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Free Cloud AI Workflow Checklist
A practical checklist for reviewing AI-generated cloud infrastructure output before it reaches production. Catch what AI gets wrong in Terraform, AWS, Kubernetes, and GitHub Actions.
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WHAT’S COVERED
Stop Shipping AI Output You Haven’t Reviewed
This checklist gives you a systematic review process for AI-generated cloud output — so you catch problems before they reach production.
Validate provider versions, check state backend configuration, review resource naming, verify module inputs and outputs, catch missing required tags, and flag potential state drift issues.
Review IAM policies for wildcard actions and resources, check for overly permissive roles, validate security group rules, review S3 bucket policies, and verify encryption settings.
Check for missing resource limits and requests, verify liveness and readiness probes, review security contexts, validate RBAC configurations, and flag missing namespace isolation.
Review for hardcoded secrets and credentials, check OIDC authentication configuration, verify secret scanning steps, validate permissions scoping, and review third-party action pinning.
Verify rollback procedures exist, check for environment-specific configuration handling, validate secrets management approach, review monitoring and alerting coverage.
Flag obviously over-provisioned resources, check for missing auto-scaling configuration, review data transfer patterns, and catch common cost traps in AI-generated AWS architecture.