Bulmann, UlrikeUlrikeBulmannStahlberg, NadineNadineStahlberg2026-03-102026-03-10202553rd Annual Conference of the European Society for Engineering: Educating Responsible Engineers, SEFI 2025https://hdl.handle.net/11420/61940To reflectively supervise students in final theses along the research process is very much under pressure in the age of artificial intelligence (AI). Being inspired by TL;DRs (abbreviation for «too long; didn't read», automatically generated hyper-short paper summaries), we emphasize in this article on the rather unattentive aspect of reading competences within the intertwinned reading – writing – researching – critical thinking approach. We asked: ''How can academics support students' reading competences when supervising them in their final theses in the age of AI?'' Thus, we encouraged reflection in a workshop for 17 supervisors by using (1) a self-designed, survey consisting of three parts: reflection, exercise and transfer, and (2) a peer exchange. Supervisors' reflections showed that they read scientific articles with joy, less time and rely on traditional reading strategies rather than using AI tools for reading. Being unaware of TL;DRs first, an exercise on writing and generating a hyper-short summary using a university's HAWKI-based LLM led them to evaluate the text quality to be both promising and risky. This resulted in assessing their training of competences to be multifaceted. Together, they updated their supervision guidelines considering multiple deskilling risks and various competence development potentials for students when using AI or not. Finally, we argue that such practical reflections and peer dicussions raise supervisors' awareness for responsible guidance of students in their final theses (best earlier within the curriculum) to strengthen their critical and AI literacy in an AI-enriched learning environment.enhttps://creativecommons.org/licenses/by-nc-sa/4.0/Social Sciences::378: Higher Education (Tertiary Education)::378.1: Organization and Management; CurriculumsSocial Sciences::371: Teachers, Methods, and Discipline::371.3: Methods of instruction and studyComputer Science, Information and General Works::006: Special computer methods::006.3: Artificial IntelligenceConference Paperhttps://doi.org/10.15480/882.1683810.5281/zenodo.1763132310.15480/882.16838Conference Paper