The field of game development and testing is experiencing significant advancements with the integration of artificial intelligence (AI). Researchers are exploring innovative ways to leverage AI technologies, such as Large Language Models (LLMs) and reinforcement learning, to improve game design, testing, and development. One notable direction is the use of LLMs for automatic playtesting, which has the potential to reduce manual testing efforts and improve game quality. Additionally, researchers are investigating the application of AI in game development, including the use of generative models to create game content and the development of modular harnesses for LLM agents in multi-turn gaming environments. These advancements are expected to have a significant impact on the field, enabling more efficient and effective game development and testing. Noteworthy papers include: LLMShot, which introduces a novel framework for automating snapshot test analysis, General Modular Harness for LLM Agents, which presents a modular harness design for LLM agents, and Fly, Fail, Fix, which proposes an automated design iteration framework that pairs a reinforcement learning agent with a large multimodal model to refine game mechanics.