An eleven-year-old boy in California has successfully developed a functional video game using Microsoft Copilot, demonstrating how generative AI can lower technical barriers and amplify youth creativity. The project, spearheaded by Jacob Ragon, illustrates the tool's capacity to serve as an accessible scaffolding platform for neurodivergent learners while highlighting emerging conversations around digital literacy, content verification, and educational integration. Jacob, who was recently diagnosed with attention deficit hyperactivity disorder, dyslexia, and dysgraphia, approached software development with no prior coding experience. Drawing inspiration from a children's novel and a strategy title discovered on the Steam platform, he used Copilot to structure a game concept. Rather than writing scripts manually, he relied on natural language prompts and voice input to guide the AI through iterative design cycles. Over four days, working one to two hours daily, he collaborated with the model to draft mechanics, interpret error codes, and adapt assets when stability issues arose. The resulting prototype was completed in under eight hours of cumulative development time, fully playable without traditional programming knowledge. The development process underscored several functional advantages of AI-assisted creation. Jacob reported that the model offered consistent, non-judgmental feedback, enabling him to request repeated explanations of technical errors until he achieved comprehension. When encountering persistent debugging roadblocks, he adapted his approach by modifying game assets rather than abandoning the build, ultimately substituting complex character designs with simpler graphics to maintain progress. His parent, Michele Ragon, noted that the AI functioned as a creative catalyst, transforming abstract concepts into tangible digital products and providing positive reinforcement that traditional coding environments often lack. Despite the project's success, the initiative revealed notable challenges and oversight considerations. Jacob acknowledged difficulty recognizing when to modify his prompting strategy to resolve recurring AI errors, a limitation linked to developing metacognitive debugging skills. Broader concerns include the potential for children to accept AI-generated information without verification, as well as the risks associated with open digital distribution platforms and insufficient parental controls. These factors underscore the need for structured guidance when minors engage with generative tools. Educational and technology professionals view such cases as evidence of an urgent shift in digital literacy training. As AI integration accelerates across consumer and enterprise sectors, educators increasingly advocate for formal curricula covering prompt engineering, source validation, and ethical AI usage. Without proactive instruction, students may lack the critical frameworks necessary to navigate a creative and professional landscape increasingly mediated by machine learning systems. The project reinforces the potential of accessible AI to democratize software development. While regulatory and pedagogical frameworks continue to evolve, the case demonstrates that when deployed with appropriate guidance, generative models can empower younger users to innovate beyond traditional technical limitations.