OpenAI Codex for engineering teams
OpenAI Codex for Engineering Teams
Use OpenAI's coding agent locally, in the IDE and in the cloud, with clear rules.
OpenAI Codex is a coding agent that works in the terminal, in the editor and as cloud tasks that run in their own sandbox. We help teams set it up with AGENTS.md conventions, sensible approval and sandbox settings, and a review process for the pull requests it produces.
What we cover
- AGENTS.md conventions
- Approval modes and sandboxing
- Cloud tasks and environments
- GitHub code review
- MCP tool connections
- Team guidelines and training
Requirement-led advice · Documented handover
- Advice based on your requirements
- Works with your existing stack
- Documented, maintainable delivery
What Is OpenAI Codex?
Codex is OpenAI's software engineering agent. The open-source Codex CLI runs in your terminal, an IDE extension brings it into editors such as VS Code, and Codex cloud runs tasks in isolated containers that have your repository checked out, then proposes changes as a diff or pull request. Codex can also review pull requests on GitHub.
Codex reads AGENTS.md files for project instructions such as build and test commands and coding conventions. Approval modes decide whether it asks before editing files or running commands, and the sandbox limits what it can reach. Access comes through ChatGPT business plans or an OpenAI API key, which matters for billing and data controls.
When Codex is a good fit
- Your organisation already uses ChatGPT Business or Enterprise, or the OpenAI API.
- You want tasks to run in the cloud in parallel while developers keep working.
- You want one instruction file (AGENTS.md) that several tools can read.
- You need clear approval steps before an agent edits or runs anything.
Where Teams Use OpenAI Codex
Tasks that suit an agent working from a clear description. A developer reviews every result.
Well-defined features
Implement scoped changes with tests from an issue description.
Parallel cloud tasks
Run several small tasks at once in separate sandboxes.
Pull request review
An automated first review on GitHub pull requests.
Maintenance work
Dependency bumps, deprecations and small refactors.
Tests and fixes
Add tests and fix failing builds.
Codebase questions
Explain how parts of the system work.
Documentation
Keep READMEs and developer docs in step with code.
Scripts and automation
Write and update scripts, pipelines and tooling.
OpenAI Codex Services We Deliver
Each piece of work has a clear output, so you know what you will receive.
Pilot design
Pick repositories, task types and measures for a first pilot.
Deliverables: pilot plan, task catalogue, measures
Repository setup
AGENTS.md files with build, test and style rules.
Deliverables: instruction files, conventions guide
Cloud environment setup
Environments, setup scripts and network access for cloud tasks.
Deliverables: environment configuration, runbook
Safety settings
Approval modes, sandbox and secret handling for local and CI use.
Deliverables: settings baseline, usage policy
Review workflow
Pull request templates and review rules for agent changes.
Deliverables: PR templates, review checklist
Team enablement
Workshops on writing tasks and reviewing agent output.
Deliverables: training, team guidelines
Codex Features We Configure
What teams typically set up when adopting Codex.
Where it runs
- Codex CLI
- IDE extension
- Codex cloud tasks
- GitHub code review
Instructions
- AGENTS.md files
- Task templates
- Setup scripts for environments
Safety and access
- Approval modes
- Sandbox settings
- ChatGPT workspace controls
- API key and usage limits
Integrations
- GitHub repositories
- Model Context Protocol servers
- Non-interactive runs in CI
Listing a feature here does not mean every project uses it. We recommend what fits your requirements, skills, licensing and running costs.
How Codex Fits Your Stack
Codex works with common languages and test frameworks, and connects to other systems through Model Context Protocol. AGENTS.md is a plain Markdown file, so the same instructions can guide other agents your team uses.
For dedicated engineers who already work this way, see Hire OpenAI Codex Developers. If you are choosing between tools, compare it with GitHub Copilot, Claude Code and Cursor.
Implementation Considerations
- Decide early whether access is through ChatGPT plans or the API, because controls and billing differ.
- Give cloud tasks only the network access and secrets they need.
- Small, clearly described tasks give better results than broad requests.
- Keep human review and CI tests on every agent pull request.
- Write AGENTS.md with the exact commands to build, test and lint the project.
- Track which tasks work well and adjust guidelines monthly.
How We Work With OpenAI Codex
The same four steps we use across our technology work, adapted to your scope.
Discover
Goals, users, constraints and the systems OpenAI Codex must work with.
Select
Confirm OpenAI Codex is the right fit and agree the architecture and scope.
Build and integrate
Deliver in short iterations with testing, reviews and documentation.
Operate and improve
Monitor, support and improve the solution as your needs change.
OpenAI Codex Questions, Answered
What is OpenAI Codex?
OpenAI's coding agent, available as a CLI, an IDE extension, cloud tasks and GitHub code review.
What is AGENTS.md?
A Markdown file in the repository that gives coding agents project instructions such as build commands, tests and conventions.
Can Codex change code without approval?
That depends on the approval mode. We usually start with modes that ask before editing files or running commands.
Where do cloud tasks run?
In isolated cloud containers with your repository checked out. You control setup scripts and internet access for those environments.
How do we pay for Codex?
Through ChatGPT business plans or OpenAI API usage. We help you compare the options for your team.
Do you provide Codex developers?
Yes. See our Hire OpenAI Codex Developers page.
Bringing OpenAI Codex to Your Team?
Tell us about your repositories, tools and controls, and we will suggest a safe first pilot.
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