Digital skills, particularly programming, have become a vital prerequisite for succeeding in today’s work life. Developing those skills is, however, a challenging task, as it requires perseverance, effort, and practice. To teach coding, individualized tutoring adapted to the novice programmers’ state of knowledge has evolved as the most promising learning strategy. However, offering sufficient learning support while practicing coding tasks is a challenge due to resource constraints. Following a three-cycle design science research approach, we developed a chatbot-based digital tutor that can support novice programmers using individualized, automated conversations based on adaptive learning paths and in-depth code analyses. In this article, we present the final version of the digital tutor software and report the findings of introducing it in a field setting over two entire lecture periods. We show that digital tutors can effectively provide individualized guidance in moments of need and offer high learning satisfaction in a long-term learning setting. This article expands the state of research by presenting insights into how students interact with a digital tutor over an entire lecture period. This also provides insights on how to design digital tutors for developing skills.