How to Generate Code with ChatGPT

ChatGPT is not limited to answering questions or writing content. You can also use it to generate code, explain programming concepts, debug errors, write SQL queries, and learn new programming languages.

For example, you can ask ChatGPT to create a Python function, generate a Java utility method, build an HTML form, or provide the structure for a Spring Boot REST API.

In this beginner-friendly tutorial, you will learn how to generate code with ChatGPT through eight practical examples.

We will also explore how to improve generated code with follow-up prompts, test the results, and use ChatGPT to understand unfamiliar programming concepts.

Watch the Video Tutorial

Watch the original video for a practical demonstration of generating code with ChatGPT using different programming languages and technologies.

What Can ChatGPT Do for Programmers?

ChatGPT can assist programmers with different stages of software development.

The video demonstrates or discusses the following tasks:

Generating Python, Java, HTML, and SQL code.
Explaining generated programs.
Adding comments to existing code.
Updating code using follow-up instructions.
Identifying programming errors.
Generating a Spring Boot CRUD REST API example.
Suggesting topics for learning a programming language.
Creating beginner-friendly learning content.

ChatGPT generates code based on your instructions. You should still review, run, and test the generated code before using it in a real application.

Prerequisites

To follow this tutorial, you need:

Access to ChatGPT.
A working internet connection.
Basic familiarity with the programming language you want to use.
A suitable environment for testing generated code.

The video demonstrates these examples using the free version of ChatGPT available at the time of recording.

You can open ChatGPT at:

https://chatgpt.com/

Available models, features, and usage limits may differ from those shown in the recording.

Example 1: Generate a Python Function to Check Prime Numbers

Let's begin with a simple Python programming example.

Suppose you want to write a function that checks whether a number is prime.

A prime number is a natural number greater than 1 that has exactly two positive divisors: 1 and itself.

Step 1: Enter the Python Coding Prompt

Open ChatGPT and enter the following instruction, based on the requirement demonstrated in the video:

Write a Python function that checks if a number is prime.

Submit the prompt.

ChatGPT generates a Python function for checking prime numbers.

In the video, the response also includes an explanation of how the function works.

Step 2: Review the Generated Python Code

Read the generated function before using it.

Check whether it handles important cases correctly, including numbers smaller than 2, the number 2, other prime numbers, and composite numbers.

You can also read ChatGPT's explanation to understand the function's logic.

Source note: The transcript does not contain the actual Python function returned by ChatGPT. Insert the original generated code from your video here if you want to reproduce that output exactly.

Step 3: Ask ChatGPT to Add Comments

Suppose you understand the general idea but want a clearer explanation of the code.

Instead of starting a new conversation, enter this follow-up prompt:

Add comments in the above Python function.

ChatGPT uses the existing function as context and returns an updated version containing comments.

The comments are intended to explain the important parts of the program.

This demonstrates how follow-up prompts can improve or clarify previously generated code.

Example 2: Generate a Java Utility Method to Check Null Objects

Next, let's generate a utility method for a Java application.

Suppose you are working on a Java project and frequently need to check whether an object reference is null.

You can ask ChatGPT to generate a reusable utility method.

Step 4: Enter the Java Utility Prompt

Write a Java utility function that checks null for objects.

Submit the prompt.

In the video, ChatGPT generates a utility method and provides an explanation of the implementation.

The demonstrated response includes:

A static utility method.
Explanatory comments.
Example code for testing the method.

A static method can be called without creating an instance of its utility class.

The specific method name and implementation depend on the generated response.

Step 5: Review the Utility Method

Before copying the generated method into your project, inspect its implementation and test examples.

Confirm that its behavior matches your requirements.

For example, decide whether you need a method that returns true when an object is null or one that returns true when it is not null.

The original prompt does not specify the method name or return convention, so these details should be verified in ChatGPT's generated response.

Source note: The exact Java class and method generated in the video are not included in the transcript.

Example 3: Generate an HTML Contact Form with ChatGPT

ChatGPT can also generate code for web development.

Let's create a simple HTML form containing three fields:

Name.
Email.
Message.

Step 6: Enter the HTML Form Prompt

Enter the following prompt:

Generate an HTML form with fields for name, email and message.

Submit the prompt.

ChatGPT generates HTML code based on the requested fields.

This is useful when building simple forms, prototypes, or basic web pages.

Step 7: Test the Generated HTML Form

After ChatGPT generates the code, the video demonstrates testing it using an online HTML compiler.

