In this episode of the LAOT Podcast, Arnav Mathur speaks with Mustafa Rajkotwala (Senior Legal Engineer, NYAI) about how artificial intelligence is reshaping legal education, early-career practice, and regulation in India. The conversation is anchored by a pivotal moment: the Supreme Court's June 2026 draft AI regulations for courts, and its subsequent ruling in Pooja Ramesh Singh v. Jammu and Kashmir Bank, where fabricated, AI-hallucinated precedents were struck down and the Bar Council of India was directed to examine the issue. Against this backdrop, Mathur and Rajkotwala trace the structural gaps in India's legal education system, from the 2008 Bar Council rules that never anticipated AI to the widening divide between elite law schools building their own AI centres and the fifteen-hundred-plus colleges left reliant on bare regulatory mandates. They examine what AI means for junior lawyers, questioning whether automating "grunt work" erodes the traditional osmosis through which young associates learn the profession, and unpack the case for a hybrid model where human judgment remains firmly in the loop. The discussion turns to Rajkotwala's own path from corporate practice at Khaitan & Co. to legal AI, and what that shift signals for freshers considering legal tech over traditional practice. Finally, they weigh the merits of industry self-regulation against formal rulemaking, drawing on comparisons to the ABA's Formal Opinion 512 and the history of Britain's Red Flag Act, and close on a shared conviction that no technology can substitute for a lawyer's judgment, only sharpen it.