AI-Powered Game Development: How a Novice Used Local LLMs to Build a Snarky Mage Platformer

AI-Powered Game Development: How a Novice Used Local LLMs to Build a Snarky Mage Platformer

In a remarkable demonstration of how accessible AI tools are becoming to non-experts, a Reddit user known as /u/swagonflyyyy has developed a fully functional 2D platformer game in Godot — not with years of programming experience, but with the help of a locally run large language model (LLM) called Claude Code. The game, centered around a sarcastic, follow-along mage who mocks the player’s every misstep, showcases a novel approach to game AI: real-time contextual feedback powered by local inference rather than cloud APIs or pre-scripted behaviors.

The developer, who identifies as "super new to Godot," began experimenting with local LLMs after finding existing tools like Cline and Codex too resource-intensive and unreliable on his hardware. After switching to Claude Code — a variant of Anthropic’s Claude optimized for code generation — he found the model delivered consistent, high-quality output without overheating his GPU or causing CPU-GPU switching issues. What began as a two-week curiosity project has evolved into a playable prototype with emergent AI behavior, where the mage NPC observes player actions, logs them in a running chat history, and delivers witty commentary every 10 seconds.

Unlike traditional NPC systems that rely on finite state machines or decision trees, this mage’s responses are generated dynamically based on in-game events — such as falling off a platform, taking damage, or collecting items. The logic is hard-coded to trigger the LLM’s output at intervals, but the content is context-sensitive. For example, if the player repeatedly fails to jump a gap, the mage might quip, "Did you train under a rock? Even a sloth could’ve made that leap." The developer confirmed that the model does not have direct access to game state variables; instead, he manually feeds it a summary of recent events through a logging system, effectively creating a "context window" for the AI to react to.

This hybrid approach — where human developers define the structure and the LLM generates the flavor — is gaining traction in indie game circles. While not yet a replacement for traditional game design, it offers a powerful tool for rapid prototyping of personality-driven NPCs. The developer plans to enhance the system by integrating tool calls, allowing the mage to autonomously suggest healing items, switch equipment, or highlight hidden paths — effectively turning the AI into a dynamic game designer assistant.

While the Reddit post does not reference formal academic research, the underlying methodology aligns with recent trends in human-AI collaboration in creative domains. According to research published in academic journals on AI-assisted development, local LLMs reduce latency and privacy risks while enabling iterative, exploratory coding — a concept the developer describes as "vibecoding." This term, though informal, captures the essence of a relaxed, experimental workflow where AI serves as a creative sparring partner rather than a code generator.

Notably, the project does not rely on any of the object-oriented programming constructs like Python’s super() or Java’s super() for inheritance — as confirmed by Stack Overflow discussions on these topics — but instead leverages procedural scripting in Godot’s GDScript. The developer’s success underscores that deep programming knowledge is not a prerequisite for leveraging advanced AI tools; understanding context, iteration, and feedback loops is often more critical.

As local LLMs become more efficient and accessible, we may see a new wave of indie games built not by large studios, but by hobbyists using AI as a co-pilot. This project is not just a quirky novelty — it’s a glimpse into the future of democratized game development, where personality, humor, and emergent behavior can be crafted with minimal code and maximum AI assistance.