Codex can now guess what you are about to type. On October 9, 2026, OpenAI began a beta of composer predictions in the Codex desktop app: after Codex responds, a suggested next message may appear in the input box, and pressing Tab moves it into the box so you can edit it before sending. It is limited to personal ChatGPT Pro users, is on by default, and costs nothing extra during the beta.
The feature is small, but it touches three things readers of this blog keep asking about: how much agent usage you burn, what a vendor does with your conversation history, and whether agents are turning into interfaces that talk to themselves. Below is what OpenAI's own release notes say, how it compares with the similar Claude Code feature we covered last week, and a short checklist for trying it.
TL;DR: questions people are asking
| Question | Answer |
|---|---|
| What does it do? | Suggests your next message from the current Codex thread; Tab puts it in the box. |
| Does it send for me? | No. You review or edit, then send. |
| Who gets it? | Personal ChatGPT Pro users, 18 and older, all supported regions, latest Codex desktop app. |
| Which threads? | Local and SSH threads using GPT-6 Astra or GPT-6.1 Sol. |
| Is it on by default? | Yes. Off switch: Show predictions in Composer, under General settings. |
| Does it cost usage? | Not during beta. Predictions do not count toward limits or use credits; sent messages still do. |
| Is it trained on my usage? | The release notes do not say; check your data controls. |
| Shown after every reply? | No. The notes say a suggestion "may appear". |
What exactly did OpenAI announce?
The release notes entry dated October 9 describes composer predictions as a beta that "suggests your next message based on the conversation in your current Codex thread." Two details matter for planning. First, the model restriction: it works on threads using GPT-6 Astra or GPT-6.1 Sol, the models we compared in GPT-6.1 Sol versus Astra cost efficiency. Threads on other models will not show suggestions. Second, the surface restriction: local and SSH threads in the desktop app, not Codex Cloud tasks and not Chat in the browser.
Where does this sit in the Codex desktop app?
Context helps here. OpenAI's Codex changelog records that on July 9, 2026 Codex became part of the ChatGPT desktop app on macOS and Windows, alongside inline Markdown and code editing and PR Chat for reviewing GitHub pull requests. Earlier entries show the composer itself being extended step by step, for example local branch search and non-image file pasting added on April 20, 2026. Composer predictions continue that pattern: the message box is where most of the interaction happens, so each change there affects every session. The changelog page we read does not yet list predictions, so the release notes remain the only primary source for this beta.
How do I use it, and how do I turn it off?
- Update the Codex desktop app to the latest version.
- Start or open a local or SSH thread on GPT-6 Astra or GPT-6.1 Sol.
- After Codex replies, look for a grey suggestion in the message box. It may not appear after every response.
- Press Tab to accept. The text lands in the box; edit it freely.
- Press send when you are ready. Nothing is sent by accepting.
- To disable it, open Settings, then General, then the Composer section, and turn off Show predictions.
The "review before sending" design is the right call for a coding agent. A wrongly predicted "yes, go ahead and delete the migration" is a different risk than a wrongly predicted word in a chat. Because acceptance only fills the box, the human gate that matters, the send, stays in your hands. If you want a similar discipline elsewhere, our guide to Codex Auto-Review covers the other side: letting a reviewer agent reduce approval prompts.
What does it cost?
For now, nothing beyond what you already pay. OpenAI says that during the beta, generating predictions does not count toward Codex usage limits or consume credits. The messages you send, including accepted predictions, count normally.
That wording leaves the post-beta picture open. OpenAI has not said whether predictions will keep being free, count toward limits, or move to other plans. Given how often usage rules have shifted this month, as in our coverage of Pro 200 usage allowances changing, treat "free in beta" as a time-limited offer.
What about privacy and training data?
This is the question most likely to follow any "predicts how you talk" feature. The release notes describe the suggestion as based on "the conversation in your current Codex thread", but say nothing about whether that data is used for model training. We could not find an official OpenAI statement on that point in the notes, so check your account's data controls and OpenAI's current policy.
The same question came up around a rival product days ago. We covered a claim that Claude Code's suggested messages were training data and Anthropic's denial in Are Claude Code's suggested messages training data?. The pattern is useful: whenever a product predicts what you will type, users reasonably assume it learned from what you typed, and the vendor needs a clear public answer. For Codex predictions, OpenAI's notes leave the question open.
A hand placing a green pebble into one of two consent bowls, representing choices about how conversation data is used
How does this compare with Claude Code's suggestions?
Both products now offer a suggested next message you can accept with a key press. The visible differences from what is public:
- Availability: Codex's is a Pro-only beta on the desktop app; check Anthropic's documentation for Claude Code's current rollout.
- Scope: Codex limits it to local and SSH threads on two named models.
- Cost statement: OpenAI explicitly says predictions are free of usage charges during the beta.
- Data statement: OpenAI's notes are silent on training; Anthropic's denial is covered in our linked post.
We have not benchmarked the two. How often the suggestion is what you actually wanted, and how often it saves time, is exactly what a beta is for, and independent hands-on reports will matter more than either announcement.
Why it matters beyond the keystrokes
A next-message predictor looks like autocomplete, but in an agent workflow most of your messages are short approvals and redirections: "yes, continue," "run the tests," "use the second approach." If the model can predict those, the loop between you and the agent tightens. That sits next to the larger OpenAI push toward agents that act more on your behalf, such as dots on mobile and in Codex, and the daily-improvement commitment we covered in Codex's 28 days of updates with its day-by-day log.
The risk is habit. If Tab becomes the default answer, you may start approving things you did not read. Keep the suggestion for low-stakes continuations, and write your own message for anything involving deletes, deploys, credentials or money.
Is it worth leaving on? A practical way to decide
Treat the first week as an experiment instead of a default. Predictions are on by default, so you will start seeing them whether or not you chose to, and the useful question is whether they change your outcomes. A simple test: for five working days, keep a tally each time a suggestion appears, noting whether you accepted it as-is, edited it, or ignored it. If you accept or lightly edit more than about a third of them, the feature is saving real typing. If you mostly ignore them, they are visual noise and the off switch is one click away.
Pay attention to which kinds of messages get predicted well. Short continuations such as "continue," "run the tests again," or "commit this with a clear message" are the best case, because the right answer is obvious from context. Messages that carry new information, like a design decision or a constraint you have not mentioned yet, are the worst case, since the model can only guess from the thread.
Also consider your review habits. Teams that already require a human to read agent diffs before merge lose little by letting Tab fill in routine replies. Solo developers working on production systems late at night are the people for whom a quick Tab is most likely to wave through something unread. If that is you, turn predictions off for sessions that touch infrastructure.
Finally, watch the usage meter. Because predictions are free but the messages you send are not, a tool that makes sending easier can raise your consumption on plans where Codex limits are already tight. The settings detail is in the release notes.
What is still unknown
- Whether predictions will stay free after the beta, and which plans will get them.
- How the model is personalized, beyond "your conversation and how you talk to it."
- Whether Codex Cloud tasks will ever get predictions.
- Independent accuracy numbers: none published so far.
Details reflect OpenAI's October 9, 2026 release notes and public posts, and may change as the beta evolves.