According to @AnthropicAI, an experiment with software engineers found that coding with AI accelerated work but reduced skill mastery, with outcomes varying by how the tools were used (source: @AnthropicAI). The source indicates a usage-dependent tradeoff that organizations should account for when deploying AI coding assistants, balancing short-term productivity with deliberate practice and structured review to preserve capability growth (source: @AnthropicAI). The source further implies that engineering workflows, onboarding, and training policies should be designed to encourage active problem solving alongside AI assistance to limit mastery erosion while retaining speed gains (source: @AnthropicAI).

According to Miles Deutscher, traders should ignore market noise and concentrate on continuous self-improvement and upskilling, highlighting that there's always an opportune moment to enhance one's trading capabilities.