Game dev harnesses help LLMs handle non-code assets

The core issue is identified as a context problem. LLMs rely on context windows, and if the input is polluted or lacks clarity about the game's structure, the model cannot reason effectively. The author introduces the concept of a "harness," a set of patterns and tools that makes a game legible to AI agents. By converting opaque game components into addressable data, developers can guide LLMs to work within the specific constraints of their project.

This approach moves beyond one-shot demos to support real, daily development workflows. The author emphasizes that managing context and reducing pollution are key to making AI useful in game dev. The post is a human-authored reflection on a talk, clarifying that the content is not AI-generated, and aims to share these engineering practices with a broader audience beyond the conference attendees.