Follow these steps:

Copy the HTML code generated by ChatGPT.
Open a new browser tab.
Search for an HTML online compiler.
Choose an appropriate HTML editor or compiler.
Paste the generated code.
Run the code or open its preview.

You should see a form displaying the Name, Email, and Message fields.

The video does not identify the exact online compiler used, so no particular website is required for this step.

Step 8: Update the HTML Form Using a Follow-Up Prompt

Now suppose you want to modify the form.

Instead of a single Name field, you want separate First Name and Last Name fields.

You also want to add validation.

Enter the following follow-up prompt:

Update the above HTML form with fields first name, last name, email and message. Also add validation.

ChatGPT updates the form using the previous code as context.

In the video, the generated response includes:

First Name.
Last Name.
Email.
Message.
Client-side validation.

The response also contains formatted code and explanations.

Step 9: Test the Updated HTML Form

Copy the updated code and return to the online HTML compiler.

Replace the previous code with the new version and run it again.

Check whether the form now contains all four fields.

Next, test the validation behavior.

For example, inspect how the form handles missing required values and an invalid email address, if those checks are present in the generated implementation.

Client-side validation can improve the user experience, but it is not a replacement for server-side validation in a real application.

Source note: The transcript confirms that client-side validation was added, but it does not reproduce the exact HTML or JavaScript implementation.

Example 4: Debug Java Code with ChatGPT

Code generation is only one part of software development.

ChatGPT can also help investigate programming errors.

In the video, the presenter demonstrates debugging a Java program that calculates the factorial of a number.

Step 10: Prepare the Java Factorial Program

The demonstration begins by finding a Java factorial program online.

The presenter copies its factorial logic and intentionally introduces an error by removing an occurrence of the variable i.

The transcript does not include the complete program or identify the exact edited line.

Therefore, the faulty code must be recovered from the video before reproducing this demonstration exactly.

Step 11: Submit the Faulty Code to ChatGPT

Paste the faulty Java code into ChatGPT and ask it to identify the problem.

An example instruction that expresses the demonstrated task is:

Find the error in the following Java code and explain how to fix it.

[Paste the Java code here]

This is a reconstructed instruction. The transcript describes the debugging request but does not preserve its complete text.

ChatGPT analyzes the supplied program and attempts to identify the error.

In the video, ChatGPT points out the relevant faulty line and provides a correction.

Step 12: Verify the Suggested Fix

Do not assume that every suggested correction is accurate.

Review the explanation, apply the proposed fix, and run the Java program.

For a factorial implementation, check whether the program produces the expected results for appropriate test inputs.

The video illustrates error identification, but the exact source code and corrected version are not provided in the transcript.

Example 5: Generate SQL Queries with ChatGPT

ChatGPT can also help write SQL queries.

For example, suppose you want to retrieve employee names from a particular department.

Step 13: Enter the SQL Query Prompt

The video uses the following general requirement:

Write a SQL query to fetch the names of all the employees in the department.

ChatGPT responds by generating a SQL query.

However, the original request does not specify the actual database schema or the department name.

In the demonstration, ChatGPT assumes an employee table and relevant columns before writing the query.

Step 14: Provide Your Database Schema for Better Results

The video highlights an important lesson: do not leave your database structure to guesswork.

When requesting SQL code, provide details such as:

The table name.
The relevant column names.
The required filtering condition.
The expected output.

For example, if you want employees from a particular department, identify the department and explain how it is represented in your database.

Review the generated SQL against the actual schema before executing it.

Source note: The transcript does not contain the assumed table definition or the SQL statement generated by ChatGPT. The article intentionally does not invent either one.

Example 6: Generate Spring Boot CRUD REST APIs

Let's move to a larger software development example.

Suppose you are building a library management system and need CRUD REST APIs for managing books.

CRUD stands for Create, Read, Update, and Delete.

Instead of requesting only a small code snippet, you can ask ChatGPT to outline a complete implementation.

Step 15: Describe the Project and Technology Stack

In the video, the presenter provides a project requirement and specifies the technologies.

The demonstrated setup includes:

A library management system.
CRUD REST APIs for books.
Spring Boot 3.
Spring Data JPA.
MySQL.

The request can be expressed as follows:

Create CRUD REST APIs for books in a library management system using Spring Boot 3, Spring Data JPA and MySQL.

This prompt is reconstructed from the spoken instructions because the transcript does not preserve the exact final wording.

Including the framework version, persistence library, database, and resource name gives ChatGPT important implementation context.

Step 16: Review the Generated Project Setup

In the video, ChatGPT generates a step-by-step Spring Boot implementation.

The response begins with project setup.

