Introduction Programming courses continue to grapple with several pedagogical challenges, such as class size, variety of student prior experiences, and the necessity of timely, individualized feedback. Although Intelligent Tutoring Systems (ITS) have been targeted to solve them for some time, the rise of Generative Artificial Intelligence (GenAI) instruments prospective for transformation. But advanced systems such as these need to be designed based on educational stakeholders' expectations. In this paper we introduce a modular architecture of a GenAI-driven ITS that caters to the needs of both students and teachers for introductory programming. To validate and refine this framework we conducted a mixed-methods survey of programming teachers. The results indicate a high consensus regarding the desired features: teachers place valued emphasis in the ability of an ITS to auto grade questions, track learners’ progress, and provide deep analytics of most common mistakes and engagement patterns. For students, the focus is on immediate, explainer feedback and guided hints. Specifically, concerns from instructors were identified as being incredibly substantial regarding GenAI in terms of student overuse and the possible “hallucinations” of AI-generated misconceptions. These results can be directly related to our proposed approach, highlighting the need of a separate teacher's interface for monitoring, and a strong pedagogical module, that enables to steer the GenAI to generate hints and not solutions. This teacher driven approach guarantees not only that the artifact is technologically advanced, but also pedagogically fit and meets an authentic educational need.