LLMs are the Ideal Candidate for Mixed-Initiative Game Design Pillar Workflows

TL;DR

This paper explores how Large Language Models can support game design workflows centered on design pillars, introducing a prototype tool, SPINE, and evaluating its utility through a pre-study, case study, and expert interviews.

Contribution

It provides a formal definition of game design pillars, presents the SPINE prototype, and demonstrates the potential of LLMs to assist in early-stage game design processes.

Findings

Gemini-2.0-flash outperforms GPT-4o-mini in output variety and consistency.

SPINE received positive feedback during a local game jam.

Experts found value in integrating LLMs into design pillar workflows.

Abstract

Game Design Pillars are natural language artifacts commonly used in game development to communicate a project's core vision and ensure a coherent player experience. Their linguistic nature aligns well with the strengths of Large Language Models (LLMs), which excel at generating and interpreting natural language, making them strong candidates for supporting mixed-initiative workflows centered on design pillars. In this study, we introduce a formal definition of game design pillars, present an initial prototype -- SPINE -- and investigate the utility of LLMs in the creation and decision-making processes associated with pillar-driven workflows. We begin with a pre-study to identify an appropriate model, comparing \texttt{gemini-2.0-flash} and \texttt{GPT-4o-mini}. Results show that Gemini is better suited to our tasks due to its greater output variety and consistency. We then conduct a case study by deploying the tool at a local game jam. Findings indicate positive reception and clear value in integrating SPINE into early-stage development. Finally, we interview four experts, demonstrating the tool and allowing them to experiment with it in a controlled environment. While individual perspectives vary, the overall perception is encouraging and supports our intuition: LLMs can meaningfully contribute to game design pillar workflows. These early findings highlight the potential of formalizing pillar-driven design as a research space and point toward several promising avenues for future work.