This study investigates feedback seeking behaviors (FSB) among second language (L2) learners when engaging with GenAI for writing feedback. Utilizing a multiple case study approach, the research recruited two EFL learners with differing language proficiency and technological competence as participants. Data were collected from three writing tasks in an L2 writing course. After data codification using two tailored coding scheme, the researchers performed statistical analysis on the data of on the participants’ prompting patterns and interactional sequences Findings reveal that the learner with higher language and technology competences crafter longer prompts in fewer rounds of interaction, and gradually adapted towards more sophisticated prompting strategies, while the learner with moderate language and technological competences inclined to shorter prompt in more conversational rounds, and kept on using a simpler approach to prompt GenAI. Additionally, learner with higher language and technology competences comparatively engaged in more effective dialogic interaction with GenAI compared to the other learner who exhibited weaker engagement and likelihood to abruptly terminate the dialogic interaction. This paper contributes to the literature by providing insights into the dynamics of FSB in technology-mediated learning environments and suggests directions for future research to further explore the implications of AI-assisted feedback in language education.