Power trading operates on identifying congestion, where physical limitations on transmission lines create price dislocations between regions, rather than relying on simple directional bets. Success in this opaque market requires deep modeling of fundamentals—such as weather patterns, plant outages, and fuel costs—while managing the extreme asymmetry of "skew events" where prices can spike hundredfold. Neel Somani, a former quant researcher at Citadel, highlights that these markets are capital-intensive and structurally favor those who can navigate binding constraints. In the broader context of AI, career strategy is shifting; junior talent must move beyond traditional software engineering toward high-leverage domains like GPU kernel optimization, robotics, or AI-adjacent physical sciences. As agentic tools disrupt median software roles, building a personal knowledge moat through ambitious, hardware-intensive, or research-heavy projects is essential for long-term professional differentiation.
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