Agentic Trek is a modern recreation of the classic 1970s Trek game, enhanced with sophisticated AI agents that provide dynamic, intelligent gameplay. Originally played on DEC VAX computers, this version brings the strategic depth of space exploration and combat into the modern era with pygame and advanced AI decision-making systems.
* * * GALACTIC MAP * * *
1 2 3 4 5 6 7 8
+---+---+---+---+---+---+---+---+
1 | . | K | . | * | . | . | K | . |
+---+---+---+---+---+---+---+---+
2 | . | . | B | . | . | K | . | . |
+---+---+---+---+---+---+---+---+
3 | K | . | . | . | . | . | . | * |
+---+---+---+---+---+---+---+---+
4 | . | . | . | E | . | . | . | . |
+---+---+---+---+---+---+---+---+
5 | . | * | . | . | . | . | B | . |
+---+---+---+---+---+---+---+---+
6 | . | . | . | . | K | . | . | . |
+---+---+---+---+---+---+---+---+
7 | . | . | K | . | . | . | . | . |
+---+---+---+---+---+---+---+---+
8 | B | . | . | . | . | * | . | . |
+---+---+---+---+---+---+---+---+
Legend: E=Enterprise, K=Klingon, B=Starbase, *=Star, .=Empty
🎮👾 From VAX Terminals to Agentic Coding: Rebuilding Trek with Amazon Q Developer CLI for the #BuildGamesChallenge 🚀✨
In the early 1980s, as a sophomore high schooler I got my first real taste of programming during a summer camp at Appalachian State University. I spent hours in the lab on a DEC VAX, captivated by the computer lab experience and the game Trek. Before heading home, the grad students handed me a stack of wide green-bar paper that was the complete BASIC source code for Trek. On my Apple ][+ with just 48KB of memory, I typed it in line by line (untold hours spent). That experience hooked me into a lifetime of computing.
🕹️ Fast forward to today, and I am reliving that origin story through the power of AI-assisted development. As part of the Amazon Q Build Games Challenge to develop in a rapid, AI-powered style to rebuild Trek using the cutting-edge Amazon Q Developer CLI.
📦 My setup: Windows 11 + WSL (Ubuntu 22.04); Bash; Python 3.13 + PyGame; Windows Terminal + GitHub CLI; Amazon Q Developer CLI; Community Profile: CarnegieJ on community.aws
🧠 With Amazon Q’s agentic CLI interface, I prompted, iterated, and debugged all within conversational flows—no IDE required. This is fun and exciting! What once took months of typing and troubleshooting now took minutes to ask for a search of the Internet for the legacy game, Trek: 🏗️ Described the new game architecture desired in plain English; 🤖 Generated boilerplate PyGame code using AI prompts; 🐛 Resolved bugs interactively through natural language; 🔁 Iterated over gameplay logic feature additions and UI updates seamlessly; 🥋 Generated unit tests; 📗 Generated game play documentation. 😇 Amazon Q and I had a very productive conversation.
The agentic foundation is built but some features are not yet fully activated in the current initial release gameplay experience. The AI agents exist but are not yet prominently influencing the visible game flow.
We plan to add more content and even add retro sound effects and scoring logic that is all powered through conversational automation. Sound like fun? You can clone, play, and even contribute! Let's rebuild Trek together.
🧥 This experiment proves and demonstrates how AI is revolutionizing the creative coding experience for nostalgic builders and new developers alike. I literally feel the coding excitement of years ago because of engaging with AI.
- Galaxy Exploration: Navigate through an 8x8 galaxy grid with 64 quadrants
- Strategic Combat: Engage Klingon vessels with phasers and photon torpedoes
- Resource Management: Monitor energy, shields, and torpedo supplies
- Starbase Operations: Dock for repairs, refueling, and resupply
- Time Pressure: Complete missions within stardate limits
- Adaptive Klingon AI: Dynamic combat strategies that learn from player behavior
- Strategic Planning Agent: Optimal route planning and resource allocation
- Difficulty Scaling: AI adjusts challenge level based on player performance
- Behavioral Analysis: AI observes and adapts to player patterns
- Event Generation: Dynamic mission events based on game state
- Dual Display Modes: ASCII terminal mode and pygame graphical interface
- Save/Load System: Persistent game state with multiple save slots
- Replay System: Record and analyze gameplay sessions
- Performance Metrics: Detailed statistics and performance tracking
- Modular Architecture: Extensible plugin system for new features
- Platform: Windows 11 with WSL Ubuntu 22.04
- Language: Python
- Graphics: PyGame
- AI Framework: Custom multi-agent system with decision trees
- Testing: pytest with coverage reporting
- Documentation: Sphinx with automated API docs
┌───────────────────────────────────────────────────────────────┐
│ Game Application Layer │
├───────────────────────────────────────────────────────────────┤
│ UI Layer │ Game Logic Layer │ AI Agent Layer │
│ ┌─────────────┐ │ ┌──────────────┐ │ ┌─────────────┐ │
│ │ ASCII UI │ │ │ Game Engine │ │ │ Klingon AI │ │
│ │ pygame UI │ │ │ Combat Sys │ │ │ Strategy AI │ │
│ │ Input Mgr │ │ │ Navigation │ │ │ Adaptive AI │ │
│ └─────────────┘ │ │ Resources │ │ └─────────────┘ │
│ │ └──────────────┘ │ │
│ │ │ │
├────────────────────┼──────────────────────┼───────────────────┤
│ Data Layer │ AI Data Layer │
│ ┌─────────────────────────────────────┐ │ ┌─────────────┐ │
