DevOps and platform engineers
AI coding tools for DevOps and platform engineers
DevOps is where AI coding agents stop being an editor feature and become a pipeline step. All three run headless, emit structured JSON and support scheduled automations, which makes them usable in CI — and makes sandbox policy and hooks the guardrails that matter, because there is nobody present to approve anything.
What actually changes
Approval prompts stop protecting anything. An interactive session has a person deciding whether a command runs; a scheduled one does not, so what a command can reach has to be decided in advance by sandbox policy, and what must happen every time has to be a hook rather than an instruction.
Structured output becomes the difference between a CI step that can branch on a result and one that can only log it. Both Claude Code and Codex emit JSON on request.
Recipes for your stack
These are documentation pages. Some are free to read; the rest are part of the subscription.
Where you stand
Twenty-five questions on how production-grade your AI engineering is, with a plan at the end. Free, no account.
Frequently asked questions
How do you run an AI coding agent in CI?
Claude Code takes claude -p "task" with --output-format json; Codex takes codex exec "prompt" with codex exec --json; Cursor exposes CLI, SDK and Cloud Agents. All three also support scheduled automations.
What stops an agent doing damage in an unattended run?
Not approval prompts — there is nobody to answer them. Sandbox policy decides what a command can reach, and hooks run checks the agent cannot skip. In Codex those are two separate settings, which is the distinction worth configuring deliberately.