Engineer shares fail-closed checklist for safely deploying AI agent fleets each week

A software editor at Stackyard has published a structured Monday checklist designed to prevent costly errors when deploying AI agent systems at the start of each work week. The checklist follows a fail-closed principle, meaning any missing, unvalidated, or unrecognized input causes the agent to stop rather than proceed with assumptions. Key steps include diffing and validating tool schemas, running dry-run tests before enforcement, canirying a single agent before fleet-wide rollout, and capping token and spend budgets before enabling parallel or coordinator modes. The guide also emphasizes treating tool outputs and web-fetched content as untrusted data, ensuring destructive tools require explicit human approval, and pinning model IDs to avoid unexpected provider-side defaults. The author argues that starting each deployment cycle with strict schema validation and defined refusal paths reduces surprise failures and makes outcomes defensible in team reviews.