Build a React Dice Roller with AI Using Claude Code

Build a React Dice Roller with AI Using Claude Code

Run the Dice Roller Demo in 5 Easy Steps

This demo shows how Intent-Driven Engineering with Claude Code can generate and run a working application directly from an intent file.

Repository:

https://github.com/kendallmark3/teambrain-repro

1. Clone the Repository

Open a terminal and clone the repository.

git clone https://github.com/kendallmark3/teambrain-repro.git

2. Open the Demo Folder

Navigate to the demo directory that contains the dice roller intent.

cd teambrain-repro/demo

3. Open the Project in VS Code

Launch the repository in Visual Studio Code.

code .

This allows Claude Code to inspect the repository and access the intent files.

4. Ask Claude Code to Execute the Intent

Open Claude Code in the IDE and give it this prompt:

Read the file:intentdice.mdThis file contains the intent for a dice roller application.Execute the intent by:1. Generating the application described in the file2. Creating the project using Vite + React + TypeScript3. Installing all dependencies4. Running the development server5. Opening the application in the browserRun any commands required automatically.Explain briefly what you are doing as you execute each step.

Claude will read intentdice.md, generate the project, and run the application.

5. View the Running Dice Roller

Claude will start the development server and open the application.

Typical output:

http://localhost:5173

You will now see the dice roller application running in your browser.

Click Roll Dice to generate new random dice values.

What This Demonstrates

This simple demo illustrates the core idea behind Intent-Driven Engineering:

1. Define the system intent

2. Provide the intent file to the AI

3. Allow the AI to generate and run the system

Instead of writing every file manually, developers guide the system through intent definitions.

Introduction

Modern AI tools are changing how developers learn and build software. Instead of starting from a blank editor, developers can describe the program they want and allow an AI coding assistant to generate the implementation.

In this demonstration, we build a simple React dice roller using Claude Code, showing how quickly AI can help generate working programs.

This approach aligns with the Learn → Teach → Master framework, where developers learn by experimenting, teaching concepts, and refining their understanding through practice.

Video Demonstration

Watch the full demo here:

What Is Claude Code?

Claude Code is an AI-powered development environment created by Anthropic that allows developers to interact with code using natural language prompts.

Instead of writing every line manually, developers can describe the intent of the program and allow the AI to generate the code.

Claude Code enables developers to:

• Generate working code from prompts

• Analyze existing codebases

• Refactor or improve code

• Rapidly prototype ideas

Official documentation can be found here:

Claude Code Documentationhttps://docs.anthropic.com/claude/docs/claude-code

Anthropic Claude Platformhttps://docs.anthropic.com

The Example: A React Dice Roller

The example demonstrated in the video is a classic beginner programming exercise.

The AI generates a Python program that:

1. Randomly generates numbers between 1 and 6

2. Displays the result

3. Allows the user to roll again

Even simple exercises like this are powerful for demonstrating how AI can accelerate development and learning.

The core React concept being demonstrated is random number generation, which simulates rolling a physical dice.

Why AI-Assisted Coding Matters

AI-assisted development changes the way developers approach programming.

Traditional workflow:

1. Write code manually

2. Search documentation

3. Debug issues

4. Repeat

AI-assisted workflow:

1. Describe the desired outcome

2. Generate working code

3. Modify and refine

4. Learn through iteration

This dramatically reduces the time required to move from idea to working software.

How This Fits the Learn Teach Master Framework

The Learn Teach Master (LTM) framework encourages developers to reinforce learning by teaching concepts and experimenting with real examples.

The process looks like this:

LearnExplore a concept or tool such as AI-assisted coding.

TeachExplain the concept or demonstrate it through examples.

MasterBuild projects and refine understanding through practice.

Using AI tools like Claude Code accelerates this learning cycle.

Related Learn Teach Master Articles

To deepen your understanding of AI-assisted development, Claude Code, and intent-driven engineering, explore these related Learn Teach Master articles.

Bare-Bones Setup for Claude Code (Developer Quick Start)https://www.learnteachmaster.org/post/bare-bones-setup-for-claude-code-developer-quick-start 

Intent-Driven Engineering with Claudehttps://www.learnteachmaster.org/post/intent-driven-engineering-with-claude 

The Learn–Teach–Master Guide to Using AI With Clarity and Powerhttps://www.learnteachmaster.org/post/the-learn-teach-master-guide-to-using-ai-with-clarity-and-power 

Claude Code Skills: Building a Team Brain that Scaleshttps://www.learnteachmaster.org/post/claude-code-skills-building-a-team-brain-that-scales

LearnTeachMaster + Claude Code in VS Codehttps://www.learnteachmaster.org/post/learnteachmaster-org-claude-code-in-vs-code

From Prompt Chaos to Intent Architecturehttps://www.learnteachmaster.org/post/from-prompt-chaos-to-intent-architecture

External References

If readers want to explore the tools used in this demonstration:

Claude Code Documentationhttps://docs.anthropic.com/en/docs/claude-code

Anthropic Claude Platform Overviewhttps://docs.anthropic.com

Python Official Documentationhttps://docs.python.org/3/

Key Takeaways

AI coding tools are rapidly transforming the developer workflow.

Important ideas demonstrated in this example include:

• AI can generate working code from simple prompts

• Developers can experiment and learn faster

• Small projects like a dice roller are ideal for learning

• AI-assisted development accelerates the Learn → Teach → Master cycle

Final Thoughts

The future of software development is increasingly intent-driven.

Instead of focusing only on syntax, developers will focus on describing the behavior they want and guiding AI tools to implement those ideas.

Learning how to work effectively with AI development tools like Claude Code is becoming an essential skill for modern developers. Build a React Dice Roller with AI Using Claude Code | Learn Teach Master

Meta Description

Learn how to build a Python dice roller using Claude Code and AI-assisted development. Explore prompt-driven coding and the Learn Teach Master framework.

Keywords

Claude CodeAI coding toolsPython dice rollerAI assisted programmingintent driven engineeringlearn teach master framework