Claude Code vs Codex CLI: how we use both AI coding agents together

Nov 1, 2026 · updated Nov 1, 2026 · 6 min read

Claude Code (from Anthropic) and Codex CLI (from OpenAI) are both AI coding agents that run in your terminal: they read your project, edit files and run commands. We use both every day. Here is what each is like in practice, and why we often make them check each other's work.

These tools change quickly. This comparison reflects our own use as of November 2026; check the official docs for current features.

What they have in common

• Terminal agents: you describe a task in plain language; the agent explores the code, proposes changes and runs commands.
• Permissions and sandboxing: both ask before risky actions or run inside limits you set, such as “may write only inside this folder”.
• Project instructions: both read a guidance file in the repository (for example CLAUDE.md or AGENTS.md) so they follow your team’s rules.
• Extensible: both can connect to external tools through the Model Context Protocol (MCP).

Where Claude Code fits well for us

• Long, multi-step work: planning a feature, editing many files, running tests and fixing what fails, while keeping track of the whole task.
• Working with the browser and apps: through its Chrome integration it can operate web pages, which we use to set up and check our own sites.
• Orchestration: it can split work across sub-agents and follow project rules strictly.

Where Codex CLI fits well for us

• Quick non-interactive runs: codex exec "..." is handy in scripts: give it a task, let it write the result to a file, done.
• Second opinion: it is a different model family, so it notices different things.
• Generating assets: in our setup we used it to generate images such as thumbnails and channel banners as part of a pipeline.

Our favourite trick: let them review each other

For anything important (a script, a plan, a security fix) we let one agent create it and the other review it independently:

1. Claude Code writes the first version.
2. Codex reads it with a clear brief: “find factual errors, unclear parts, risky claims”.
3. We merge the useful feedback and keep what we disagree with, with a reason.

Two different models make different mistakes, so cross-review catches problems that a single agent misses. It is the same idea as a human code review.

Which one should you use?

Practical tips for either agent

• Put your rules in the instructions file: coding style, commands to run tests, things never to touch.
• Keep secrets out of the repository and out of prompts.
• Review every change before you merge it. Agents are fast, not infallible.
• Start them in a sandboxed or limited-permission mode until you trust the setup.

Sources

• Claude Code documentation (Anthropic)
• Codex CLI repository (OpenAI)

Written with AI assistance, then checked and edited by a human engineer. Found a mistake? Tell us.