Anjney Midha opens the quarter of Stanford’s CS 153 Frontier Systems by framing the course as a speaker-led “AI Coachella,” emphasizing relationships, fun, and “obsessing over what you love” as a life heuristic. He introduces his background and the course goal of real-world preparedness, then outlines the modern AI stack from capital and data centers through chips, cloud, models, applications, and governance. Midha reviews how AI development has industrialized—especially reinforcement learning and continuous post-training—and argues that “context” and verifiable feedback loops determine where progress accelerates and where value accrues, citing examples like IDE access conflicts and sovereign AI needs. He then deep-dives on compute infrastructure, showing how capabilities and revenue correlate with compute buildouts, why GPU prices can rise, how infrastructure cycles resemble past commodity booms, and why compute remains non-fungible without standards and institutions.