It describes the required dependencies for the Maven pom.xml file.

Next, it provides instructions for configuring MySQL.

The video refers to configuration using application.properties or a YAML configuration file.

Verification note: The transcript renders the YAML filename as application.iml. The intended Spring Boot YAML filename is commonly application.yml. Check the original screen before quoting the filename as a verbatim detail from the recording.

The exact dependencies and database properties are not included in the transcript.

Step 17: Review the Book Entity

The generated example includes a Book entity.

According to the transcript, it contains the following fields:

ID.
Title.
Author.
Publisher.
Year.

Check that the generated entity matches your application's requirements.

The exact Java source is not present in the transcript and should be inserted from the original video if required.

Step 18: Review the Repository, Service, and Controller

After the entity, ChatGPT generates additional application components.

The video identifies:

Repository.
Service.
Controller.

These components form the structure used in the demonstrated application.

Review each generated class and verify how it interacts with the other components.

Step 19: Review the CRUD Operations

The generated controller contains REST API operations for managing books.

The transcript identifies five operations:

Operation	Purpose
Get all books	Retrieve the book collection.
Get book by ID	Retrieve a particular book.
Create book	Add a new book.
Update book	Modify an existing book.
Delete book	Remove a book.

The video does not provide the exact endpoint paths, controller annotations, request bodies, or HTTP response codes.

Those implementation details should be taken from the original generated code rather than invented.

Step 20: Create the Database and Test the Endpoints

The final part of the demonstrated response instructs the user to create the database and test the book-related endpoints.

Before using the generated API, verify:

The required dependencies are present.
The MySQL connection is correctly configured.
The application starts successfully.
The CRUD operations behave as expected.
Invalid input and missing records are handled appropriately.

The transcript does not include a completed endpoint test or test output.

Important: Generated project code is a starting point. Review security, validation, database behavior, and error handling before using it in production.

Example 7: Learn Python Programming with ChatGPT

ChatGPT can also help beginners plan their learning journey.

Suppose you want to learn Python but do not know which topics to study.

Step 21: Ask ChatGPT for a Python Learning Roadmap

The video demonstrates a beginner asking ChatGPT to suggest important Python topics.

Use this prompt:

I am a beginner and I want to learn Python programming language. Suggest the important topics.

Submit the prompt.

In the demonstration, ChatGPT generates a list of Python programming topics.

Step 22: Review the Suggested Python Topics

The response in the video includes:

Python basics.
Variables and data types.
Input and output.
Operators.
Control flow statements.
Data structures.
Functions.
Modules and packages.
File handling.
Error and exception handling.
Object-oriented programming.
Libraries and development tools.

This provides a starting structure for learning the language.

Step 23: Request Content for a Specific Topic

After receiving the learning roadmap, choose a topic you want to study.

The video demonstrates asking ChatGPT to generate content for Python basics.

Create content for basics of Python.

ChatGPT then generates learning material for that topic.

You can continue with the remaining topics through additional prompts.

Review the examples and practice the concepts yourself rather than relying only on generated explanations.

Example 8: Add Comments to Existing Java Code

Finally, let's see how ChatGPT can help document existing code.

Suppose you have a Java program that calculates the factorial of a number using a loop.

You want to add explanatory comments so that the code is easier to understand.

Step 24: Provide Your Java Code

Copy the Java program you want to document.

In the video, the presenter uses a factorial program.

Paste the program into ChatGPT along with the following instruction:

Add comments to the below Java code.

[Paste your Java code here]

Submit the prompt.

ChatGPT returns a version of the program with added comments.

Step 25: Review the Generated Comments

In the video, the response includes comments explaining the program.

Before accepting the updated code, check that the comments correctly describe its behavior.

Also verify that ChatGPT has not accidentally changed the original program logic.

Comments should explain important decisions and non-obvious behavior rather than unnecessarily repeating every line.

Source note: The original Java factorial program and the commented output are not included in the transcript.

Summary: ChatGPT Coding Examples Covered in This Tutorial

Example	Programming Task
1	Generate a Python prime-number function and add comments.
2	Generate a Java null-checking utility method.
3	Build an HTML form and add validation.
4	Find an error in a Java factorial program.
5	Generate an SQL query for employee data.
6	Generate Spring Boot CRUD REST APIs for books.
7	Create a Python learning roadmap and learning content.
8	Add comments to an existing Java program.

Tips for Getting Better Code from ChatGPT

1. Clearly Describe Your Requirement

Explain what you want the program to accomplish.

For example, specify that you need a Python prime-number function or an HTML form containing particular fields.

