Codex Can Now "Copy" Your Tasks

2026-06-23 · Source: Matt Wolfe · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Robotics & Autonomous Systems · Depth: Fundamental Awareness, quick

Summary

OpenAI has introduced a "record and replay" feature for Codex, enabling the AI to observe and learn computer tasks directly from user demonstrations. This functionality allows users to record a video of themselves performing an action, after which Codex can replicate those steps on demand. For instance, a user can demonstrate uploading a YouTube video, including selecting files, adding a thumbnail, and attaching subtitles. Once learned, the user can then provide new video, thumbnail, and subtitle files to Codex via a chat interface, instructing it to "Upload this YouTube video using the YouTube upload skill." Codex will then autonomously execute the exact sequence of steps, such as selecting files, uploading them, and setting privacy to private, streamlining repetitive digital workflows.

Key takeaway

For automation engineers or power users seeking to streamline repetitive digital workflows, OpenAI's Codex "record and replay" feature offers a direct path to custom automation. You can now create bespoke automation skills simply by demonstrating a task once, eliminating complex scripting. Consider integrating this visual learning capability to rapidly build tools for content management, data entry, or other routine computer operations, significantly reducing manual effort.

Key insights

OpenAI's Codex can learn and automate complex computer tasks by observing user demonstrations, creating reusable skills.

Method

Record a task video; Codex learns the steps and creates a skill. Later, provide new inputs and command Codex to execute the learned skill.

In practice

• Automate repetitive digital tasks.
• Create custom skills from demonstrations.
• Streamline content uploads (e.g., YouTube).

Topics

• OpenAI Codex
• Task Automation
• Record and Replay
• Skill Learning
• YouTube Uploads
• Digital Workflows

Best for: Machine Learning Engineer, AI Product Manager, Product Manager, AI Engineer, Automation Engineer, Software Engineer

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Editorial summary, takeaway, and curation by AIssential. Original article published by Matt Wolfe.