Reddit has become a space for informal student discourse where computer science students share experiences, seek advice, compare courses, and express frustrations. These conversations can provide valuable insights into the student experience and help faculty education leadership proactively identify recurring concerns rather than reacting to isolated complaints. The challenge is that the sheer volume and informality of posts make it difficult to identify patterns and themes.

We conducted a pilot project that automates the scanning of publicly available Reddit posts, uses generative AI to summarize discussions, and delivers regular digests to the faculty education leadership team. Importantly, the analysis does not track individuals but focuses only on aggregate patterns and recurring themes. The goal is not to use Reddit as a source of truth, but to treat it as a student-driven advice community that complements structured feedback channels such as end-of-semester course evaluation surveys.

Findings from the past year reveal consistent themes relevant to CS education: perceived course difficulty and comparisons, workload management, and concerns about assessment and results. Students appear to rely on Reddit as a crowdsourced community for choosing courses, navigating workload expectations, and coping with assessment pressures. By highlighting such patterns systematically, education leadership can move from reacting to isolated complaints to proactively identifying emerging concerns and misconceptions, particularly in large CS cohorts.

In this lightning talk, we will share lessons learned, focusing on how AI-driven summaries of informal student discourse can provide early signals that enrich existing approaches to student feedback in computing education.