Prevent double-processing by generating stable keys from unique fields like email plus date, or a file checksum. Check if a record already exists before creating a new one. Normalize text, trim spaces, and sanitize user inputs. When possible, upsert instead of blindly inserting. Store a brief run history to reconcile edge cases. Clear deduplication rules eliminate embarrassing repeats, reduce cleanup work, and make the behavior easy to explain to stakeholders who value consistency over surprise.
Build a small test harness: representative sample data, edge cases, and a clean rollback plan. Run through empty fields, invalid formats, rate limits, and permission changes. Add descriptive step names and inline comments so intent survives future edits. Capture screenshots or logs for before-and-after comparisons. Test failure paths deliberately, not just the sunny day. Document expected outputs in plain language, so a teammate can verify functionality without guessing, especially when deadlines loom and confidence matters most.