DEV Community

Cover image for Building Neon Drift: My Journey Creating a Game with AI Assistance
yxmil68
yxmil68

Posted on

Building Neon Drift: My Journey Creating a Game with AI Assistance

#ai #webdev #python #amazonqcli

Introduction

Neon Drift is a top-down infinite runner game with neon aesthetics, drift mechanics, and an upgrade system. I chose to create this game because:

• I've always been fascinated by arcade-style games with simple yet addictive mechanics
• The neon aesthetic provides a visually striking experience even with simple graphics
• The drift mechanics add a skill-based element that keeps gameplay interesting
• The upgrade system provides progression and strategic choices

The game challenges players to navigate through an endless track, collecting energy orbs with funny faces while avoiding obstacles. As you progress, the game speed increases, making it progressively more challenging.

Effective Prompting Techniques I Discovered

Throughout the development process, I learned several effective prompting techniques:

  1. Be specific about game mechanics: When I asked for "Game Idea: 'Neon Drift' – Score, Speed, Upgrade!" with a clear genre definition, the AI understood exactly what I wanted.

  2. Break down complex tasks: When the AI timed out on complex visual enhancements, I learned to split the work into smaller steps, which proved much more effective.

  3. Iterative development: Starting with a basic game and then requesting specific enhancements allowed for better control over the development process.

  4. Visual descriptions matter: Describing the desired visual style ("neon aesthetics") helped the AI generate appropriate code for glowing effects and color schemes.

  5. Reference familiar concepts: Mentioning "drift mechanics" gave the AI a clear understanding of the movement system I wanted.

How AI Handled Classic Programming Challenges

The AI effectively tackled several classic game development challenges:

Collision Detection

The AI implemented a clean rectangle-based collision system:

# Check collisions with obstacles
player_rect = player.get_rect()
for obstacle in obstacles[:]:
    if player_rect.colliderect(obstacle.get_rect()):
        if player.shield_active:
            obstacles.remove(obstacle)
            score += int(5 * player.score_multiplier)
        else:
            game_state = STATE_GAME_OVER
Enter fullscreen mode Exit fullscreen mode

Game Loop Structure

The AI created a well-structured game loop with distinct states:

# Game states
STATE_MENU = 0
STATE_PLAYING = 1
STATE_GAME_OVER = 2
STATE_UPGRADE = 3
Enter fullscreen mode Exit fullscreen mode

Difficulty Progression

The AI implemented an elegant difficulty scaling system:

# Increase game speed and distance
game_speed += 0.0005
distance += game_speed
Enter fullscreen mode Exit fullscreen mode 
# Spawn faster as game speed increases
obstacle_spawn_timer = random.randint(30, 90) // game_speed
Enter fullscreen mode Exit fullscreen mode

Visual Effects

The AI created impressive visual effects with pure code:

# Draw pulsing glow
glow_radius = self.radius + self.pulse_size
glow_surf = pygame.Surface((glow_radius * 2, glow_radius * 2), pygame.SRCALPHA)
pygame.draw.circle(glow_surf, (self.color[0], self.color[1], self.color[2], 100),
                  (glow_radius, glow_radius), glow_radius)
screen.blit(glow_surf, (self.x - glow_radius, self.y - glow_radius))
Enter fullscreen mode Exit fullscreen mode

Development Automation That Saved Me Time

Working with AI significantly accelerated the development process:

  1. Boilerplate Code Generation: The AI automatically set up the Pygame initialization, game loop, and state management system, saving hours of setup time.

  2. Class Structure Creation: The AI generated well-structured classes for the player, obstacles, and energy orbs with appropriate methods and properties.

  3. Git Repository Setup: The AI automated the entire process of setting up a Git repository with appropriate .gitignore, LICENSE, and README files.

  4. Visual Effects Implementation: Creating the neon glow effects would have required significant research and experimentation, but the AI implemented them efficiently.

  5. Game Balancing: The AI suggested reasonable values for game parameters like speed increases, spawn rates, and upgrade costs.

Code Examples of Interesting AI-Generated Solutions

Energy Magnet Upgrade

The AI created a clever implementation of the energy magnet upgrade that attracts nearby orbs:

# Energy magnet effect
if player.energy_magnet > 0:
    dx = player.x + player.width // 2 - orb.x
    dy = player.y + player.height // 2 - orb.y
    distance_to_player = math.sqrt(dx * dx + dy * dy)

    if distance_to_player < player.energy_magnet:
        # Move orb toward player
        attraction_strength = 1 - (distance_to_player / player.energy_magnet)
        orb.x += dx * 0.1 * attraction_strength
        orb.y += dy * 0.1 * attraction_strength
Enter fullscreen mode Exit fullscreen mode

Drift Mechanics

The AI implemented an intuitive drift system that enhances horizontal movement when pressing up/down with left/right:

# Drift mechanics (faster horizontal movement when holding up/down)
if keys[pygame.K_UP] and self.y > 0:
    self.y -= self.speed
    if keys[pygame.K_LEFT]:
        self.x -= self.speed * (self.drift_factor - 1)
    if keys[pygame.K_RIGHT]:
        self.x += self.speed * (self.drift_factor - 1)
Enter fullscreen mode Exit fullscreen mode

Funny Faces on Energy Orbs

The AI added a delightful touch with randomly generated funny faces on energy orbs:

# Draw funny face if enabled
if self.has_face:
    # Draw eyes
    eye_size = self.radius // 4
    pygame.draw.circle(screen, eye_color, (int(self.x - 5), int(self.y - 3)), eye_size)
    pygame.draw.circle(screen, eye_color, (int(self.x + 5), int(self.y - 3)), eye_size)

    # Draw smile
    pygame.draw.arc(screen, mouth_color,
                  (int(self.x - 5), int(self.y - 3), 10, 10),
                  0, math.pi, 2)
Enter fullscreen mode Exit fullscreen mode

Screenshots of the Final Creation

Image description

Image description

Image description

Image description

The game features:
• A neon grid background with twinkling stars
• A blue player car with glowing effects
• Colorful obstacles with different designs
• Energy orbs with funny faces
• Visual feedback for upgrades and collisions

Conclusion

Creating Neon Drift with AI assistance was an enlightening experience. The AI handled complex programming challenges efficiently while allowing me to focus on the creative aspects of game design. The process demonstrated how AI can be a powerful tool for game developers, especially for rapid prototyping and implementing complex features.

The final game includes all the elements I envisioned: drift mechanics, an upgrade system, increasing difficulty, and a distinctive neon aesthetic. While there's always room for improvement, Neon Drift stands as a testament to what can be accomplished with AI-assisted game development.

Resources:

Github Repo - https://github.com/yxlim68/neon-drift

Top comments (0)