│ │ Game State, Galaxy Map, Ship Data │ │ │ Behavior │ │
│ │ Save/Load, Configuration │ │ │ Learning │ │
│ └─────────────────────────────────────┘ │ │ Analytics │ │
│ │ └─────────────┘ │
└───────────────────────────────────────────┴───────────────────┘
- Windows 11 with WSL2 enabled
- Windows Terminal
- Ubuntu 22.04 LTS installed in WSL
- Python 3.10.12 or higher
- GitHub CLI
- Amazon Q CLI
- Your favorite text editor
- Clone the repository:
git clone https://github.com/carnegiej/agentic-trek.git
cd agentic-trek- Create virtual environment:
python -m venv venv
source venv/bin/activate- Install dependencies:
pip install -r requirements.txt- Run the ASCII game:
python run_game.py --asciinav <quadrant>- Navigate to specified quadrant (e.g., "nav 3,4")mov <sector>- Navigate to specified sector (e.g., "mov 3,4")srs- Short range sensors (local quadrant scan)lrs- Long range sensors (adjacent quadrant scan)pha <amount>- Fire phasers with specified energytor <course> <spread>- Fire photon torpedoshi <amount>- Raise/lower shieldsdock- Dock with starbase (when adjacent)com- Computer functions and calculationsdam- Damage reportquit- Exit game
- Mouse: Click to select targets and navigate
- Keyboard: Arrow keys for movement, spacebar for actions
- ESC: Pause menu
- F1: Help system
- Aggressive: Direct attacks with maximum firepower
- Defensive: Evasive maneuvers and shield management
- Tactical: Coordinated multi-ship attacks
- Adaptive: Learns from player combat patterns
- Route Optimization: Calculates efficient travel paths
- Resource Prediction: Anticipates supply needs
- Threat Assessment: Evaluates danger levels
- Mission Planning: Suggests optimal strategies
- Basic game engine and mechanics
- ASCII interface implementation
- Simple AI opponents
- Save/load functionality
- Basic pygame interface
- Advanced Klingon AI behaviors
- Strategic planning agent
- Adaptive difficulty system
- Player behavior analysis
- Complete pygame interface
- Replay system
- Performance analytics
- Comprehensive help system
- Multiplayer support
- Custom scenarios
- Mod support
- Advanced AI learning
We welcome contributions! Please see CONTRIBUTING.md for guidelines.
- Fork the repository
- Create a feature branch
- Make your changes
- Add tests for new functionality
- Submit a pull request
Run the test suite:
pytest tests/ -v --coverageThe game tracks various performance metrics:
- Decision Time: AI response times
- Win/Loss Ratios: Player success rates
- Resource Efficiency: Optimal resource usage
- Combat Effectiveness: Battle performance statistics
This project is licensed under the MIT License - see LICENSE file for details.
- Original Trek game creators from the 1970s
- pygame community for excellent documentation
- AI research community for decision-making algorithms
- Classic computer gaming preservation efforts
STARDATE: 2267.3 CONDITION: GREEN QUADRANT: 1,1
ENERGY: 3000 SHIELDS: 1500 TORPEDOES: 10
1 2 3 4 5 6 7 8
+---+---+---+---+---+---+---+---+
1 | E | . | . | K | . | . | . | * |
+---+---+---+---+---+---+---+---+
2 | . | . | . | . | . | . | . | . |
+---+---+---+---+---+---+---+---+
COMMAND: _
Screenshot placeholder - Run python src/main.py to see the pygame interface
The pygame interface features:
- Visual Quadrant Display: Click-to-navigate galaxy map
- Real-time Status Panel: Ship systems and mission progress
- Interactive Controls: Mouse and keyboard input
- Multiple Views: Main game, galaxy map (F2), help screen (F1)
For questions, suggestions, or bug reports, please open an issue on GitHub.
"Space: the final frontier. These are the voyages of the starship Enterprise..."
mov <x,y>- NEW! Impulse engine movement within quadrants for tactical positioning- Example:
mov 4,5moves to sector 4,5 within current quadrant - Uses impulse engines (lower energy cost than warp)
- Allows precise positioning for combat and docking
- Example:
- Fixed Torpedo Targeting - Torpedoes now accurately hit targets with proper trajectory calculation
- Course Directions Clarified:
- 0° = North (up)
- 90° = East (right)
- 180° = South (down)
- 270° = West (left)
- Spread System: 1=tight precision, 10=wide area coverage
help <command>- Get detailed help for any command- Example:
help torshows complete torpedo usage guide - Example:
help movexplains impulse movement system
- Example:
- Enhanced Documentation - Every command now has comprehensive help
- Dual Coordinates - Shows both quadrant (8x8 galaxy) and sector (8x8 within quadrant)
- Example:
QUADRANT: 2,4 SECTOR: 4,7 - Enhanced Damage Reports - Detailed system status with efficiency ratings
# Two-tier movement system
nav 2,4 # Warp to quadrant 2,4
mov 4,7 # Move to sector 4,7 for tactical positioning
tor 90 1 # Fire torpedo east with tight spread
# Enhanced help system
help # Show all commands
help mov # Detailed impulse movement help
help tor # Complete torpedo usage guide
# Comprehensive damage system
dam # Show detailed damage report with efficiency ratings- Strategic Positioning - Use
movfor optimal combat range and starbase approach - Energy Efficiency - Impulse movement costs less energy than warp navigation
- Combat Precision - Position precisely before firing torpedoes for maximum accuracy
- Enhanced Gameplay - Two-tier movement adds tactical depth to space combat
All systems operational, Captain! The Enterprise is ready for enhanced tactical operations. 🖖