The conversation centers on the rise of AI agents as primary users of enterprise software, moving beyond human-centric design. Agents succeed in coding because they operate with precise system awareness and can navigate fragmented backends without UI friction—yet face adoption hurdles like cost, reproducibility, and organizational trust. Security becomes paramount: agents lack privacy rights, amplify data leakage risks, and demand new governance standards beyond human permission models. Enterprises must modernize APIs, identity systems, and monetization to support agent-driven workflows, while rethinking infrastructure to handle rising compute demands and token inefficiencies. Abstraction layers won’t disappear—they remain essential for policy, security, and human coordination—even as agents reinterpret them. The discussion also challenges Wall Street’s narrow focus on GPU economics, highlighting instead the broader consumption-driven growth in software usage. Finally, current AI spending anxieties are framed as transitional, pointing toward an imminent 'transistor moment' where capacity, cost, and utility align to unlock widespread agent adoption across engineering and sales functions.