AI engineer agents can generate Terraform, Kubernetes manifests, and Dockerfiles at scale, but without sustainability constraints in the specification, they systematically reproduce over-provisioned infrastructure patterns. The post argues that sustainability must be a first-class constraint at the specification level — before agents generate a single line of IaC — rather than an operational fix applied after deployment. Three high-impact domains are identified: cloud resource provisioning (e.g., oversized GKE node types), Kubernetes pod resource requests (set to arbitrary safe values instead of measured p95 utilization), and container base image selection (full Ubuntu/Debian instead of distroless/Alpine). Enforcement is achieved through four pipeline stages: constrained spec generation, static analysis tools (Checkov, tfsec, KICS, Trivy), blocking quality gates in CI/CD, and runtime telemetry feeding back into constraint refinement. Practical starting steps include auditing existing IaC specs for sustainability defaults, adding a single blocking Checkov policy, and embedding constraints before agentic pipelines scale.
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