Apply responsible AI practices, understand data handling, configure policies and exclusions, and review generated output before use. In this scenario, focus on tracking artifacts from a multi-agent run, then verify the result from the source of truth and verify the security overview metric.

Paste regulated secrets into prompts to get more accurate suggestions. It may look faster for tracking artifacts from a multi-agent run, but it weakens maintainable automation and creates avoidable operational risk.

Accept generated code without validation because Copilot was trained on public code. It leaves duplicated workflow logic unresolved and does not use the security overview metric to validate the outcome.

Disable content exclusions when repository context is sensitive. It skips the required validation for tracking artifacts from a multi-agent run and provides no durable accountability.