Claude Code for Infrastructure as Code: A Practical Guide
· via Spacelift
Why this matters now: This is the piece closest to what this site is about. IaC is a good match for coding agents because plans give you a review gate before anything applies, and this guide turns that observation into a full working model for Claude Code against a Terraform estate. It is specific where most agent content stays vague: real CLAUDE.md examples, real permission rules, and an honest section on where the tool breaks, from context limits on large codebases to mishandled secrets.
Three takeaways:
- The mental model is a strict split between drafting and deploying. The agent’s job ends at the diff. Every change travels through a pull request and CI before production, and the operator who merges stays accountable for the result. Nothing the agent writes reaches infrastructure without a human in the merge path.
- Start with the boring work: module generation, splitting monolithic configs, updating deprecated syntax, writing tests and OPA policies. Small scoped changes are easier to review and cheaper to roll back when the agent hallucinates a provider argument, which it still does on less common resources.
- Guardrails come in layers. CLAUDE.md carries repo conventions, permission rules deny apply and destroy while allowing fmt and validate, hooks run scanners and validators on every edit, and OS-level sandboxing sits underneath. Gruntwork develops the same idea into six defense layers, and the two pieces read well together. For reaching cloud APIs and live context, the article leans on MCP servers instead of handing the agent raw credentials.
What I’d add today: Figure out how to use AI coding assistants safely within your IaC workflows. The tools are here to stay and will only get better.
Who should read it: platform engineers who want to try an agent against a Terraform estate without gambling production on it. Give the agent plan-only permissions first and let it earn trust per repo, the same way a new team member would. When the agent itself becomes the workload, deploying it with IaC is the follow-up read.