Analyzing Frontier Model Progress with My Favourite Game: Prince of Persia

In this insightful analysis, the author explores the rapid evolution of frontier artificial intelligence models by using the classic video game Prince of Persia as a unique benchmark. By evaluating how modern LLMs navigate the complex, logic-heavy environments of the game, the article provides a fresh perspective on the reasoning capabilities and limitations of current frontier models. The author argues that traditional benchmarks often fail to capture the nuance of long-horizon planning and spatial reasoning required in gaming environments. By testing models against the intricate traps and timing-based challenges of the 1989 classic, the piece highlights significant breakthroughs in agentic behavior while identifying persistent gaps in state-tracking and error recovery. This creative methodology offers a compelling alternative to standard academic evaluations, suggesting that gaming environments may serve as a more rigorous testing ground for the next generation of autonomous AI systems.