OpenAI Codex CLI: Everything you need to know about the terminal code assistant

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The emergence of artificial intelligence in software development has brought with it a new generation of tools that promise to revolutionize programming productivity. One of the most recent protagonists of this trend is OpenAI Codex CLI, a utility designed to operate directly from the terminal and provide, through AI, a new way to write, modify, and execute code assisted and conversationally.

In the following lines, we break down everything you need to know about Codex CLI, from its installation to its strengths, risks, and the context in which it was created. If you're looking to understand why this lightweight agent is already generating so much excitement among the developer community and how it integrates with OpenAI's latest advancements in models, here's the definitive guide to understanding and leveraging it.

What is OpenAI Codex CLI and what is its purpose?

OpenAI Codex CLI is a lightweight, open-source, terminal-based coding agent that allows users to interact with AI models to compose, edit, and execute code conversationally. As OpenAI explains, the goal is to provide a minimal and transparent interface for connecting advanced AI models—including the recent o3 and o4-mini—with local tasks and code in your own environment. If you'd like to dig deeper into how integrating AI models into development works, you can also visit our article on data processing in AI.

This CLI reflects the company's vision of the "agentic software engineer," a roadmap that aims to enable AI agents in the future to be able to receive a project brief and turn it into a working application, complete with tests. While Codex CLI doesn't quite achieve that level of autonomy yet, it represents a firm step in that direction, acting as an assistant that obeys high-level instructions from the console and responds with tangible actions on your files and development environment.

Installation and initial configuration: quick and without surprises

One of the strengths of Codex CLI is its simplicity of implementation: all you need is an OpenAI API key and three basic steps. First, it is installed globally with npm via the command npm i -g @openai/codex. Next, set your API key with a simple environment variable export. This can be done temporarily for that session or left fixed in your shell configuration file (e.g., ~/.zshrc).

The tool is developed with programmers accustomed to working in the terminal in mind, so it doesn't require advanced configurations or complex dependencies. In addition, it is cross-platform for Unix environments, although the use of WSL2 is essential on Windows.

The minimum technical requirements are:

• Operating system: macOS 12+, Ubuntu 20.04+/Debian 10+ or ​​Windows 11 (using WSL2)
• Node.js: version 22 or higher (LTS recommended)
• RAM: at least 4 GB (8 GB is suggested for smoother operation)
• Go: recommended to take advantage of collaborative functions

The security policy emphasizes: never use sudo npm install -g; it is best to fix npm permissions if necessary.

How Codex CLI Works: Modes, Key Commands, and Conversational Experience

Codex CLI is designed to be interacting with like a “smart” conversation with an assistant, but in the context of your own code. You can open an interactive REPL by simply running codex or start a session with an instruction so that the agent understands the context from the start, for example: codex "refactoriza el componente X a hooks".

The CLI incorporates different levels of autonomy, which you can adjust using the parameter --approval-mode (also abbreviated as -a):

• Suggest (suggest): default option, where the agent can read any file, but needs your explicit permission for changes and command executions.
• Auto Edit: allows you to apply modifications to files but requires validation to execute commands in shell.
• Full Auto: The agent can modify and execute commands automatically, always in a restricted environment and without an Internet connection.

This modular approach allows each user to decide how much control they relinquish to the agent, while still maintaining oversight and avoiding unexpected code crashes.

In practice, you can use Codex CLI both interactively and to execute specific instructions unattended (“quiet” mode), useful for automated tasks or integration into CI/CD pipelines.

Key capabilities: from refactoring to multimodal automation

Codex CLI extends the power of OpenAI models for common and advanced programming tasks, integrating reasoning, file manipulation, and secure command execution into a single conversational flow.

