Can Codex Create and Edit Videos?

Codex's day job is a simple loop of reading a project, editing files, and running a command. A demo video fits that loop, as long as the video is plain files and something can render them.

Getting there depends less on the prompt than on the setup underneath. Codex needs a project format it can edit, a renderer it can run, and a sign-in and environment that line up. Once those are in place, the prompt is the easy part.

This post sets that up on Windows, macOS, and Linux, using CoAnimator for the project format and the renderer. It starts with a five-second test, then covers a brief that holds up and the review steps I would keep.

Can Codex make videos on its own?

No. Codex CLI is a coding agent that runs in your terminal: it reads a project, edits files, and runs commands. None of that is a video renderer, so it needs a project format it can edit and a renderer it can run.

CoAnimator supplies both. A video is stored as plain project files, a stage updates as they change, and a command-line tool called coa renders the MP4 on your machine. Since it is ordinary files, Codex works on it the way it works on code: read, edit, run, look at the result. The alternative is having Codex write for a code-based framework such as Remotion, which means building and maintaining the preview and render stack yourself.

This is not always worth it. For one video you will publish once, a screen recorder is faster. The setup pays off when the video has to change, because a changed video becomes an edit instead of a re-record. Codex will also animate whatever you hand it, including a stale screenshot, so the story and the accuracy stay your job.

Set up Codex CLI and CoAnimator

Setup is terminal work, so this assumes you are comfortable with npm and PATH. The steps follow CoAnimator's docs as I read them on 2 November 2026. CoAnimator updates often, so a menu name or flag may differ from the docs. If it does, trust what your app shows. Keep everything in one environment. On Windows, a tool installed inside WSL may be invisible to the native app that launches Codex, so for a first run I would stay on the Windows side. OpenAI's Windows guide covers both native PowerShell and WSL2.

1. Install CoAnimator

Download the build for your system. The macOS installer is Apple Silicon, Windows is 64-bit, and Linux is chosen by distribution and processor. The docs list macOS 13 or later. The editor is free to use and does not require a CoAnimator account. Then open Settings → Media tools and prepare FFmpeg and FFprobe, which rendering depends on.

2. Install Node.js and Codex CLI

Install an LTS release from the Node.js download page; npm comes with it, and CoAnimator's Settings → Media tools can install Node too. Node is needed for the npm install of Codex and for the adapter in step 3. In a fresh terminal, check both:

node --version
npm --version

In PowerShell, use npm.cmd --version for the second line. Then install Codex and sign in:

In PowerShell, plain npm resolves to a .ps1 wrapper that the default execution policy blocks, and the .cmd launchers avoid it (npm's tracker has the history). Command Prompt accepts the plain names. OpenAI's own docs now lead with a standalone installer that needs no Node, and list npm and Homebrew as alternatives. This post uses npm because CoAnimator's docs do and its adapter needs Node anyway. Pick one route so you do not debug two copies.

CoAnimator reads the Codex CLI's sign-in from ~/.codex, whether it came from a ChatGPT plan or an API key, so the CLI itself needs to be installed. CoAnimator's Codex page documents this. Never paste credentials into a brief.

3. Connect Codex inside a project

Open a blank project or a template and choose Codex in the agent picker. The app sets up a small adapter between Codex and CoAnimator, which is why Node and npm have to work. If the connection fails, rerun the version checks in a fresh terminal and restart CoAnimator.

4. Install the skill and the coa command

Open Settings → General → Command line & agent skill. There are two installs, and neither includes the other. The skill teaches Codex the project format; choose Codex CLI and it lands in ~/.agents/skills/coa-cli/ (under %USERPROFILE% on Windows). The coa command does the rendering. Start a new Codex session afterwards.

Check the command with coa --help (coa.cmd --help in PowerShell). On Windows the installer adds a per-user coa.cmd to your PATH, with no admin rights or WSL needed. coa ships with its own runtime, so Node matters only for the Codex install and the adapter.

Now verify the FFmpeg and FFprobe from step 1. If they are on your PATH, ffmpeg -version and ffprobe -version should print. Otherwise FFMPEG_PATH and FFPROBE_PATH point CoAnimator at them.

5. Run a five-second smoke test

Before any assets or script, ask Codex to read the skill, find the current project, and create a five-second scene with one heading. Check the stage, then render from the folder that contains the project's project.json. If you do not know where that is, ask Codex for the project path, or pass the project ID instead of the dot:

coa render . --out ./smoke.mp4

On Windows PowerShell:

coa.cmd render . --out .\smoke.mp4

The dot means the current folder. This is the video version of a hello-world, and I think it earns its place. If it fails, the cause is a missing command, the wrong environment, or a project Codex cannot find, and none of those involve your prompt or your assets.

Write a brief Codex can't misread

Three things to settle before the brief.

Assets. Name each file for what it shows, such as config-before.png or watch-rebuild.mp4, so every scene points at one file. Scrub terminal recordings for tokens, hostnames, and home-directory paths, and cut dead air. Use real recordings for anything that claims a feature works. Generated imagery is fine for decoration you cannot capture, but invented interface footage proves nothing. Then ask Codex to describe each screenshot before it builds. I could not confirm how the Codex connection handles images, so a wrong description is cheaper to catch here than in a caption.