2. Mention the Programming Language and Framework

If you need Java, Python, HTML, or SQL, include that information in your prompt.

For framework-based projects, identify the framework and relevant version.

3. Provide Project Context

For the library management example, the prompt specifies Spring Boot 3, Spring Data JPA, MySQL, and the Book resource.

This gives ChatGPT more information about the intended implementation.

4. Provide the Database Schema

When requesting SQL queries, specify the actual table names and columns.

Otherwise, ChatGPT may assume a schema that does not match your database.

5. Use Follow-Up Prompts

You do not need to start a new conversation for every modification.

The video demonstrates adding comments to Python code and updating an HTML form using follow-up instructions.

6. Test the Generated Code

Copy the code into an appropriate development environment and verify that it works.

The video demonstrates this approach by running the generated HTML forms in an online editor.

For other languages, use the appropriate compiler, interpreter, or project environment.

7. Review Code Before Using It in a Project

Check the implementation for correctness, security, error handling, and compatibility with your application's requirements.

ChatGPT can make programming mistakes, and generated explanations can also be incorrect.

Troubleshooting Common Problems

1. ChatGPT Generates Incorrect Code

Review the code and describe the problem in a follow-up prompt.

Include the actual error message and relevant code when appropriate.

Run the corrected code to verify whether the problem has been resolved.

2. The Generated SQL Query Does Not Work

Check whether ChatGPT assumed the wrong table name or column names.

Provide the actual database schema and regenerate the query.

3. My HTML Form Does Not Validate Input Correctly

Review the generated validation logic and test the form with valid and invalid values.

For production applications, implement server-side validation as well.

4. The Spring Boot Project Does Not Start

Review the generated dependencies, framework version, and database configuration.

Use the startup error to identify the failing component.

The transcript does not contain a specific Spring Boot startup error or its solution.

5. ChatGPT Changes My Code While Adding Comments

Compare the original and updated code.

If your objective is documentation only, explicitly request that the code logic remain unchanged.

6. The Generated Code Is Difficult to Understand

Ask ChatGPT to explain the implementation.

The video demonstrates explanations and commented code as ways to make generated programs easier to understand.

Frequently Asked Questions

1. Can ChatGPT Generate Code?

Yes. The tutorial demonstrates generating Python, Java, HTML, SQL, and Spring Boot-related code using natural-language prompts.

2. Can Beginners Use ChatGPT for Programming?

Yes. Beginners can ask ChatGPT to generate examples, explain concepts, and suggest learning topics.

However, they should practice programming and verify the generated code.

3. Can ChatGPT Debug Java Code?

You can submit Java code and ask ChatGPT to identify and explain errors.

The video demonstrates this using an intentionally modified factorial program.

4. Can ChatGPT Generate HTML Forms?

Yes. The tutorial demonstrates generating a contact form and modifying it to include additional fields and client-side validation.

5. Can ChatGPT Write SQL Queries?

Yes. You can describe the information you need and ask ChatGPT to generate an SQL query.

Provide the real table names and columns to avoid incorrect assumptions.

6. Can ChatGPT Generate Spring Boot REST APIs?

The video demonstrates requesting a book management CRUD API using Spring Boot 3, Spring Data JPA, and MySQL.

Review and test the generated implementation before using it.

7. Can ChatGPT Add Comments to Existing Code?

Yes. The tutorial demonstrates adding comments to Python and Java programs using follow-up instructions.

8. Can ChatGPT Help Me Learn Python?

Yes. The video demonstrates generating a list of important Python topics and requesting learning content for Python basics.

9. Should I Copy ChatGPT-Generated Code Directly into Production?

No. Review, test, and adapt the generated code to meet your application's correctness, security, and maintenance requirements.

10. Do I Need ChatGPT Plus for the Examples in This Tutorial?

The presenter uses the free version available at the time of recording.

Current feature access and usage limits may differ. Check the available capabilities in your account.

Conclusion

In this tutorial, you learned how to generate code with ChatGPT using eight practical programming examples.

We started by generating a Python prime-number function and adding comments through a follow-up prompt.

Next, we explored Java utility methods, HTML forms, client-side validation, and debugging a Java factorial program.

We also demonstrated how to request SQL queries and generate a Spring Boot CRUD REST API example for a library management system.

Finally, we used ChatGPT to create a Python learning roadmap and add comments to existing Java code.

The key takeaway is to provide clear requirements, include the relevant technologies, refine the result through follow-up prompts, and test the generated code before using it.

ChatGPT can assist with many programming tasks, but understanding and verifying the code remain essential parts of software development.