Keep ego out of it and focus on craft improvement.
Good response pattern
1. Assume positive intent 2. Ask clarifying questions 3. Fix or discuss trade-offs with data 4. Thank the reviewer 5. Encode the lesson (lint rule, checklist, test)
STAR outline
Situation: Reviewer flagged my Spark job for collect() on a large DataFrame.
Action: I agreed it was risky, rewrote to keep transforms distributed, added a note in the PR, and put "no collect on prod-sized data" on my personal checklist.
Result: Safer job; I later caught the same issue in a peer's PR.
Fresher tip
Professor/TA/GitHub classroom feedback counts.
Interview tip: Don't trash the reviewer. Don't pretend you never get comments.