The software engineering landscape is experiencing a significant transformation with the advent of Generative Artificial Intelligence (GenAI) tools. While these tools show promise in enhancing programmer productivity, their impact on Time-Constrained Coding Challenges (TCCs), such as competitive programming, hackathons, and technical interviews remains poorly understood. TCCs are fundamental to both educational assessment and professional recruitment in software engineering. The integration of GenAI tools in these environments raises critical questions about skill development, assessment validity, and the nature of programming expertise. Current research lacks a systematic understanding of how GenAI tools affect programmer performance and learning outcomes in time-constrained environments. This gap is particularly concerning as educational institutions and industry organizations struggle to establish guidelines for GenAI use in TCCs. Without proper frameworks for integration, there are risks of: (1) Over-reliance on AI, potentially compromising fundamental skill development, and (2) Misalignment between traditional evaluation metrics and emerging co-intelligent programming practices. This doctoral research proposal aims to explore potential solutions for these issues.