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Building a Retro Tennis Pong Game with AI: A Developer's Journey

#webdev #awschallenge #buildgameschallenge #programming

How I recreated classic gaming magic with modern AI assistance

The Game That Started It All

When I set out to build a retro-style game with AI assistance, Pong was the obvious choice. But not just any Pong - I wanted to create something that captured the essence of tennis with realistic court surfaces and physics that would make Wimbledon proud.

Why Tennis Pong?

  • Nostalgic Appeal: Pong is the grandfather of video games, released in 1972
  • Perfect Complexity: Simple enough to complete, complex enough to be interesting
  • Tennis Twist: Adding realistic court surfaces (grass, clay, hard court) made it unique
  • Physics Playground: Each surface affects ball speed, bounce, and friction differently

The AI-Powered Development Process

Effective Prompting Techniques I Discovered

Through this project, I learned that successful AI collaboration requires strategic prompting:

1. Context-Rich Requests

Instead of: "Make a Pong game"
I used: "Create a tennis-themed Pong game with three court surfaces (grass, clay, hard court) where each surface has different physics properties affecting ball speed and bounce"

2. Iterative Enhancement 

Phase 1: Basic Pong mechanics
Phase 2: Add tennis court visuals
Phase 3: Implement surface physics
Phase 4: Add AI opponents
Phase 5: Tournament mode
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3. Specific Technical Requirements

  • "Use HTML5 Canvas for rendering"
  • "Implement realistic physics with different friction coefficients"
  • "Add sound effects using Web Audio API"
  • "Create responsive controls for both keyboard and touch"

How AI Handled Classic Programming Challenges

Challenge 1: Game Loop Architecture

The Problem: Creating smooth 60fps gameplay with proper state management

AI Solution: Generated a clean game loop with requestAnimationFrame:

function gameLoop() {
    if (!gameState.gamePaused && gameState.gameRunning) {
        update();
        render();
    }
    requestAnimationFrame(gameLoop);
}
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Challenge 2: Collision Detection

The Problem: Accurate ball-paddle collision with realistic physics

AI Generated Solution:

function checkPaddleCollision(ball, paddle) {
    if (ball.x < paddle.x + paddle.width &&
        ball.x + ball.width > paddle.x &&
        ball.y < paddle.y + paddle.height &&
        ball.y + ball.height > paddle.y) {

        // Calculate hit position for spin effect
        const hitPos = (ball.y - paddle.y) / paddle.height;
        const spinFactor = (hitPos - 0.5) * 2;

        ball.velocityX *= -1;
        ball.velocityY += spinFactor * 2;

        soundManager.play('paddleHit');
        return true;
    }
    return false;
}
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Challenge 3: Court Surface Physics

The Problem: Making each tennis surface feel authentically different

AI's Elegant Solution:

const courtSurfaces = {
    grass: {
        name: 'Grass Court',
        ballSpeedMultiplier: 0.85,
        frictionCoefficient: 0.98,
        bounceReduction: 0.7,
        color: '#2d5016',
        description: 'Wimbledon Style - Slower, softer bounce'
    },
    clay: {
        name: 'Clay Court', 
        ballSpeedMultiplier: 0.75,
        frictionCoefficient: 0.95,
        bounceReduction: 0.6,
        color: '#8B4513',
        description: 'French Open Style - Slowest, lowest bounce'
    },
    hard: {
        name: 'Hard Court',
        ballSpeedMultiplier: 1.0,
        frictionCoefficient: 0.99,
        bounceReduction: 0.8,
        color: '#4169E1',
        description: 'US Open Style - Fastest, highest bounce'
    }
};
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Development Automation That Saved Hours

1. Instant Code Generation

What used to take hours of research and implementation:

  • Sound system with Web Audio API: Generated in minutes
  • AI opponent with multiple difficulty levels: Created instantly
  • Responsive UI with court switching: Automated completely

2. Bug Detection and Fixes

AI caught issues I would have spent hours debugging:

  • Ball getting stuck in paddle collision loops
  • Inconsistent frame rate causing physics glitches
  • Memory leaks in sound generation

3. Feature Enhancement

When I asked for "tournament mode," AI generated:

  • Complete bracket system
  • Score tracking across matches
  • Victory animations
  • Statistics dashboard

