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, and they come with the subscription.
Which level you are at
Twenty-five questions that place your agentic workflow on the ladder. The ladder runs Level 0 to 5 and the scorecard puts you on 1 to 4, with a 30/60/90-day plan for the next rung. 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.