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OpenAI expands its Codex desktop app with background computer use, in‑app browser, image generation and new plugins, now available on Windows and macOS.
OpenAI announced a major update to its Codex desktop application, adding the ability for the AI to control a user’s computer, generate images, and integrate a growing set of plugins. The rollout begins for Windows and macOS users signed in with a ChatGPT account, though the new “computer use” feature is limited to macOS for now [1].
Key takeaways
The update transforms Codex from a pure coding assistant into a broader productivity companion. Developers can now run multiple Codex agents in parallel, schedule long‑running tasks, and reuse prior conversation threads so the AI retains context across days or weeks [1]. A new summary pane displays agent plans, sources and generated artifacts, while the sidebar offers file previews for PDFs, spreadsheets, slides and documents. Support for GitHub review comments, multiple terminal tabs, and early‑stage SSH connections to remote devboxes further extend its developer‑focused toolkit [1][2].
Codex desktop is now available on both Windows and macOS, with Windows users gaining a native agent sandbox that leverages OS‑level controls such as restricted tokens and dedicated sandbox users to run safely in PowerShell environments [3]. The “computer use” capability—where the AI can operate applications in the background—is currently limited to macOS, and the feature is not yet offered in the EU or UK [1][2]. Memory and context‑aware suggestions, part of the previewed memory feature, will initially roll out to enterprise, education and EU/UK users at a later date [1].
By allowing the AI to interact directly with the operating system, OpenAI blurs the line between code generation and full‑workflow automation, potentially reducing the need for custom scripts or API integrations. The addition of native image generation and a growing plugin ecosystem positions Codex as a more versatile tool for developers seeking end‑to‑end assistance. However, the platform‑specific limitations and the need for careful token management suggest that widespread adoption will depend on how reliably the new features perform in real‑world workflows.
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