Interesting AI-Generated Solutions

Smart AI Opponent

The AI created a sophisticated opponent system with realistic imperfections:

class AIPlayer {
    constructor(difficulty = 'medium') {
        this.difficulty = difficulty;
        this.targetY = 0;
        this.reactionTime = 0;
        this.accuracy = 0;
        this.speed = 0;
        this.setDifficulty(difficulty);
    }

    setDifficulty(difficulty) {
        const settings = {
            easy: { reactionTime: 300, accuracy: 0.6, speed: 0.7 },
            medium: { reactionTime: 200, accuracy: 0.8, speed: 0.85 },
            hard: { reactionTime: 100, accuracy: 0.95, speed: 1.0 },
            expert: { reactionTime: 50, accuracy: 0.98, speed: 1.2 }
        };

        Object.assign(this, settings[difficulty]);
    }

    update(ball, paddle) {
        // Predict ball position with reaction delay
        const predictedY = ball.y + (ball.velocityY * this.reactionTime / 16);

        // Add human-like inaccuracy
        const error = (Math.random() - 0.5) * (1 - this.accuracy) * 100;
        this.targetY = predictedY + error;

        // Move paddle with speed limitations
        const diff = this.targetY - paddle.y;
        paddle.y += Math.sign(diff) * Math.min(Math.abs(diff), this.speed * 5);
    }
}
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Dynamic Sound System

Instead of loading audio files, AI created a procedural sound system:

createTone(frequency, duration, waveType = 'sine') {
    return () => {
        const oscillator = this.audioContext.createOscillator();
        const gainNode = this.audioContext.createGain();

        oscillator.connect(gainNode);
        gainNode.connect(this.audioContext.destination);

        oscillator.frequency.setValueAtTime(frequency, this.audioContext.currentTime);
        oscillator.type = waveType;

        // Create natural sound envelope
        gainNode.gain.setValueAtTime(0, this.audioContext.currentTime);
        gainNode.gain.linearRampToValueAtTime(this.masterVolume * 0.3, this.audioContext.currentTime + 0.01);
        gainNode.gain.exponentialRampToValueAtTime(0.001, this.audioContext.currentTime + duration);

        oscillator.start(this.audioContext.currentTime);
        oscillator.stop(this.audioContext.currentTime + duration);
    };
}
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The Final Creation

Game Features Achieved:

  • ✅ Three authentic tennis court surfaces
  • ✅ Realistic physics for each surface
  • ✅ AI opponents with 4 difficulty levels
  • ✅ Tournament mode with brackets
  • ✅ Procedural sound effects
  • ✅ Responsive controls (keyboard + touch)
  • ✅ Pause/resume functionality
  • ✅ Score tracking and statistics

Technical Highlights:

  • Pure JavaScript: No external libraries
  • HTML5 Canvas: Smooth 60fps rendering
  • Web Audio API: Dynamic sound generation
  • Responsive Design: Works on desktop and mobile
  • Clean Architecture: Modular, maintainable code

Key Takeaways

What AI Excelled At:

  1. Rapid Prototyping: From idea to playable game in hours
  2. Complex Logic: Physics calculations and game state management
  3. Code Quality: Clean, well-commented, maintainable code
  4. Feature Completeness: Comprehensive implementations, not just basics

What Required Human Guidance:

  1. Creative Vision: Defining the tennis theme and court surfaces
  2. User Experience: Fine-tuning gameplay feel and balance
  3. Quality Assurance: Testing edge cases and user interactions
  4. Project Direction: Deciding which features to prioritize

The Magic Formula:

Clear Vision + Specific Prompts + Iterative Refinement = AI Development Success

Try It Yourself!

The complete Tennis Pong game is available in this repository. Open tennis-pong.html in your browser and experience the different court surfaces:

  • Grass Court: Feel the Wimbledon grass beneath your virtual feet
  • Clay Court: Experience the slow, strategic play of Roland Garros
  • Hard Court: Enjoy the fast-paced action of the US Open

Controls:

  • Player 1: W/S keys
  • Player 2: Arrow keys
  • Space: Pause/Resume
  • Court buttons: Switch surfaces mid-game

This project demonstrates how AI can accelerate game development while preserving the creative joy of building something uniquely yours. The future of coding isn't about replacing developers—it's about amplifying our creativity and productivity.

Ready to build your own retro masterpiece? The only limit is your imagination!

Github link to project: https://github.com/ultrasage-danz/tennis-pong-championship

Full Youtube Link: https://www.youtube.com/watch?v=N8Me-FDBmNo

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