Standing rules. For a series, write colors, caption style, length limits, and wording down once instead of repeating them in every brief. OpenAI's AGENTS.md guide says Codex reads a global file from ~/.codex, then files from the project root down to the working folder, with closer files taking precedence. A starting point for an AGENTS.md in the project folder:

Use the logo and font files that are already in the project.
One main message per scene.
Use real product screenshots for interface details.
Keep text away from the frame edges.
Hold screen movement still while a label is being read.
Ask before replacing an approved asset or changing the script.

Add your color values, font names, and output dimensions, then ask Codex to quote the rules it loaded. I could not confirm which folder a session starts in, so that check also tells you whether the file was found.

Format. State the aspect ratio up front. A vertical cut needs tighter crops and fewer words, so treat it as its own layout pass. A project can hold several timelines, which lets it sit beside the 16:9 cut.

Now the brief. Take a made-up example: a CLI is shipping a --watch flag, and you have three screenshots, a 15-second terminal recording, and the release notes. A good brief names the assets, the scene order, the closing line, and a checkpoint:

Build a 30-second demo of the new --watch flag. Use the three screenshots and the terminal recording in the project media. Open on rebuilding by hand after every edit, show the flag being enabled in the config, then show the terminal rebuilding on its own after a file save. Close on the line "Stop re-running the build." Share the scene plan and wait for my approval before building.

The last sentence matters most, because a plan is cheaper to fix than a built cut. Read it against the real product. Suppose the release notes say --watch while the recording shows -w. That mismatch needs an answer before Codex writes captions and narration, because a wrong fact copied into three places is tedious to find again.

A 30-second plan could look like this:

Treat the timings as a draft. Read the narration aloud against the recording at real speed, and if something will not fit, cut a secondary point before compressing the main action. A script that reads at 35 seconds against a 30-second target needs shorter narration and retimed scenes, because trimming the last five seconds cuts the closing line instead of the excess. Generated narration comes from a plugin, and plugins carry their own sign-in or API key.

Before the full build, ask for one still frame and approve it as the visual reference for the rest. After that, give timing feedback in plain terms:

Show the config screenshot a second earlier and keep the terminal output hidden until the narration reaches the rebuild.

Review in layers, then render

Watch the rough cut before polishing motion. This order avoids polishing a scene you later cut:

1. Story. Can a viewer follow the action without a feature list? Cut any scene that does not advance the workflow.
2. Layout. Is the key label readable at the size viewers will see?
3. Motion. Does movement point at the next action? Keep the screen still while there is something to read.
4. Sound. Is the narration clear? Keep music under speech, and keep a licensed track's license with the project.
5. Export. Does the MP4 match the approved preview? Play the file outside the editor and check text, missing assets, audio, aspect ratio, and the last frame.

Render previews with the smoke-test command and a new --out name, and watch the MP4 rather than the stage. When a scene needs changing, name it and protect the rest:

Replace the second scene with the new config recording. Keep the opening and closing as they are, adjust the narration to match, keep the total under 30 seconds, render a new preview, and list what you changed.

Then compare the two exports: right asset, only the named scenes changed, time left to read the result. CoAnimator's docs say project files diff like source code. If your project folder is in git, commit before each revision. git diff then gives you a second way to confirm Codex touched only what you asked, though how readable that diff is depends on the project.

To re-check just the scene you changed, render a range. The values are seconds, and the end is exclusive:

coa render . --start 5 --end 17 --out ./scene2.mp4

Use coa.cmd the same way in PowerShell. Final exports use the same command, and the CLI reference covers flags such as --resolution and --quality.

Privacy and cost

Rendering happens on your machine, but the model behind Codex does not. Your prompts go to the model provider, and CoAnimator's licensing page says images, video frames, and files supplied to an agent may be sent too. Keep video work in its own folder, send only assets you are allowed to share, and read the permission prompts before allowing unattended edits or commands.

Cost can come from up to three places: Codex access through a ChatGPT plan or API key, any audio or generation plugin, and a CoAnimator license. Free exports use a 720p short side and carry a CoAnimator watermark. A valid paid license unlocks higher resolutions and removes the watermark. Local exports are not metered by CoAnimator credits. For a customer-facing video, check which tier your final render will use before you build around it.

Fix common setup and export problems

Debug from the bottom up: command, path, project, then prompt. A reworded prompt will not fix a missing executable.

Next steps: re-render instead of re-record

The payoff of a video made from files is the second version. When the UI changes, the fix can be a pull request instead of a re-shoot, which matters most for teams whose interface moves every sprint. Keep the first demo as the template and let later versions change only the content scenes.

The step beyond that is scheduling. CoAnimator's docs describe a cron job where an agent reads the week's merged pull requests and coa render runs at the end, with the CLI exiting 0 or 1 like any build step. Its changelog-video page sketches the pipeline with a person still pressing publish. Its docs list no hosted render workers, so scheduled renders would run on your machine or on a CI runner you set up. I would review the first several outputs by hand before letting a model with file access run on a schedule.

If you try the smoke test, I would like to hear where your setup broke first, especially on Windows with WSL in the mix. Post it in the comments and I will add it to the troubleshooting table.