Among the highlighted functions:

• Refactor code and migrate components, for example converting classes into hooks in frameworks such as React, with immediate execution of tests and visualization of generated differences.
• Generate and execute SQL migrations adapting to your ORM and launching the scripts in isolated databases for security.
• Writing and iterative validation of unit tests, with self-correction until all tests are successful.
• Batch file operations, such as renaming images with Git commands, updating imports safely.
• Natural language explanation of complex code fragments, such as regular expressions or confidential algorithms.
• Automated security review, locating vulnerabilities and providing detailed reports on detected risks.
• Code evaluation and suggestions for high-impact PRs, helping to detect priority tasks within the repository.
• Supports multimodal inputs: You can send screenshots or diagrams so the agent can visually interpret a feature and translate it into code.

The ability to merge custom Markdown statements, both at the global level (~/.codex/instructions.md) as per project (codex.md), making it especially versatile for teams with specific standards or documentation preferences.

Security and isolation: protection against risks and bad practices

One of the most important concerns with generative AI tools is security. Codex CLI addresses this challenge with a strict enforcement policy and controls to minimize risk exposure.

By default, everything Codex CLI runs is done in an isolated environment:

• Without access to the internet: Even if any process tried to make an external request, it would be blocked.
• Limited to the working directory: can only read/write to the root of your repo and temporary directories.
• OS-specific sandboxing: on macOS use Apple Seatbelt (sandbox-exec), on Linux we recommend Docker with firewall rules that only allow traffic to OpenAI.
• Alert if the directory is not under version control with Git: from the CLI itself you will be notified so that changes are not lost or files are affected outside of secure areas.

Despite these mechanisms, OpenAI reminds that all AI-generated code should be reviewed before deploying in production environments, as studies confirm that these solutions can introduce bugs or propagate bad practices.

Current limitations and future vision

OpenAI makes it clear that Codex CLI is still in its experimental phase and its development is very active, so it is not a "closed" product nor is it free from bugs or disruptive changes. At the moment, it is not focused on generating software completely autonomously nor does it replace humans in critical review tasks.

The company is moving toward a future where tools like Codex CLI are the first step toward becoming a digital software engineer who can handle the full cycle of building, testing, and improving applications. In this context, human oversight remains essential.

Additionally, new command whitelisting features are in development to automate certain network-connected tasks and offer greater granularity for automatic approvals.

Compatible models and community contribution

Codex CLI is completely open source and looks forward to community input, including feedback, bug reports, enhancement requests, and code contributions. To this end, OpenAI establishes a clear contribution policy: changes must be atomic, documented, and accompanied by tests that verify their correct integration.

As for supported models, you can use any available through the Responses API, although o4-mini is used by default. If you want to learn more about how the , we recommend you delve deeper into this topic to optimize the use of models like Codex CLI.

To facilitate ecosystem growth, OpenAI has launched a grant initiative with up to $1 million in API credits, distributed in blocks of $25.000 to outstanding projects integrating Codex CLI. Evaluation is ongoing and provides teams with access to resources to develop plugins, integrations, and new features based on Codex CLI.

Competitive context and ecosystem expansion

The launch of Codex CLI coincides with a clear strategic move by OpenAI to position itself in the AI ​​coding assistant sector, taking on rivals such as Anysphere's Cursor or potential acquisitions such as Windsurf. The sector itself is experiencing a boom, with mergers, investments, and tool launches competing to offer the best assisted and secure programming experience.

The role of the o3 and o4-mini models is fundamental here: o3 represents OpenAI's biggest leap forward in reasoning to date (outperforming previous generations in math, coding, and visual understanding), while o4-mini seeks to balance cost, speed, and performance to democratize access to generative AI.

In addition, OpenAI is strengthening the security component of these models with monitors capable of filtering and preventing responses to requests that may pose biological or chemical risks, a further step in its commitment to responsible and ethical AI.

The ability to combine conversational instructions, image integration with multimodal reasoning, execution on local code, and support for open contributions make Codex CLI one of the most promising products for those who want to work hand in hand with artificial intelligence in everyday programming.

The rise of these technologies opens the door to a new way of building software, where humans rely on AI for repetitive or complex tasks, maintaining supervision and professional judgment. Codex CLI is, today, one of the most advanced and flexible tools if you're looking for that symbiosis without sacrificing control or security.