Teaching in academic settings often faces criticism for lagging behind current industry practices. The gap between software development curricula and industry standards has widened significantly with advancements in Agile, AI-powered assistants, Large Language Models (LLMs), and emerging cloud-native DevOps solutions. A major obstacle for academic staff in adopting an AI-Driven Agile development environment is the absence of a coherent toolkit to support teaching within this paradigm. Additionally, existing AI-driven agents or chatbots are not fully exploiting capabilities in project stages like building, testing, and code execution, alongside Agile methods. Furthermore, AI agents face challenges in tracking shifts in customer intent through conversation, where human assistants still excel. To bridge this gap, we introduce TruDevOps, an automated AI-driven framework that enables autonomous conversation, intent extraction, project planning, and execution, while incorporating Agile best practices, particularly Scrum, to enrich software development pedagogy at the university level. Classroom experiments indicate promising results, with more students in the AI-Driven DevOps team adhering to intelligent agent suggestions to maximize team value by prioritizing critical tasks and reducing project time.