According to Greg Brockman (@gdb), building pretraining infrastructure for AI models requires advanced skills in complexity management, abstraction design, operability, observability, and a deep understanding of both systems engineering and machine learning (Source: Greg Brockman, Twitter, Sep 7, 2025). This process highlights some of the most challenging and rewarding problems in software engineering. For businesses in the AI industry, mastering these domains opens up opportunities to develop scalable, efficient AI systems, increase model training reliability, and differentiate through robust infrastructure. The emphasis on infrastructure design reflects a growing trend where operational excellence and system abstraction are critical for deploying next-generation AI at scale.