; DR

For a deeper dive into maximizing your coding efficiency with ChatGPT, check out our detailed article, "[Level Up Coding with ChatGPT](https://oril.co/blog/level-up-coding-with-chatgpt-use-cases-for-developers/)."

## Wrapping Up

We've showcased just two ways to use ChatGPT for quickly creating prototypes. However, this model's capabilities extend far beyond these examples. ChatGPT can generate a variety of code snippets for different needs. While these snippets might need some fine-tuning, they generally provide a solid starting point. The key is to provide detailed instructions to get the best results.