PC/Console Game Development
Engine selection and platform-specific principles.
1. Engine Selection
Decision Tree
What are you building?
│
├── 2D Game
│ ├── Open source important? → Godot
│ └── Large team/assets? → Unity
│
├── 3D Game
│ ├── AAA visual quality? → Unreal
│ ├── Cross-platform priority? → Unity
│ └── Indie/open source? → Godot 4
│
└── Specific Needs
├── DOTS performance? → Unity
├── Nanite/Lumen? → Unreal
└── Lightweight? → Godot
Comparison
| Factor |
Unity 6 |
Godot 4 |
Unreal 5 |
| 2D |
Good |
Excellent |
Limited |
| 3D |
Good |
Good |
Excellent |
| Learning |
Medium |
Easy |
Hard |
| Cost |
Revenue share |
Free |
5% after $1M |
| Team |
Any |
Solo-Medium |
Medium-Large |
2. Platform Features
Steam Integration
| Feature |
Purpose |
| Achievements |
Player goals |
| Cloud Saves |
Cross-device progress |
| Leaderboards |
Competition |
| Workshop |
User mods |
| Rich Presence |
Show in-game status |
Console Requirements
| Platform |
Certification |
| PlayStation |
TRC compliance |
| Xbox |
XR compliance |
| Nintendo |
Lotcheck |
3. Controller Support
Input Abstraction
Map ACTIONS, not buttons:
- "confirm" → A (Xbox), Cross (PS), B (Nintendo)
- "cancel" → B (Xbox), Circle (PS), A (Nintendo)
Haptic Feedback
| Intensity |
Use |
| Light |
UI feedback |
| Medium |
Impacts |
| Heavy |
Major events |
4. Performance Optimization
Profiling First
| Engine |
Tool |
| Unity |
Profiler Window |
| Godot |
Debugger → Profiler |
| Unreal |
Unreal Insights |
Common Bottlenecks
| Bottleneck |
Solution |
| Draw calls |
Batching, atlases |
| GC spikes |
Object pooling |
| Physics |
Simpler colliders |
| Shaders |
LOD shaders |
5. Engine-Specific Principles
Unity 6
- DOTS for performance-critical systems
- Burst compiler for hot paths
- Addressables for asset streaming
Godot 4
- GDScript for rapid iteration
- C# for complex logic
- Signals for decoupling
Unreal 5
- Blueprint for designers
- C++ for performance
- Nanite for high-poly environments
- Lumen for dynamic lighting
6. Anti-Patterns
| ❌ Don't |
✅ Do |
| Choose engine by hype |
Choose by project needs |
| Ignore platform guidelines |
Study certification requirements |
| Hardcode input buttons |
Abstract to actions |
| Skip profiling |
Profile early and often |
Remember: Engine is a tool. Master the principles, then adapt to any engine.
🧠 AGI Framework Integration
Hybrid Memory Integration (Qdrant + BM25)
Before executing complex tasks with this skill:
python3 execution/memory_manager.py auto --query "<task summary>"
Decision Tree:
- Cache hit? Use cached response directly — no need to re-process.
- Memory match? Inject
context_chunks into your reasoning.
- No match? Proceed normally, then store results:
python3 execution/memory_manager.py store \
--content "Description of what was decided/solved" \
--type decision \
--tags pc-games <relevant-tags>
Note: Storing automatically updates both Vector (Qdrant) and Keyword (BM25) indices.
Agent Team Collaboration
- Strategy: This skill communicates via the shared memory system.
- Orchestration: Invoked by
orchestrator via intelligent routing.
- Context Sharing: Always read previous agent outputs from memory before starting.
Local LLM Support
When available, use local Ollama models for embedding and lightweight inference:
- Embeddings:
nomic-embed-text via Qdrant memory system
- Lightweight analysis: Local models reduce API costs for repetitive patterns
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