According to Greg Brockman, a co-founder of OpenAI, a critical yet often overlooked skill in machine learning is the ability to extract meaningful insights from minor fluctuations or 'small wiggles' in model performance graphs (source: Greg Brockman, Twitter, Sep 7, 2025). This analytical capability enables AI professionals to identify hidden patterns, diagnose model behavior, and optimize algorithms more efficiently. For businesses, developing this nuanced expertise can lead to significant performance improvements, faster troubleshooting, and competitive advantage in deploying AI solutions. As AI models grow more complex, the ability to interpret subtle data signals becomes increasingly valuable for maximizing return on investment and ensuring robust, reliable machine learning deployments.