9 Years Solo: Building Complex AI Competition in a Game Management SIM

After 9+ years of solo development, I just shipped what might be the most technically challenging update to my game management simulator, City Game Studio.

*The Technical Challenge:* v1.24.0 introduces AI competitors that create their own gaming consoles with full market dynamics. This isn't scripted behavior - it's emergent competition where AI entities: - Analyze market conditions to determine optimal console timing - Calculate component costs vs performance ratios - Compete for market share with dynamic pricing strategies - Execute M&A decisions based on company valuations - Snowball their growth through strategic acquisitions

*Tech Stack & Constraints:* - Built entirely in Godot Engine 2.1 (yes, ancient but stable) - Custom scripting language (GDScript) - not the most performant choice - Single-threaded architecture handling 16,000+ potential employees - Real-time economic simulation with 50+ years of gaming history data - Save files now use compression (new saves load 4x faster)

*Performance Solutions:* The biggest challenge was optimization. When players manage dozens of simultaneous projects with thousands of employees, the game would crawl. Solution: - Built custom benchmarking tools for GDScript performance profiling - Text rendering optimized by 40% through better caching - Threaded save/load operations - Pagination systems for large datasets

*Business Model Learnings:* - Started as side project in 2016, launched on Steam 2019 - $19.99 price point, quarterly major updates - DRM-free approach (moving away from Steam-only) - Community-driven development via Discord feedback loops - No VC, no team - just sustainable solo dev income

*AI Architecture:* Instead of hardcoded difficulty scaling, competitors now use economic models: ``` if (marketShare < threshold && cashFlow > consoleCost) { generateConsoleSpecs(targetMarket, availableTech, competitorAnalysis); calculateOptimalPricing(productionCosts, marketDemand); executeMarketingStrategy(budget, targetDemographics); } ```

*Unexpected Outcomes:* Players report AI competitors creating consoles that historically dominate markets differently than reality. The Wataggi 2600 analog sometimes gets dethroned by AI-generated consoles in the 80s. Emergent behavior we didn't explicitly program.

*Solo Dev Sustainability:* Revenue allows full-time development without external funding. Key metrics: quarterly update cycle maintains engagement, community feedback drives feature priority, open-source toolchain keeps costs minimal.

Next challenge: City Game Studio 2 with modern engine architecture and multiplayer competition.

*Demo/Source:* Steam: https://store.steampowered.com/app/726840/City_Game_Studio_Your_Game_Dev_Adventure_Begins/ *65% OFF starting September 17th for one week* - good timing to test the new competitive AI systems.

Happy to answer technical questions about solo game dev challenges or AI behavior design!