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OpenAI Codex Adds Digital Memory, Screen Recording as Core Productivity

OpenAI Codex Adds Digital Memory, Screen Recording as Core Productivity

July 22, 2026
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OpenAI has introduced a notable feature called "Chronicle" for its Codex application. It records screen activity in the background, building a comprehensive "memory library" for the AI. This allows Codex to have a perspective similar to a human colleague, understanding in real time the specific projects users are working on, the tools they use, and their current progress. In later interactions, users no longer need to repeat lengthy context, as the AI accurately understands their intent based on this "digital memory."

Technically, Chronicle demonstrates a high level of automation. Once activated, it runs silently in the background, with an internal agent analyzing and organizing recorded screen content, extracting concise summaries, and saving them as Markdown files on the user's local device. To balance efficiency and storage, these files are temporary; according to official statements, the system automatically deletes them six hours after generating the memory.

Chronicle feature in Codex interface

Currently, this advanced feature is available as a preview for ChatGPT Pro subscribers on macOS. Eligible users can go to the "Personalization" option in settings, enable "Memory" and "Chronicle" in sequence, and grant the necessary screen recording and accessibility permissions to start using it. However, due to local privacy laws, it is temporarily unavailable for users in the EU, UK, and Switzerland.

While Chronicle greatly boosts collaboration efficiency, its potential risks are worth noting. The official release includes a reminder: due to frequent data processing, it will consume the user's usage quota faster. More importantly, there are security concerns—memory content is stored locally without encryption, and displayed web content may contain malicious instructions, so users should be wary of prompt injection attacks. This feature, balancing convenience with complex security boundaries, marks an important step for AI from "instruction response" to "environmental perception."

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