A developer describes a production incident in which a reported crash in a weekly attendance sheet appears, at first, to be caused by a single student contact record. After a teammate reports that the system fails with a “Cannot read properties of undefined” error for a specific child record, the developer initially considers applying a direct SQL update to fill in a missing last-name field. Instead, they run a broader database query to identify all related records exhibiting the same underlying pattern—contacts marked as “inscrit” with missing or empty first or last names. The query returns 16 matches, including two fully blank records and fourteen cases where first names were lost due to a legacy Airtable import that did not map one column. The developer argues that focusing only on the reported instance leads to repeated, isolated incidents and delayed fixes affecting other records. They recommend a sequence of questions before making changes: define the bug’s class as a predicate, measure how many instances exist in production, and ensure the proposed fix addresses the class rather than only the individual ticket. The post also notes that AI-assisted patching can reduce the perceived cost of skipping investigation, increasing the need for this disciplined widening step.