§ Guide · OpenAI Codex for teams
OpenAI Codex isn't autocomplete it's a parallel engineering colleague that picks up tasks in the cloud.
Codex is OpenAI's software engineering agent: it runs in an isolated sandbox, reads your whole repo, executes tasks in parallel and ships pull requests. Below: what Codex is, when to choose it, and how an Agentic Engineering team takes it to production.
01 — Definition
What is OpenAI Codex?
OpenAI Codex (the 2025 version, not to be confused with the older code-davinci model) is a cloud-based software engineering agent powered by codex-1, a variant of OpenAI's o-series specialised in code. It runs in an isolated container with a copy of your repository, executes tasks in parallel and delivers the result as a pull request or diff.
Codex comes in multiple surfaces: a web interface in ChatGPT, a Codex CLI for your terminal, a VS Code extension and a GitHub integration. The thread: you describe a task, Codex plans, executes, tests and reports back — without you approving every step.
02 — Architecture
Core concepts on one page
Cloud sandbox
Every task runs in an isolated container with restricted internet, a copy of your repo and the tools you configure. No access to your local machine.
Parallel tasks
You can fire dozens of tasks at once — each in its own sandbox. Codex works through them in parallel, ideal for refactors, expanding test suites or exploring multiple features at the same time.
AGENTS.md
The project file where you record conventions, build commands, testing strategy and code style. Codex reads it as a briefing for every task — comparable to CLAUDE.md for Claude Code.
Codex CLI
Open-source terminal tool to drive Codex locally. Works with OpenAI models, and with other providers via configuration.
Pull requests & reviews
Default output is a PR with diff, commit message and test results. Codex can also pick up tasks from Linear or GitHub Issues and ship them autonomously.
OpenAI Codex versus the alternatives
| Dimension | OpenAI Codex | Claude Code | Cursor |
|---|---|---|---|
| Primary surface | Cloud (ChatGPT, web) + CLI + IDE | Terminal-native CLI | IDE (VS Code fork) |
| Execution | Parallel in cloud sandboxes | Locally in your terminal | Locally in editor |
| Underlying model | codex-1 (o-series, code-tuned) | Claude Sonnet/Opus | Multi-model (Claude, GPT, Gemini) |
| Briefing file | AGENTS.md | CLAUDE.md | .cursorrules |
| Best use case | Async backlog work, parallel refactors | Deep interactive sessions on one problem | Pair programming, fast edits |
| Governance | Sandbox + PR review | Per-tool approval flow | Editor-level review |
03 — Application
When to choose Codex (and when not)
Use Codex
- Bulk refactors across many files where you want ten sandboxes running in parallel.
- Backlog work you want to handle async — letting Codex pick up issues from Linear/GitHub.
- Expanding test suites and bugfixes with clear acceptance criteria.
- Exploratory spikes: have five variants of an approach built simultaneously to compare.
Skip Codex
- Deep, interactive debug sessions where you want to walk the stack trace together — use Claude Code or Cursor.
- Codebases with heavy local tooling that doesn't fit the sandbox (custom hardware, GPUs, legacy DBs).
- Strictly confidential code that can't leave OpenAI's network — consider an on-prem alternative via OpenClaw.
04 — Operations
Production, governance and cost
Choose sandbox permissions deliberately
By default Codex has restricted internet access. We configure per project which domains, package registries and internal APIs are reachable — so builds succeed without opening a wide gate.
AGENTS.md as a contract
A good AGENTS.md contains build/test commands, naming conventions, lint rules and 'do not touch'. That's what lifts a first Codex PR from noise to usable.
Token and task budget
Parallel tasks burn cost fast. We set per-team budgets, model routing (codex-mini for triage, codex-1 for execution) and dashboards on actual usage.
Review discipline stays
Codex ships PRs — a human reviews. We set up branch protection, codeowners and eval suites so parallel agent output doesn't introduce silent regressions.
05 — Risk
Pitfalls we see in pilots
Vague tasks
'Improve the auth flow' produces ten PRs with ten interpretations. Codex performs as well as the task description — tight acceptance criteria are part of the job.
No AGENTS.md
Without a briefing Codex learns your conventions only after multiple PRs and review cycles. Write AGENTS.md before the first task.
Parallel merge conflicts
Ten sandboxes editing the same file produce unmanageable conflicts. Split tasks across files and domains before going parallel.
No evals
A PR that looks great isn't a PR that works. Build eval suites and CI checks every Codex PR must pass before review.
Our stance: Codex shines for parallel async work, Claude Code for deep sessions
We combine both. Codex handles bulk backlog work — refactors, test coverage, well-documented bugfixes — and ships PRs that a human or Claude Code finishes off. For deep interactive sessions on one problem, Claude Code remains our primary instrument.
The difference between a fun demo and a production-ready agent workflow always lives in the same places: clear task briefings, sandbox permissions, cost control, evals and branch protection. That's Agentic Engineering.
OpenAI Codex production-ready in your engineering team?
We help teams set up and harden Codex: AGENTS.md, sandbox config, budget dashboards, eval pipelines and — if desired — an on-prem alternative via OpenClaw for code that can't leave the network.
Frequently asked questions
Is Codex the same as the old 2021 Codex model?
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No. The old Codex was a code-tuned GPT-3 deprecated in 2023. Today's Codex (2025) is an agent platform powered by codex-1, an o-series variant trained specifically for software engineering tasks.
What's the difference between Codex and GitHub Copilot?
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Copilot is autocomplete + chat in your editor. Codex is an agent that picks up tasks autonomously, runs in a sandbox and ships pull requests. Copilot helps you type faster; Codex does work while you do something else.
Can Codex run on confidential code?
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Code goes to OpenAI's sandbox environment. For strictly confidential or regulated codebases that's often not allowed. We then offer an on-prem alternative via OpenClaw, where code and prompts never leave the network.
What is AGENTS.md and do I need one?
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AGENTS.md is a markdown file at the repo root with conventions, build/test commands and guidelines. It's the way to give Codex your project knowledge. Codex works without it, but with much more iteration and lower PR quality.